Curtailment-storage-penetration nexus in the energy transition

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Applied Energy journal homepage: www.elsevier.com/locate/apenergy

Curtailment-storage-penetration nexus in the energy transition ⁎

T

A.A. Solomon , Dmitrii Bogdanov, Christian Breyer Lappeenranta University of Technology, Skinnarilankatu 34, 53850 Lappeenranta, Finland

H I GH L IG H T S

nexus is shown with detailed techno-economic data. • Curtailment-storage-penetration optimal curtailment is part of the least cost balancing options. • An storage and penetration simultaneously increase during the transition. • Curtailment, feasibility of specific storage options depends on the observed nexus. • Techno-economic • The observed nexus defines when to deploy and dispatch a particular storage option.

A R T I C LE I N FO

A B S T R A C T

Keywords: Curtailment Diurnal storage Seasonal storage Penetration Curtailment-storage-penetration nexus Dispatch order

The nexus between growing shares of renewables (penetration), storage requirements, and curtailment was studied using a linear optimisation model. The study was performed using a dataset of Israel’s electricity system. Five scenarios are designed to assess the techno-economic impact of curtailment under various policy-based frameworks. The results show that the three parameters are linked to each other in a way that necessitates simultaneous increase of a total loss (curtailment plus storage efficiency), penetration and storage capacity in the energy transition. Depending on the curtailment policy, penetration increases significantly with a small increase in storage capacity until it reaches a corresponding point of inflection. Based on these physical relationships, storage technologies were classified as diurnal and seasonal. Diurnal storage capacity continually increases to a maximum capacity of about daily average demand, which corresponds to a penetration of approximately 90% of annual demand where the deployment of seasonal storage significantly increases. Having no curtailment was shown to lead to higher total system cost as compared to the system optimised with curtailment. Overall, the nexus between the three factors was shown to define when to deploy and dispatch storage technologies. The evidence supporting these findings is detailed for the first time.

1. Introduction Transitioning to very high Renewable Energy (RE) systems is under way even if it is at a slow pace. The agreement to reduce greenhouse gas (GHG) emissions at the 2015 United Nations Climate Change Conference [1], COP21, provides further drives to increase the effort towards low-carbon energy future. At the same time, as massive deployment of new Renewable Energy (RE) technologies continue its cost competitiveness improves. For instance, studies forecast continued PV capacity growth [2] that will lead to continual cost reduction [3] and

increased role to change the future energy system [4]. Despite difference in expected cost reduction from location to location [5], there is a universal agreement on the promising future of PV technologies [6]. Similar cost reduction was forecast for Batteries [7] as well as PV and Wind [8]. As a result, the global RE intake [9] as well as its competitiveness [10] is improving. At the same time, their role in global energy mix [11] and the resulting levelized cost of electricity [12] is /will be/ improving year by year. Furthermore, techno-economic feasibility of low-carbon energy system is widely reported by several researcher’s for various parts of the world, e.g. Israel [13], Macedonia [14], India [15],

Abbreviations: A-CAES, Adiabatic Compressed Air Energy Storage; CCGT, combined cycle gas turbine; CSP, Concentrated Solar Thermal Power; CHP, combined heat and power plant; DES, desalination; CO2eq, CO2-equivalent; COP21, the 21st conference of parties; GT, gas turbine; GHG, greenhouse gases; HHB, hot heat burner; IEC, Israel Electric Corporation; (I)NDC, (intended) nationally determined commitments; LCOE, levelised cost of electricity; OCGT, open cycle gas turbine; PHS, pumped hydro storage; PtG, power-to-gas; PV, photovoltaic; RE, renewable electricity; ST, steam turbine; TES, thermal energy storage; UNFCC, United Nations Framework for Climate Change; WS, Water Security ⁎ Corresponding author. E-mail address: solomon.asfaw@lut.fi (A.A. Solomon). https://doi.org/10.1016/j.apenergy.2018.11.069 Received 16 May 2018; Received in revised form 17 November 2018; Accepted 19 November 2018 0306-2619/ © 2018 Elsevier Ltd. All rights reserved.

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Australia [16], Finland [17], Northeast Asia [18], Portugal [19], Denmark [20], United States [21], global [22], western electricity coordinating council [23], Turkey [24], Saudi Arabia [25], etcetera. Currently, many agree that a RE future is a possibility both technically and economically [26]. Fossil and nuclear fuels are also losing ground in some markets to RE [27]. Moreover, the shares of Variable Renewable Energy (VRE), such as wind and solar PV, in the energy market are increasing globally. With the reported increase in VRE penetration comes also a report of certain challenges, such as curtailment, related to its intermittency depending on the energy system structure [28]. The foregoing energy system transition studies and the one reported by Greenpeace [29], IEA [30], shows continued increase in the use of renewables and storage technology. The reported contribution of RE to the total energy need, as well as the corresponding dominant resource and technology, depend on the focus of the studies in terms of geographic location, target year and various assumptions related to technology costs and policy. Though there are significant variations regarding the detail of the findings, the overall conclusion shows that an increasing use of VRE resources, such as wind and solar PV, is inevitable. However, an increased use of VRE is regarded with concern in the power industry due to the challenges that comes with its variability [28]. The key challenges to achieve large-scale use of VRE are threefold, namely:- (i) matching the VRE output to the load profile; (ii) adding a fluctuating resource to an electro-mechanical system designed to handle an already fluctuating load; and (iii) uncertainty to forecast VRE output. In a series of studies focussed on assessing matching challenges of VRE output to the Israeli power system and the associated solutions, phenomena such as curtailment with [31] and without [32] storage, increased grid dispatch flexibility [33], resource distribution [34] as well as complementarity of wind and solar [35], were investigated in order to increase grid penetration. Notice that the percentage share of the total annual electricity demand supplied by direct VRE output plus storage discharge is defined as penetration. These studies showed that depending on a target penetration, a various mix of these phenomena would be necessary. In a separate paper [36], the authors also showed that curtailment not only increases penetration but also increases the use of storage resources and as a result reduces the required storage capacity. Another multi-node study investigating the role of storage design [37] and resource complementarity [38] for California’s grid also reported similar results with additional new sets of findings such as the ability to reduce balancing need using curtailment. In agreement with them, studies performed for other geographies suggested a mix of solutions such as demand response as well as curtailment and storage [39], variety of flexibility options in general [40] and including those suitable for power quality control [41], excess energy curtailment [42], increased load following capability [43], increased use of vast geographically distributed resources [44], complementarity of wind and solar [43], improved forecasting [45] as well as the use of energy storage technologies [46], in order to increase the uptake of VRE by the energy system. Curtailment was also found to reduce storage and balancing need for the European system [47], whose optimal values also depend on the use of a resource mix and other factors [48]. Studies assess the role of multiple tools such as electric mobility and storage [49], and a broader mix of technologies [50] and varying system sizes [51]. In [37], energy storage is shown as a key enabler for high VRE penetration. Studies examining the role of storage have reported a relationship between the required storage capacity, total energy loss (loss due to storage efficiency plus curtailment) and VRE penetration using datasets of the Israeli [32] and Californian power system [37]. The total energy loss does not include losses related to other factors than curtailment and losses incurred during the storage charging and discharging processes. Due to an inherent relation between the two types of losses (to be detailed later), the nexus between the three parameters will be examined by using total loss as a substitute for curtailment while providing specific information about the corresponding curtailment. In studies reporting high penetration of VRE through the use of

storage, three important lessons emerge. First, designing the required electricity storage based on seasonal and diurnal matching of renewables and load profile is very important [32]. Storage enables higher grid penetration by transferring the stored electricity to later times of insufficient generation. To effectively handle the storing need at a time of VRE excess generation and supply at a time of insufficient generation, it is required to model the proper storage time dynamics while achieving time synchronicity between load and VRE output [37]. Second, if storage is to be optimally designed for a certain amount of high VRE penetration, it is important to allow some curtailment in order to avoid limiting the use of the storage resources that are built [36]. Because of this, storage requirement and curtailment are shown to partly substitute each other [52]. Specifically, at a given amount of VRE penetration, high curtailment was shown to require smaller electricity storage capacity and vice versa. This is because of the role curtailment plays in increasing VRE penetration. As detailed in the case of Israel [36] and California [37], at higher penetrations curtailment enables better matching by increasing storage utilisation. The third lesson relates to sizing the required storage system for a given purpose [32]. Unlike many conventional generators, which are reported in terms of one dimensional parameters (namely power capacity), energy storage system size should be reported with two dimensional parameters, namely storage system power capacity (kW) and energy capacity (kWh), or one of them plus the corresponding hours of storage, also called the energy-to-power ratio [37]. An optimal system design includes proper identification of storage technology type and characteristic, its location in the network, and its specific power and energy capacity [37]. This is challenging because of the requirement for several abstract parameters to correctly characterise storage technologies, uncertainties related to operational policies as well as pricing of the future grid. As discussed in [52], present models vary in a number of ways in modelling energy storage. As a result, it is difficult to clearly show the relation between total energy loss, storage capacity requirement and RE penetration. The above studies detailing the case of Californian [37] and Israeli grid [36], show that the three increase simultaneously. At the same time, several transition results, for instance [24], suggests the same without paying much attention to its significance. As a result, the magnitude of the necessity of the link between these parameters were never clear because it was considered simple phenomenon. Furthermore, there is a tendency to consider storage as a full substitute to curtailment despite evidence that indicates that the two could complement each other [52]. Moreover, even though the number of modelled storage technologies and their representation may affect their comparative importance regardless of their cost, currently little is known about factors that define the storage deployment and dispatch order. However, there seems to be global agreement that energy storage is needed and RE penetration will continuously increase as we press forward in energy system transition efforts. Thus, a novel approach that will clarify the relation between total energy loss, energy storage requirement, and grid penetration of VRE and its role during the energy transition is required. The important questions of interests include:

• How does the storage technology mix and capacity requirement relate to VRE penetration? • What is the economic opportunity/penalty of allowing curtailment? • What are the factors that will define storage deployment and dispatch order?

In Solomon et al. [38] and Heide et al. [47], curtailment was shown to have technical benefits in reducing both storage and balancing capacity needs at certain amount of VRE penetration. This suggests that some economic benefit may also be found. On the contrary, other researchers treat curtailment as a mere waste of energy [53]. This is in spite of various studies, discussed above and those analysing various results for Europe [54] and wider geographic regions [55], that report 1352

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curtailment as a part of least cost optimisation result. This research will present for the first time empirical data that shows that an optimally designed energy system with curtailment costs less than the one designed without curtailment. Together with the first set of these scenarios, a compelling theoretical explanation of the novel “curtailmentstorage-penetration nexus” concept will be presented to clarify the scientific base for the observed techno-economic benefit of curtailment. On top of this, Ref. [56] argued that system level issue need to be considered when developing energy technologies. This is particularly important when model results are much dependent on assumed cost [57] and varieties of other considerations [58]. This paper will bring forward key techno-economic parameters that policy makers could use to assess system level suitability of various technologies during energy transition. This study uses a dataset of Israel’s electricity system. The choice was made because of the smaller size of Israel’s system, which provides the opportunity for a detailed study of the subject in question using a system that has several characteristics typical of many other countries as detailed in [13]. Moreover, studies evaluating the link between VRE penetration, energy storage requirement and total energy loss exist for this system.

implementing a 5-year time step sequential optimisation during the transition from the present system to the aspired 100% RE system. This was done while enforcing a requirement that various technologies built over the transition period are fully amortised. This model ensures that an hourly output of all generation and storage technologies supply the demand for electricity at each hour of the year. Generation technologies in this model include a mix of the present day conventional fossil fuel generators and RE technologies. The RE technologies in the model include static tilted PV, north–south single-axis tracking and rooftop PV, concentrating solar thermal power (CSP), both onshore and offshore wind generators, hydropower systems with or without a dam, power plants running on biogas and solid biomass, as well as geothermal power plants. In addition, 5 storage technologies, namely lithium ion batteries assumed to serve as residential and system storage, pumped hydro storage (PHS), adiabatic compressed air energy storage (ACAES), thermal energy storage (TES) and gas storage, are included in the model. Power-to-Gas (PtG) technologies such as water electrolysis, methanation, CO2 direct air capture, gas storage, and both combined and open cycle gas turbines are part of the synthesis of synthetic natural gas (SNG) and its reconversion to electricity. The PtG technologies have to be operated in synchronization in the charging mode because of the assumed absence of hydrogen and CO2 storage. For systems that have resources for biogas production, the model employs a 48-hour biogas buffer storage, and part of the biogas can be upgraded to biomethane and introduced to the gas storage. The time synchronicity between VRE and load is suitable to satisfy the requirements discussed in [37], but the Energy-to-Power ratio limitation applied for storage technologies, following an approach that seems to be a tradition in this area [51], could limit the storage design flexibility. However, the LUT model can be considered as one of the advanced hourly resolution optimisation tools to study how to transition to a net zero greenhouse gas (GHG) emission energy systems. This model was also used to study the coupling of sectors such as desalination [59] and non-energetic industrial gas [60] to the power sector. The objective of the LUT optimisation model is to minimise the total energy system costs, which is framed as a sum of the annualised capital expenditures of the different technologies, as well as operational expenditures of the system. The other important feature of this model is the possibility of estimating a prosumer market potential during system planning. This is done by applying an exogenously defined mini-transition hourly model, which installs rooftop PV and battery systems for residential, commercial and industrial customers. This mini-transition optimisation tool also minimises the cost of consumed electricity for potential prosumers. The key inputs of the present research is the same as the input to the decarbonisation policy scenario result given in [13], to which readers interested in more details are referred. A short summary is given below.

2. Problem formulation and model This section presents brief information on the methodology and various assumptions. The specific inputs related to Israel are similar to those given in [13], which is based on the present energy system of that country and its present and future policy directions [13]. This section provides a brief summary of the model, assumptions and the details of the relevant scenarios. 2.1. LUT energy system transition model and data The research was carried out using the LUT Energy System Transition model, which is developed by researchers at Lappeenranta University of Technology and referred as the “LUT model” in this paper. In the following, a brief summary of the LUT model is given. It is a linear optimisation tool developed to examine how to transition the present hydrocarbon based energy system to a 100% RE system by the year 2050. Fig. 1 presents a simplified block diagram showing the model’s various components and the related flow chart. More detail regarding the model is given in Bogdanov and Breyer [18] and Breyer et al. [22]. This optimisation tool achieve time synchronicity between the demand profile and VRE output throughout the year by optimising on an hourly time scale. The computational burden of modelling largescale energy systems on an hourly resolution was overcome by

Fig. 1. Simplified Block diagram and the flow model of the LUT Energy System Transition model [18]. 1353

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potential underground CO2 emission storage capacity in the southern region [63]. Using the structure as A-CAES and gas storage rather than for storing CO2 may be of long-term national benefit to Israel. As a result, large storage capacities were assumed for both technologies in this region. If the technologies are cost competitive, batteries as well as TES technologies can be built in all regions. The existing total transfer capacities of the transmission interconnections between sub-regions were estimated based on 2015 model results together with a thorough comparison of the results against the data given in IEC, 2010 [61]. Other important input data are the regional load profiles for each of the five sub-regions. The electricity consumption of each sub-region over 2010 was given in IEC, 2010 [61]. The corresponding data for 2006 [64] shows that each sub-region’s annual share of the total demand of the country changes little from 2006 to 2010. As a result, the 2010 consumption shares of each sub-region were utilized to estimate the sub-regional profile from the national load profile of IEC in 2011. Future demand was forecast by assuming a 2.7% annual increase, a rate assumed by the Government of Israel, by considering the reduction in the rate of demand growth subject to its energy efficiency policy [65]. 2.2. Scenarios and the nexus In order to examine the evolution of the power system with regards to the progress in VRE penetration and the related requirements on storage capacity and total loss, it is important to create scenarios that involve some diversity. The diversity of the scenarios should provide various rates of increase in VRE penetration amount as well as its dependence on curtailment, with some of the scenarios enforcing full RE penetration by 2050. Thus, a total of 5 scenarios, which are summarised in Table 1, have been developed. The scenarios aimed at clarifying how storage requirement, energy system penetration of VRE and curtailment are related. To evaluate fast transition scenarios, a GHG emission cost for two corresponding transition scenarios was applied. Alternatively, scenarios that model the transition based on the projected technology cost alone are also included. To identify any opportunities/penalties related to curtailment, two curtailment conditions were applied to both scenarios. The remaining scenario presents the case of a Current Policy (CP) scenario of Israel. This paper starts by studying the impact of these scenario variations on the power system transition. Then, it proceeds to perform a systematic analysis of the data in order to understand how the relationship of the three parameters, namely curtailment, storage capacity and VRE penetration, resulted in the observed differences, which is termed the curtailment-storage-penetration nexus. This systematic analysis will be done by exploring the relationship between the parameters independent of time. The calculation of VRE penetration and curtailment is in agreement with what is used for Israel [36] and California [37]. 3. Results 3.1. Factors affecting the power system transition In order to discuss the physical relationship of curtailment-storagepenetration, it is important to begin by analysing how these factors are interrelated in the energy transition and their related socio-economic implication to the energy transition. Fig. 3 presents the Levelised Cost of Electricity (LCOE) during the transition period for the five scenarios defined above. For the scenarios with carbon cost, Fig. 3a and d, LCOE slightly increases until 2025, then it starts to gradually decrease. The high cost in 2025 is basically due to an increase in capital expenditures (capex) in new capacities, specifically in solar PV and batteries as compared to the previous years, and the high cost of GHG emissions in that year. The cost decreases of the subsequent years are due to the significant decreases in fuel and GHG emission costs that resulted from an increased investment in cheaper RE technologies. Similarly, the two transition scenarios without carbon

Fig. 2. Israel Electricity Company sub-region map with simplified transmission interconnections between them. This map, found in IEC, 2010 [64], is not a political boundary map, thus includes the two regions of the Palestinian Authority (namely West Bank and Gaza).

To model the power system, Israel plus the Palestinian regions have been grouped into 5 sub-regions based on the district map of IEC found in [61]. The corresponding utility sub-region map is given in Fig. 2. The technical details of the Gilboa pumped hydro storage project, which is currently near its completion, is given in [62], which is assumed to come online in order to support the system based on the assumption given in [13]. All other storage technologies were modelled based on the specification typical of the model. Israel has 50 years’ worth of

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Table 1 Name and description of scenarios included in this study. Name

Description

Base Case (BC)

This scenario anticipates the use of carbon emission cost in the form of direct tax, carbon trade rules or other indirect means. The assumed effective cost of GHG emissions per ton of CO2eq is expected to increase from 9 € in 2015 to 28, 52, 61, 68, 75, 100 and 150 € at each 5-year time step until 2050. To enable easy comparison of the result with others, these carbon cost values as well as all other input data (except the specific numbers related to Israel that are discussed above), are set to a value typical of the LUT model. This scenario usually represents the fastest transition. The curtailment amount in this scenario is set based on what the model evaluates as optimal The nationally determined commitment of Israel provides specified key targets for electricity generation [63,65]. The intended RE (to be sourced mainly from wind and solar) share for 2020 is 10% of its annual electricity demand. The share of RE is planned to be increased to 17% of the annual demand by 2030 [63,65]. The post-2030 share of RE is not clear, but, in the present study, a generous increase in RE penetration of 1%/year was assumed. Due to this limit, the maximum PV prosumer market potential was reduced from 20% to 7% for this particular case. More detail on the present policy of the country can be found in [61], which also provides the justification for the assumption regarding fossil power plants. Current practices suggest that the use of coal decreases [73] while reliance on natural gas increases. At the same time, despite uncertainties over the construction of nuclear power plants in Israel1, evidence suggests that nuclear power plants are given consideration for the post2030 period [61]. After analysing this evidence, it was assumed that the first nuclear power plant of 500 MW is built by 2030, with another 1 GW and 1.4 GW being built in 2035 and 2050, respectively, as in [61]. Based on the present national and international initiatives, the possibility of using direct or indirect carbon pricing to achieve the aspired emission reduction is high. Thus, the Current Policy scenario applies the same carbon cost value as in the BC scenario. The curtailment amount is not constrained Unlike the BC scenario, the NCC scenario assumes that the GHG emission cost in the electricity sector is set to zero during the transition. Consequently, the NCC scenario does not strictly ban fossil fuels by 2050. All other assumptions are similar to the BC scenario. As presented in the results, because of the close similarity of the result of this scenarios to that of the BC, carbon cost between the two ranges studied in these scenarios were ignored in this study. The curtailment amount is not constrained This is similar to the BC scenario. However, unlike the BC scenario, curtailment is limited to approximately 0.1% throughout most of the transition. Arriving at an optimal solution by limiting curtailment was challenging at higher penetration. Thus, all post 2040 runs were performed at a relaxed curtailment limit of 0.2% This is similar to NCC scenario. However, unlike NCC scenario, curtailment is limited to approximately 0.1% throughout most of the transition. Arriving at an optimal solution by limiting curtailment was challenging at higher penetration. Thus, all post 2040 runs were performed at a relaxed curtailment limit of 0.2%

Current Policy (CP)

No Carbon Cost (NCC)

Base Case without Curtailment (BCWC)

No Carbon Cost without Curtailment (NCCWC)

To use nuclear power, Israel should import technologies and fuel. This is permitted only between signatories of the Nuclear Non-Proliferation Treaty (NNPT), which Israel did not sign.

cost given in Fig. 3b and e show the same LCOE trends as one another and with the corresponding LCOE of the transition scenarios with carbon cost when the GHG emission cost are excluded. However, note that the fuel cost in the transition scenarios without carbon cost were not zero by 2050 because these scenarios do not ban fossil fuels by the target year. By comparison, the highest LCOE values for scenarios without carbon cost (Fig. 3b and e) were observed in 2015, which shows that working for solar PV conducive policy may lead to less expensive electricity services. The similarity of the overall trends observed in Fig. 3a, b, d and e shows that all of these scenarios lead to similar transition paths. The difference between the corresponding scenarios with and without carbon cost is simply the emphasis on fast transition. The application of carbon cost leads to higher VRE penetration (to be detailed latter) as compared to the corresponding scenarios without carbon cost, which is also the reason for its slightly higher LCOE even when the GHG emission cost is ignored. Despite the evidence that favours solar conducive policy for a transition to cleaner energy systems, Fig. 3c shows that the current policy works to the contrary. Fig. 3c differs from the other scenarios in two ways. First, the LCOE for all years except 2015 and 2020 was higher than the corresponding LCOE values reported for all other scenarios. Note that the cost remains higher even when the comparison is made by excluding GHG emission costs. Second, LCOE was found to increase with time, unlike other scenarios, resulting in higher LCOE by 2050. The increase is driven by both GHG emission cost incurred due to continued reliance on fossil fuels and the relatively expensive energy system that is comprised of costly nuclear power plants. Returning to Fig. 3c, notice that the cost shares of PV and batteries remain low by 2050 as compared to the other scenarios. The highest VRE penetration in this scenario is approximately 35.2% by 2050. This research focuses on studying the detailed relation of VRE penetration, total loss (curtailment plus loss related to energy storage efficiency) and storage requirements. A detailed study of the corresponding GHG emission reduction policy and transition issues was presented in Solomon et al.

[13], which could give more detail on the impact of socio-economic policies and desalination sector coupling to electricity as part of the energy system transition. The result, as summarised here for the sake of completeness, shows two important policy lessons. First, Sun Belt countries, such as Israel, can speed up their transition to a RE system without the need to apply a GHG emission cost. However, these countries should alternatively promote a policy that encourages the use of solar PV and battery storage in order to achieve the fastest rate of PV system cost reduction, as the PV and battery storage markets depend on local policy. The overall policy target should also be frequently revised to take advantage of the cost competitiveness of PV and batteries. The implementation of such a policy could achieve a comparable decarbonisation effect as applying GHG emission cost, with the possibility of reaching 100% RE with small extra cost added on to that of the NCC by year 2050. Second, embracing a pro solar PV and battery storage policy also brings a cheaper and faster decarbonisation alternative as compared to the CP. Notably, it was found that the power system transition will also be affected by other factors, such as curtailment policy. After this, the focus will be on examining the impact of curtailment policy on the power system transition. Returning to Fig. 3, a comparison can be made of the corresponding scenarios with and without curtailment. The LCOE for the two scenarios without curtailment given in Fig. 3d and e were found to be higher than the corresponding years’ LCOE values presented in Fig. 3a and b. Specifically, LCOE values for the BCWC scenario in 2045 and 2050 were 10.3% and 8.6% higher than for BC. Similarly, the LCOE for NCCWC is 8.5% and 8.4% higher than the NCC scenario, respectively, for the same years. The significant cost increases for the scenarios without curtailment run contrary to the intuition that curtailment is a simple waste of energy. 3.1.1. Total loss and VRE penetration by scenarios In order to understand the cause of the cost difference, it is instructive to study other technical results in more detail. Fig. 4 presents the corresponding VRE penetration, total loss and curtailment for the 1355

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Fig. 3. A change in LCOE for (a) BC; (b) NCC; (c) CP; (d) BCWC; and (e) NCCWC scenarios of the power system transition from 2015 to 2050.

five scenarios. Fig. 4a shows how VRE penetration changes from now up to 2050. As clearly seen in all cases, grid penetration of VRE increases. The fastest increases occur for the two scenarios with GHG emission cost, regardless of differences in curtailment policy. These scenarios arrive at a VRE penetration value of approximately 95% of the annual demand or higher by 2040 as compared to the approximately 97% penetration value achieved by the two NCC scenario by 2050. Initially, with the exception of CP, all scenarios show a similar increasing trend but the increase takes a separate path after 2025. The NCC scenario keeps the same increasing trend up to 2045, when it starts to level off. This is

because the last few percentages of VRE penetration require more storage, making it a little more expensive, but not too expensive as can be seen from the comparative cost of electricity (Fig. 3) in 2050 for the BC scenarios. Limiting curtailment has a more pronounced impact on the NCC scenario, which is reflected by the lower VRE penetration corresponding to NCCWC up to the year 2040 that diminishes after 2040. The VRE penetrations for the NCC scenarios are 96% and 95.3% of the annual demand of the year 2045 with and without curtailment, respectively, which becomes 97% of the annual demand by the year 2050 in both cases. Notice that the scenarios related to the BC arrive at the same VRE penetration amount in the year 2045 and 2050. This

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Fig. 4. Trends of (a) VRE penetration and (b) energy loss (both total and curtailment) for all scenarios. Due to the existing inflexibility, the loss as a percentage of total VRE was much higher for all scenarios in 2015. For that particular case, loss is given as a percentage of total generation.

shows that the observed cost deviation results from other effects of the curtailment policy. The slow increase in VRE penetration, observed for the CP scenario is a simple reflection of the limited target of the CP of the nation, but the data corresponding to this scenario provide important information to explain the impact of energy system inflexibility. Fig. 4b presents the energy losses corresponding to penetrations given in Fig. 4a. For all scenarios except the CP, the total loss and curtailment increase from 2015 to 2050. The increase in total loss depends on the scenario. The difference in total loss of the BC and NCC scenarios is mainly due to the corresponding VRE penetration, which mainly leads to different amounts of curtailment. The two no-curtailment scenarios have a relatively lower total loss due to the obvious influence of the applied no curtailment policy. Note that curtailment continually increases for the scenarios that allow it. Though the increase in curtailment for the BC scenario shows some occasional decrease (for example from 2040 to 2050), it did not lead to a proportional decrease in total loss. This is because the loss due to storage efficiency increased during that same period showing the substitutional effect between curtailment and storage loss. For the no-curtailment scenarios, the figure clearly shows that curtailment remains very low (due to the applied limit) but the total loss increased from 2015 to 2050 as usual. The close correspondence of the total loss and the storage loss curve for the no-curtailment scenarios shows that the increase in total loss is driven by the increase in storage loss. Comparing the storage loss for scenarios without curtailment to the corresponding scenarios with curtailment (given in the same Fig. 4b), it can be seen that the storage loss significantly increased for the scenario without curtailment due to the increased reliance on storage to reach higher penetration, reinforcing the observed substitutional effect of losses. Because of this effect between the losses, the total loss did not decrease by an amount proportional to the avoided curtailment. However, note that the total loss is significantly lower than the corresponding total loss reported for the case with curtailment. This substitutional effect of losses shows the importance of discussing the total loss as defined in this paper and in Solomon et al. [37] perhaps with specific information on the amount of the corresponding curtailment. The presented loss trend of the CP scenario is significantly different. This will be explained in Section 3.2 in more detail. The reported increase in storage loss also shows that under both

scenarios without curtailment, a rise in VRE penetration is achieved through increased energy storage service. However, why, regardless of the reduction in total loss, did LCOE not decrease? The answer may relate to the increased storage service discussed above, because increased storage service does not mean increased utilisation of the same resources. Due to the no-curtailment limit, as discussed in Solomon et al. [36], the option to increase energy system VRE penetration is to increase storage capacity but at lower utilisation. This is clearly shown in the generation and storage capacity requirement given in Figs. 5 and 6 in the upcoming subsection, respectively. Before proceeding to that, it is important to state that “curtailment” is not a mere energy loss but a technical option that provides flexibility to increase energy system penetration of VRE. It gives the system an option to avoid the load following or storing requirement that would otherwise be necessary to enforce a strict load and generation balancing, which are to be provided by no other technologies than storage in the scenarios without curtailment.

3.1.2. Role of various technologies by scenarios Fig. 5 presents capacity requirements for the scenarios given in Fig. 4. As can be seen from this figure, except for the CP, the technology mix of generation capacities for all scenarios gradually changes from a fossil dominated system in 2015 to a solar PV dominated system by 2050. The PtG technology, CCGT, and OCGT in the 2050 system fully becomes part of the gas storage system, and involves burning the stored SNG for the scenarios with carbon cost. However, for scenarios without GHG emission cost, approximately 2% of the annual demand will be obtained from fossil natural gas. Returning to comparing scenarios without curtailment (Fig. 5d and e) to the corresponding scenarios with curtailment (Fig. 5a and b, respectively), it can be seen that the PV capacity in the corresponding year and scenario was lower for the scenarios without curtailment while technologies related to gas storage, such as PtG (labelled as methanation in the figure), increased significantly. This change comes as a logical response to the limit on curtailment where the model managed to reduce PV capacity (that would otherwise contribute to curtailment) but achieved almost the same amount of VRE penetration by storing energy from the remaining PV generators. This relationship suggests that the economically optimal amount of curtailment depends also on the relative cost of VRE and 1357

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curtailment lead to two significant differences that can be seen by comparing to the corresponding scenarios given in Fig. 6d and 6e. First, the year-to-year increase in storage technology requirement is fast and significant for scenarios without curtailment. Specifically, the total energy storage capacity by 2050 increases from approximately 11 TWh in BC to about 15 TWh in the BCWC scenario and from 6 TWh in NCC to 11 TWh in the NCCWC scenario. While the dominant increase is mainly due to an increase in the gas storage capacity, an increase in battery storage was also observed. The battery capacity increased by 9.8% from approximately 255 GWh for BC to about 278 GWh in the BCWC and by 14.5% from 242 GWh for NCC to 277 GWh for NCCWC in the year 2050. Notice that the presence of various storage technology options in the model enabled the deployment of various technologies according to their suitability while keeping the cost still at a minimum level under all given constraints. Second, the limit on curtailment has forced an earlier and increased viability of gas storage as opposed to the one observed in the corresponding scenarios with curtailment. For scenarios without curtailment, significant gas storage capacity is built already in 2030 and 2035 for the BCWC and NCCWC scenarios, respectively, as opposed to 2035 and 2045 for the BC and NCC. This difference clearly shows that the connection between VRE penetration and storage requirement depends on the curtailment policy. This occurs because the limits on curtailment force the model to start transferring energy seasonally. As a consequence, it builds larger, low-capex gas storage capacities. In the upcoming subsections, it will be shown that the techno-economic viability of a given storage technology depends on the storage capacity, VRE penetration and curtailment nexus. This phenomena also shows that gas storage starts to contribute to the energy delivery as early as the corresponding years. In summary, it can be stated that the difference between the scenarios results from a scenario’s ability to manoeuvre the physical link between curtailment, storage and VRE penetration to fulfil its objective, a subject to be discussed later. Overall, one can state that all transition scenarios initially emphasise more efficient energy storage that is required to transfer the daytime PV generation to satisfy nighttime demand. As a result of the imposed low PV penetration, the storage need for the CP scenario is significantly smaller. In the end, note that despite its large capacity, gas storage is not economically suitable for frequent use due to its low round-trip efficiency, as can be seen from its low energy contribution given in Fig. 7. Fig. 7 demonstrates that the most dominant source of stored energy was obtained from the most efficient and high-capex energy storage technology, which is battery storage. This is because of the relatively low levelised cost of storage (LCOS) resulting from its relatively high storage utilisation. However, gas storage, which contributes a lower share of the stored energy, is suitable in a seasonal energy transfer role due to its ability to provide cheap, large energy storage capacity. It can be seen that gas storage starts early energy transferring services for scenarios without curtailment (Fig. 7d and e) as described above. In comparison to scenarios with curtailment (Fig. 7a and b), the energy contribution of gas storage significantly increases when the no-curtailment policy is enforced. Note that still gas storage supplies approximately 7% of the annual demand in the highest case, which is in BCWC 2050, as compared to close to a 48% share of the battery output for the same condition. The energy contribution by each generation technology is presented in Fig. 8. In agreement with the change in the generation technology mix shown in Fig. 5 and other factors described above, Fig. 8 shows that the electricity generation mix changes from the presently fossil fuel dominated one to a RE dominated system over time. For further details on differences between corresponding scenarios, readers are referred to the Supplementary material, specifically to Figs. A1–A4 and related discussions. Despite the reduction in PV capacity and the corresponding electricity generation when curtailment is limited, LCOE rises as compared to the corresponding LCOE for scenarios with curtailment. This is because when curtailment is limited, the system needs a larger storage

Fig. 5. Change in capacity mix for (a) BC; (b) NCC; (c) CP; (d) BCWC and (e) NCCWC scenarios of the power system transition from 2015 to 2050.

storage technology and their relative mix. The increase in PtG technology enhances the ability to store more energy using gas storage. Note that due to the aspired policy the capacity mix in Fig. 5c changes in a significantly different way. Fig. 6 resents how the corresponding energy capacity of the storage technologies increases. Fig. 6 presents other significant differences between these scenarios. Fig. 6 clearly shows that, depending on scenarios, storage requirements increase in terms of the required capacity and technology mix from 2015 to 2050. In the early years the model builds the most efficient storage technologies, such as batteries (PV prosumer batteries appear first, with utility-scale batteries coming later) but in later years (starting year depends on scenario), technologies, such as gas storage, start to appear in larger capacities. Regardless of their similarities in trends, the rate of increase in storage capacity and technology mix as well as the time for techno-economic viability of some technologies such as gas storage significantly depend on the scenarios. For example, the BC scenario (Fig. 6a) needs higher storage capacity as compared to NCC (Fig. 6b), due to its requirement for a faster increase of VRE penetration. Consequently, it builds large gas storage to transfer energy seasonally much earlier, a process that appears to be started late (by 2045) and in small magnitude in the NCC scenario. However, the limits on 1358

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Fig. 6. Energy storage requirement by technology for (a) BC; (b) NCC; (c) CP; (d) BCWC; and (e) NCCWC scenarios of the power system transition from 2015 to 2050.

capacity to provide the flexibility needed to achieve comparable VRE penetration. Thus, the assumption that curtailment is a simple waste of energy is just intuitional. Previous studies [52] have shown that curtailment increases energy system penetration of VRE with a reduced need for storage and conventional balancing capacity. In the present study, economic opportunities induced by these technical advantages are seen. However, because this is a transition model, it is not possible to show how curtailment reduces the balancing requirements of conventional technologies, which retire depending on their lifetimes.

However, the overall reduction of conventional fuel demand and capacity is clearly presented in the scenarios with and without curtailment. Now, it is instructive to enquire how the preceding scenarios may have affected transmission line requirements. In order to study this difference, transmission capacities between the five nodes and their utilisation in 2050 are presented in Table 2. Transmission utilisation is the ratio of the total bidirectional power transfer throughout the year to the maximum theoretical transfer (capacity × 8760). Even if there are 1359

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Fig. 7. The share of demand sourced from electricity output of various storage options for (a) BC; (b) NCC; and (c) CP; (d) BC and (e) NCCWC scenarios of the power system transition from 2015 to 2050.

always differences between each scenarios on transmission build up given in Table 2, the comparative difference between the pair of scenarios with and without curtailment is very significant. The scenarios without curtailment lead to significant transmission increase, particularly for the North to North Western interconnection (please see Fig. 2 for the interconnection map). This may be due to the balancing challenge that is created in the North Western corner when curtailment is avoided. As a result, the system should transfer power from the southern region at times of stress using this transmission line, which

also has lower utilisation. In the present study, the interconnection was defined following the present high voltage line. However, future studies should provide more detail with better flexibility of the transmission build up. It should also be noted that a push for no curtailment also carries more risks of supply reliability to some regions in addition to higher cost. The CP scenario builds conventional generators in each node in order to reduce transmission capacity need. As a result, it should be seen separately. The preceding discussion shows that VRE penetration, total loss and

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Table 2 Electricity transmission capacity under different scenarios for the year 2050. Scenario names

Region 1

Region 2

Capacity [GW]

Utilisation [%]

VRE penetration [% annual demand]

BC

Northern

North Western Southern Southern Eastern

1.5

54

99.5

4.5 1.4 5.7

62 27 43

North Western Southern Southern Eastern

5.4

11

4.1 1.6 5.4

52 34 32

North Western Southern Southern Eastern

1.2

66

4.2 1.8 6.3

71 30 56

North Western Southern Southern Eastern

5.4

13

3.9 1.4 5.9

62 31 26

North Western Southern Southern Eastern

0.5

13

1.1 1.4 6.9

25 36 48

Northern Tel Aviv Southern BCWC

Northern Northern Tel Aviv Southern

NCC

Northern Northern Tel Aviv Southern

NCCWC

Northern Northern Tel Aviv Southern

CP

Northern Northern Tel Aviv Southern

99.4

97.0

97.3

35.2

point of the threshold depends on whether the scenarios represent cases with or without curtailment. Notice that the scatter plots of both scenarios without curtailment formed one curve, which was represented by the continuous line curve fitted to their combined data. Similarly, the other two scenarios with curtailment formed the upper dashed line curve. The CP scenario falls in the low penetration amount, thus does not show any new insight. The two curves level off at a VRE penetration of approximately 90% and 70% of the annual demand for the collective scenarios, with and without curtailment, respectively. The inflection points also correspond to an energy storage capacity of the order of daily average demand (see Fig. 9b). These inflection points are not random inflections. Fig. 10 presents the interdependence between VRE penetration and the energy storage capacity requirement for the scenarios without curtailment and the corresponding storage use for two different locations, Israel and California. The curve for the Israeli system shows an inflection at a VRE penetration of about 70% and energy storage capacity lower than one daily average demand [32]. This is in good agreement with the results of this research. The inflection for the Californian system is at much lower penetration [37]. This is because that system is more diverse than the Israeli system [38]. Overall, it is shown that the energy storage requirement is affected by the same physical constraints in both cases [52]. The inflection point for scenarios with curtailment was also predicted in those studies of the Israeli [36] and Californian [37] power systems. Both studies clearly state that up to 90% VRE penetration is possible with energy storage capacity only of the order of daily average demand, and that penetration exceeding the 90% mark is predicted to require a significant increase in the storage energy capacity. This study is in agreement with that finding but shows important lessons on how to arrive at 100% RE in a cost effective way. This is due to the ability to simultaneously model various storage technologies, in particular those which have their relative cost optimum at lower penetrations (e.g. batteries) and at higher penetrations (e.g. gas storage). Though the point of inflection for scenarios with curtailment in the present study is still of the order of daily average demand,

Fig. 8. Annual electricity generation by technology for (a) BC; (b) NCC; and (c) CP; (d) BCWC and (e) NCCWC scenarios of the power system transition from 2015 to 2050.

storage requirement simultaneously increase throughout the transition period. It also shows that the technical and financial viability of a particular storage technology could be linked to VRE penetration and the corresponding total loss. It is instructive to explore this particular relationship as given in the upcoming subsections.

3.2. Curtailment-storage–penetration nexus The foregoing section shows that VRE penetration, total energy loss and energy storage increase together. In this section, a closer investigation into the link between the three parameters is made. In order to do that, though the achieved VRE penetration depends on the year of transition as shown in the previous sub-sections, it is important to disregard its time dependence. Figs. 9 and 11 present two corresponding figures created by extracting the data corresponding to the 5 scenarios presented so far. Fig. 9 shows the interdependence between VRE penetration and bulk storage requirement. The figures present a familiar trend in which VRE penetration shows a sharp rise following an initial small increase in storage capacity and a gradual levelling off after some threshold. The 1361

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Fig. 9. VRE penetration versus bulk energy storage capacity when storage capacity on x-axis is given (a) in units of GWh and (b) daily average demand. Note that the daily average demand value of Israel varies from year-to-year (for example 168 GWh in 2015 and 410 GWh by 2050).

the energy storage requirement in the present case is slightly higher (up to approximately 1.7 times daily average demand depending on the scenario). This is because of gas storage, which contributes negligible energy at this amount of penetration. As a consequence of this, the total loss corresponding to approximately 90% VRE penetration is lower in the present study, which is approximately 15% of the VRE generation (Fig. 11) as opposed to the 20% estimate in Solomon et al. [36]. However, for approximately 100% VRE penetration, the loss becomes more than 20% of the VRE generation depending on the scenario. Returning to Fig. 10, the usefulness index (UI) curve, which is a ratio of total annual storage output to total energy capacity of the storage (also called full cycles per year), shows how storage use varies with the storage energy capacity [36]. Notice that the UI curve for the present study will also be similar, as can be inferred from the trend given in Fig. 9. But, why is there a threshold? Why does the inflection point depend

on curtailment policy? Explaining this factor is difficult based on the present data, but using earlier research of Solomon et al. [32,35–37], it was possible to explain the phenomenon by referring to the original sources for the detail of their systematic studies and findings. The above change in trend shows the change in storage application and as a consequence also a change in suitable technology preference (see also Section 3.3). Initially, when a small increase in storage capacity leads to a significant increase in VRE penetration, storage charging and discharging follow a diurnal cycle. However, after the inflection point, storage should be able to transfer energy seasonally. Consequently, the storage energy capacity requirement significantly increases. This phenomenon provided various storage technologies areas of techno-economic viability of their own. Thus, it is instructive to categorise storage technologies used for energy applications into two groups, namely diurnal and seasonal storage. Diurnal storage involves technologies that show techno-economic

Fig. 10. VRE penetration (left axis) and UI (right) versus the storage energy capacity, adapted from Solomon et al. [36,37]. 1362

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Fig. 11. The relationship between VRE penetration and total energy loss, total energy loss and energy storage for various scenarios.

viability before the inflection point, and seasonal storage involves those showing the same after the inflection. It is shown above that two inflection points exist depending on the applied curtailment policy. Without curtailment, the inflection occurs at a VRE penetration of approximately 70% for this particular case. Allowing curtailment will remove the early need for large seasonal storage. As a result, the inflection point will instead be at a VRE penetration of approximately 90% of the annual demand. This is because the removal of the curtailment limit provides the system the flexibility to curtail some of the excess generation during the consecutive days when additional nighttime discharging is no longer needed. Consequently, the system will proceed capitalizing on the diurnal role on other days by reducing the need for seasonal storage. However, once penetration approaches 90% of the annual demand, the potential for diurnal charge and discharge processes will significantly diminish. As a result, to increase penetration and reach 100% VRE supply in case it is needed, more seasonal energy transfer is required. In the present study, the diurnal energy supply was performed by batteries and the seasonal supply by gas storage enabled by PtG technology. This is because, up to 90% VRE penetration, batteries become most competitive economically due to their suitability for frequent utilisation supported by their high efficiency (more information given in the next section). On the contrary, as penetration approaches the relevant inflection point (specifically 70% for scenarios without curtailment and 90% for scenarios with curtailment) gas storage starts to be cost competitive, supported by its ability to provide cheap storage energy capacity even if it has a lower efficiency and is unsuitable for diurnal application. The presence of such complementarity between energy storage technologies is the most important factor to be credited for the reported cost effective transition to 100% RE. Note that the system still applies some curtailment to reduce unnecessary storage capacity increase, resulting in simultaneous increase in VRE penetration, total loss and storage energy capacity. The relation of total loss with VRE penetration and the storage energy capacity is given in Fig. 11. Fig. 11a shows that penetration increases together with total energy loss even though the magnitude of their interdependence depends on the applied curtailment policy. The exceptional trend observed for the

CP scenario will be discussed below using Fig. 11c. The total energy loss also shows a sharp rise with energy storage capacity, as given in Fig. 11b, before levelling off depending on the applied curtailment policy. Due to the scale of the x-axis of Fig. 11b, it is not possible to see the trend for the CP scenario, but from Fig. 11d one can see that this trend has nothing in common with the other scenario trends for the same range. The major reason for the exceptional trend of the CP is poor energy system flexibility resulting from the chosen policy, which limited the model’s ability to capitalize on the opportunities embedded in the curtailment-storage capacity requirement and VRE penetration nexus as explained below. Fig. 11c re-plots 11a for the CP scenarios with the 2015 curtailment re-calculated as a percent of VRE generation of all other years. Note that, as a result of low energy system flexibility, the high energy loss in 2015 is also common to other scenarios with curtailment as shown in Fig. 11c. Such high curtailment resulting from poor system flexibility should not be blamed on VRE technologies. The high loss in this particular year may be due to the cost of flexible dispatching in response to small incoming VRE rather than the technical flexibility of generators because most generators could be dispatched to incorporate the incoming PV electricity with a minor cost penalty. Regardless of what is happening in 2015, the data for the other years in the CP scenario show a decrease in total loss as VRE penetration increases, which contradicts the foregoing findings common to all other scenarios. Fig. 11d, which presents the magnified version of the same scenario given in Fig. 11b, also shows that the relation between total loss and the storage energy capacity demonstrates significant dissimilarity to the relations shown for the other scenarios in the same range. In the CP scenario, the flexibility of the energy system has not improved, as can be seen from the continued increase of conventional generators reported in Fig. 5. Such a path gives a narrow economic choice to the model to achieve the targeted renewable penetration. Therefore, the model built slightly larger energy storage capacities corresponding to each penetration, as shown in Fig. 9, leading to an odd relationship between energy storage and total loss as well as VRE penetration and total loss. This indicates that achieving proper system flexibility will be mandatory to exploit the potential benefit of the physical connection between storage 1363

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requirement, VRE penetration and total loss. At the same time, this result is also a warning that models favouring conventional generators are not a good tool to measure the capability of storage technologies and VRE systems. The foregoing presentation clearly shows that energy storage requirements, VRE penetration and total loss have a strong physical link, which affects the economic viability of a given storage technology, its use and design requirements. The physical link between the three is defined by seasonal and diurnal matching of VRE output and the local demand as discussed in Solomon et al. [32,37]. Studies based on models that have a limited ability to capture this relationship cannot be considered a trusted resource for transitioning to 100% RE systems.

operation time of batteries. Employment of this kind of dispatch, during challenging seasons of the year, was shown to reduce balancing capacity requirement, which was termed as backup in that study, throughout the system as discussed in Solomon et al. [38]. This model employs most of the required concepts demonstrated in Solomon et al. [37] while also enabling the achievement of 100% RE by using synthetic fuel for electricity generation. It should be noted that such a dispatch will require accurate forecasting, which is evolving quickly as energy meteorology [66]. For the BC scenario, to supply 100% of the demand including the forecasted 30 GW peak load, 9.2 GW of gas turbine capacities are required. The capacity will be about 9.0 GW for the same scenario without curtailment, which is compensated by the larger battery capacity. The corresponding capacities for the NCC scenario with or without curtailment are 8.3 GW and 8.7 GW, respectively. The remaining majority of the energy is supplied by direct solar and the stored energy from batteries. During those winter days, small curtailment could be seen on four of the days. Note that on those days and two other days, electrolysis occurs during daytime. The SNG used on those days came from the preceding year. The gas turbines were not used for electricity supply during spring days, as shown in Fig. 12b. Similarly, their role during the summer days shown in Fig. 12c is negligible. During the spring days, due to lower demand, solar PV generates significant electricity to be stored by batteries and gas storage. The portion in excess of direct use and storage charging will be curtailed as shown in the figure. Closer inspection of the figure shows that electrolysis also occurs during nighttime. This is because the energy in the batteries is more than the electricity supply needed for the night. Consequently, the model discharges the batteries for the next day by producing the gas to be stored for other season. The simultaneous battery discharging – PtG charging process actually reduces possible curtailment on the following day and the capacity increase that may have been required on the part of the PtG conversion system to store the same energy in gas storage. Fig. 12c is almost similar to that of spring but, due to high demand during summer days, PtG conversion is limited especially during nighttime. The observed simultaneous battery discharge-PtG charge process is part of the least

3.3. Storage dispatch and deployment merit order In the following section, the entire system dispatch is examined in order to gain insights regarding the storage dispatch order. For this case, it suffices to study the 2050 system dispatch for the BC scenario because it presents the 100% RE setting. At the same time, closer study of the data for other years shows that the lessons obtained in this particular case closely apply to almost all other cases with very high VRE penetration. Fig. 12 presents an hourly generation and storage discharge (both represented by positive values) and various manners of electricity use (represented by negative values) for the first 10 days of the months of July, April and August. The dispatch represents the entire Israeli electricity supply system by 2050, with hourly generation from PV, batteries and gas storage. The role of each technology in the entire system dispatch depends on the season of the year. Fig. 12a, which shows the dispatch in January of that year, shows that CCGT and OCGT play significant roles in the first 6 days, with reduced or smaller roles in the other days. Because of the low solar generation in those days, batteries did not store enough energy to supply the nighttime demand. The CCGT and OCGT have been deployed to fill the gap by firing the stored SNG from other seasons of the year. Intuition suggests operating the CCGT and OCGT at certain times of the day, but notice that the model employs a continuous operation while also enabling a prolonged

Fig. 12. System dispatch for the first 10 days of various months of the year: (a) January, (b) April and (c) July. The positive region represents the output of various generation sources. Notice also the real demand curve. The negative region shows how the excess generation is treated in the model. 1364

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cost solution. This effect has been already reported for the cases of regions within Northeast Asia [67] and India [15]. The overall dispatch trend discussed here is similar to what is discussed in Solomon et al. [38] and Breyer et al. [67] in spite of the use of gas storage to achieve 100% RE in the present case. Note that the excess generation overlaps with the summer peak demand time of Israel. The stress time for this particular area is during winter, when the solar irradiance is lower. In agreement with Solomon et al. [38], the present peak load based supply reliability criteria is no longer applicable to the future grid that will fully or partly rely on VRE depending on local resources. The foregoing result shows that batteries, which are classified as diurnal storage, are dispatched in charging mode during daytime and discharging mode during nighttime. On the other hand, gas storage, termed as seasonal storage, will be in charging mode on most of spring, summer and autumn days to store SNG to be utilized during winter days and some other days of shortage in the other seasons. The gas storing conversion chain, consisting of electrolyser, CO2 direct air capture, methanation, physical gas storage and reconversion into electricity via gas turbines, i.e. power-to-gas-to-power, will have in the future energy system a role similar to gas turbines in the present power system but will be dispatched in a different way. Due to the above technical details, storage which will suitably serve as diurnal storage will have dispatch priority during charging or discharging. Seasonal storage, constituting those technologies serving as a tool for maintaining supply reliability during stressful weeks of the year, will have to come second. However, this study is not sophisticated enough to group storage technologies into the classes identified above. Though there are 5 different storage technologies in the model, the performance of other technologies may have been affected by the chosen Energy-to-Power (E2P) ratio or cost. Comparing with the result in Solomon et al. [32] the battery E2P ration used in this study may be close to optimal, while gas storage has the flexibility of energy and power capacity design as compared to others. However, technical details of both classes of storage can be provided based on what is observed during this study. Diurnal storage can be identified by two characteristics: high storage efficiency and lower E2P ratio. On the contrary, seasonal storage could be seen as technologies that can provide a rather low cost energy capacity. Thus, it should have a high E2P ratio, and a moderate storage efficiency is allowed. In the present study, gas storage was shown to fit that requirement of seasonal storage. PHS and A-CAES could also provide such an option with added potential to serve as diurnal storage or an intermediate. In an upcoming study, these options will be explored by improving the storage design flexibility. The above presentation leads to the other important topic, which is storage technology deployment order. The two most important insights of the proceeding sections are the findings that: (i) the storage-penetration-total loss nexus requires that the three increase together in transition to a 100% RE system; and (ii) the techno-economic feasibility of each technology depends on this nexus. Thus, it is important to a make detailed assessment of the relation of a technology wise deployment to VRE penetration. Fig. 13a presents the link between VRE penetration and battery capacity while Fig. 13b presents the link between VRE penetration and gas storage capacity. As can be seen from Fig. 13a, battery capacity requirements significantly increase until penetration reaches about 90% of the annual demand, where penetration increase starts to level off and battery capacity increase stops at some maximum value because more significant battery capacity increase above that amount leads to significant marginal cost. This problem was counter balanced by the corresponding increase in gas storage capacity given in Fig. 13b. Gas storage was significantly small for penetrations lower than 90% and 70% for the scenarios with and without curtailment, respectively. But this capacity and role increased significantly afterwards. Though the capacity is still large for the lower penetration ranges, gas storage contributes almost nothing to the energy system in annual electricity supply. The early but small relationship between gas storage capacity and penetration should not be interpreted as a reflection of its

role. Thus, it can be concluded that deployment of storage technology depends on penetration and curtailment policy. In agreement with our findings, the results in [68] suggest that feasibility of PtG technology depends on its role in the system. The results in [68] may have occurred due to corresponding local inflection related to the nexus, but this was never clarified as there is a lack of attention to the importance of these relationships. Diurnal storage will be deployed at an increasing rate until 90% VRE penetration of wind and solar PV is reached. In the remaining penetration range (90–100%), seasonal storage will be significantly deployed. Note that Fig. 13 shows that for scenarios without curtailment, gas storage starts to play a role at lower penetration. In this circumstance, it replaces some role of curtailment and slightly reduces battery capacity need as compared to the capacity required for the same penetration when curtailment is allowed. Notice that battery capacity requirement differences observed depending on curtailment policy almost disappear above 90% penetration for both the BC and NCC scenarios. The complementarity of various storage technologies is the reason why the scenarios formed two simple groups based on curtailment policy as shown in Fig. 9. In general, this study shows that in policymaking, it is very important to establish the target penetration and the corresponding curtailment in order to motivate investments in RE technologies and appropriate storage capacities for that target. Finally, a transition to 100% RE requires effective exploitation of the physics of the seasonal and diurnal relationships between VRE output and the demand profile for the maximum societal benefit. 4. Discussion The foregoing results show several important insights that are in agreement with other studies. This research establishes for the first time the curtailment-storage-penetration nexus with detailed techno-economic data. Their relationship clearly shows that for an optimally designed system, the three simultaneously increase throughout the transition period. The observed nexus is in agreement with previously reported studies that implemented a systematic approach to study the subject. Our finding that initially VRE penetration increases significantly with a small increase in energy storage capacity is in agreement with the findings reported in Solomon et al. [32]. The presence of two inflection points was also clear from previous studies [36]. In agreement with Solomon et al. [36,43,44–45], with an energy storage capacity of the order of daily average demand, VRE penetration of about 90% was achieved. The corresponding total losses in those studies were approximately 20% as opposed to the estimated 15% in this study, which is explained by larger storage capacities found in the present study, mainly due to the presence of gas storage, than those studies. The inflection for the scenarios without curtailment was also similar to what was reported in previous studies of the same energy system [36]. Similar trends were reported for California for cases of both an optimal [37] and various mix [38] of wind and solar. Storage application and the suitability of a given technology depends on the curtailment policy regardless of the penetration being higher or lower than the 90% inflection point mark. However, the inflection points were useful to classify storage technologies depending on their roles before and after that inflection point. Storage technologies that play a significant role before the inflection point are classified as diurnal storage, but storage technologies that join the systems with a massive capacity above the inflection point are called seasonal storage. The inflection point is also the point where these seasonal storage technologies start to play significant roles depending on the curtailment policy. Regardless of the curtailment policy, it can be concluded that a diurnal storage technology deployment monotonically increases with VRE penetration until it reaches approximately 90% of the annual demand. The reported relationships are a consequence of the achievement of an optimal matching between VRE output and load profile under given constraints throughout the transition period. This shows that in order to take advantage of this relationship and make an effective 1365

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Fig. 13. (a) Diurnal and (b) seasonal energy storage requirement versus VRE penetration.

transition to 100% RE, planners should follow paths that would gradually increase the flexibility of the existing energy system while increasing energy storage capacity in the system. The observed least cost electricity supply reported in connection with increasing curtailment and VRE penetration shows that an optimal curtailment amount exists that carries technical and financial benefits to the system. This optimal curtailment was actually shown to lower LCOE as opposed to the no-curtailment policy. No previous study reported such an economic advantage, but curtailment was shown to carry a technical advantage of achieving higher VRE penetration at reduced energy storage capacity and balancing need [38]. The reported cost benefit was also clearly linked to these technical advantages. This is in contradiction to some researchers’ assertions that curtailment is a simple waste of energy [53]. Such an assertion is not supported by scientific evidence but is a result of an intuitional speculation. This also calls into question the result of studies made based on suboptimal system assumptions, such as Barnhart [69], Carbajales-dale [70] and Palmer [71]. It is important to note that curtailment is not a simple waste of energy but an important technical factor whose improper use or avoidance carries a penalty. The CP scenario shows a good example of improper use of curtailment that might arise due to poor system flexibility. Such curtailment should be avoided by improving energy system flexibility. No random curtailment should be supported, except those found to give relief in an optimally designed energy system. This indicates that policy making and regulation requires significant research activities, at least during the transition. The penalties that come from improper avoidance of curtailment can be seen from the results obtained in this study by enforcing a no-curtailment policy. As clearly discussed above, if no-curtailment is enforced, LCOE significantly increases (the increase being higher than 7% for all scenarios in 2045 and 2050). Other previous studies discussed above have shown a relationship between energy storage capacity requirements and curtailment amount. Some even suggested a curtailment amount of up to 50% of the generation for Europe [36] and eastern United States [42]. This occurs because of the effort to drive to 100% RE with diurnal storage technologies, which are expensive [37], or because of a tendency to treat all storage as one. Note that, as indicated in Solomon et al. [36], storage design should be able to exploit the technical suitability of various types of storage technologies by considering a mixture. Consideration of a mixture will provide the opportunity to exploit the techno-economic advantage of various technologies as shown in the present study. Future improvement could provide a mixture that is superior to the one shown in this study. Based on this study and other results [52], total loss (both curtailment and storage efficiency loss) should be lower than 30% of

the generation in the worst case. It is also important to emphasize that applying curtailment policy may lead to significantly large transmission requirement between some nodes to overcome a balancing challenge during some season. It should be clear that this carries an embedded risk of supply unreliability. This research also shows a logical storage dispatch merit order, the diurnal storage has the priority, which is to be followed by seasonal storage depending on the season of the year. The storage dispatch was found to follow an order that gives various techno-economic advantages to the system. First, it was demonstrated that the model undergoes simultaneous battery discharging-PtG charging processes during some night times, a phenomenon that helps to reduce curtailment in the next day and the required PtG conversion technology to store the equivalent SNG. This effect was also reported for other regions in the world [15]. Second, the dispatch also follows an order that will reduce balancing capacity need. It was shown that the balancing need by 2050 has the same capacity as the present gas-fired power plant capacity but will be running on SNG obtained from gas storage. It was also shown that future stress times are likely to be different from present stress times of the power system. This is in agreement with [38], and may not be solved by following the present day reserve criteria. In addition, the observed dispatch is in agreement with what was discussed in Solomon et al. [38] and Breyer et al. [67] 5. Conclusion This paper presents the results of a study aimed at examining the curtailment–storage–penetration nexus in the energy transition. The research was done using the LUT optimisation model, a linear optimisation tool that can ensure hourly synchronicity between the local load and VRE system output. The study uses the datasets for Israel, which possess characteristics representing many other countries. The study has 5 scenarios. Three scenarios enforce the application of GHG emission pricing during the energy transition period. Of those scenarios, one closely duplicates the present electricity sector policy direction of Israel. The two remaining scenarios apply no GHG emission cost. A set of two scenarios, one from each group, deal with the impact of a potential curtailment rule, with one anticipating a limit on curtailment while the other expects an optimal transition with curtailment considered as a technical solution to better match VRE output and load profile. Each of the results were analysed in detail to identify potential lessons regarding the physical link between total loss (curtailment plus storage efficiency loss), VRE penetration and storage energy capacity requirement. 1366

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First, it was shown that the levelised cost of electricity decreases as the energy transition proceeds from the present energy system to the future 100% RE system. This trend was found to depend on the use of GHG emission cost. The most important finding in this study is the cost difference observed between the corresponding scenarios when a different curtailment rule is applied. If curtailment is limited during the transition, LCOE is significantly higher than the corresponding values when curtailment is allowed. For instance, the 2050 LCOE without curtailment is found to be 8.6% and 8.4% higher than the LCOE with optimal curtailment for the BC and NCC scenario, respectively. The above observation challenges the perception that treats curtailment as a mere waste of energy despite the reported technical benefits [52], which leads to the observed cost advantage also discussed in this research. From this study, we conclude that curtailment in an optimally managed energy transition brings techno-economic opportunities to the system, while no-curtailment or improper use of curtailment carries a penalty. Second, this research establishes for the first time the curtailmentstorage-penetration nexus with detailed techno-economic data. Due to the reported nexus, throughout the transition period, total loss, VRE penetration and energy storage capacity requirements were found to increase simultaneously. The nexus between the three was actually found to define when to deploy a certain storage technology during the transition. As clearly indicated, VRE penetration significantly increases with a small increase in energy storage until it levels off. Two inflection points were found depending on the applied curtailment rule. If curtailment is allowed, the inflection point will be at a penetration amount of approximately 90% of the annual demand, which would have otherwise occurred at a much lower penetration of approximately 70% of the annual demand for a scenario without curtailment. These findings are in agreement with the findings of previous studies [41,43,44–45]. Due to the presence of varieties of the storage technology mix in the present model, the inflection points are found to be points where seasonal storage starts to get deployed. All inflection points correspond to a storage capacity of approximately one daily average demand. Based on this result, storage can be categorised into two groups, namely, diurnal and seasonal storage. A closer study of the data shows that diurnal storage continuously increases until VRE penetration reaches approximately 90% of the annual demand and the corresponding total storage capacity reaches approximately one daily average demand. If no curtailment is allowed, the storage energy capacity will be larger because of the complementing effect of seasonal storage. However, for the last 10% of the VRE penetration, seasonal storage will increase by a significant magnitude. Third, the dispatch strategy is also guided by the push to effectively satisfy the nexus between the three parameters in a resource optimal way. It has been shown that charging and discharging show a seasonal variation by storage category. This dispatch also shows that the future energy system has times of stress which are different from the present one, in agreement with what is discussed in Solomon et al. [38]. Diurnal storage has dispatch priority both during charging and discharging, followed by seasonal storage. The simultaneous battery discharging and gas storage charging processes also allow more efficient storage utilisation that will avoid additional curtailment as well as a need for more PtG capacity to store the same amount of SNG. The significance of this study lies in its ability to provide important insights into policymaking and regulation for the transition to 100% RE systems. The results show that energy system planners and regulators need to have detailed understanding of their future system to set future VRE penetration targets and the corresponding curtailment as well as guide the specification of system requirements and operational rules. Moreover, it is important that curtailment receive a proper valuing in the mix of techniques for flexibility. At the same time, significant care should be taken to avoid possibilities of incentivising unacceptable amounts of curtailment. The transition trend observed in this study is almost common to that

found for several geographical regions studied using the same model [72]. As a result, insights identified in this study should have relevance to other regions. This is due to the fact that similar physical links corresponding to each system could be found in each case with some minor differences depending on local conditions. The above findings have significant lessons for a successful energy transition. The policy decisions on curtailment, energy storage requirements and VRE penetration strongly affect the type of the energy system to be built. To be effective, regulators should clearly specify and revise techno-economic indicators often to cope with market dynamics and on-going change in the energy system. This requires an in-depth knowledge of the characteristics of local RE resources and their role in the future energy system with a detail far more than what is required for the relatively predictable present power system. Acknowledgements The authors gratefully acknowledge the public financing of Tekes, the Finnish Funding Agency for Innovation, for the ‘Neo-Carbon Energy’ project under the number 40101/14 and support from LUT internal research platform REFLEX. Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.apenergy.2018.11.069. References [1] [UNFCC] – United Nations Framework Convention on Climate Change. Paris Agreement, Paris; 2015. < http://unfccc.int/paris_agreement/items/9485.php > . [2] Haegel N, Margolis R, Buonassisi T, Feldman D, Froitzheim A, Garabedian R, et al. Terawatt-scale photovoltaics: trajectories and challenges. Science 2017;356:141–3. [3] [ETIP-PV] – European Technology and Innovation Platform for Photovoltaics. The true competitiveness of solar PV – a european case study, ETIP-PV, Munich; 2017. < http://bit.ly/2qxV9Y6 > . [4] [IRENA] – International Renewable Energy Agency. Letting in the light – how solar photovoltaics will revolutionize the electricity system, IRENA, Abu Dhabi; 2016. < www.irena.org/DocumentDownloads/Publications/IRENA_Letting_in_the_Light_ 2016.pdf > . [5] [IEA-PVPS] – International Energy Agency Photovoltaic Power Systems Programme. Trends 2015 in photovoltaic applications: survey report of selected IEA countries between 1992 and 2015, Paris; 2016. < http://iea-pvps.org/fileadmin/dam/ public/report/national/Trends_2016_-_mr.pdf > . [6] [ITRPV] – International Technology Roadmap for Photovoltaic. International technology roadmap for photovoltaic results 2016, ITRPV, Frankfurt; 2016. < www.itrpv.net/Reports/Downloads/ > . [7] [IRENA] – International Renewable Energy Agency. The power to change: solar and wind cost reduction potential to 2025, IRENA, Abu Dhabi; 2016. < www.irena.org/ DocumentDownloads/Publications/IRENA_Power_to_Change_2016.pdf > . [8] UBS. UBS evidence lab electric car teardown–disruption ahead? Q-Series, 18 May 2017; 2017. [9] [IEA-NEA-OECD] – International Energy Agency and Nuclear energy agency. Projected costs of generation electricity 2015 edition, OECD-NEA, Paris; 2015. < www.oecd-nea.org/ndd/pubs/2015/7057-proj-costs-electricity-2015.pdf > . [10] [WEC] – World Energy Council. World energy perspective-cost of energy technologies, WEC, London, 2013. < www.worldenergy.org/wp-content/uploads/2013/ 09/WEC_J1143_CostofTECHNOLOGIES_021013_WEB_Final.pdf > . [11] [BNEF] – Bloomberg New Energy Finance. New energy outlook 2016–powering a changing world. BNEF: London; 2016. [12] Lazard. Levelized cost of energy analysis-version 11.0, New York; 2017. < https:// www.lazard.com/media/450337/lazard-levelized-cost-of-energy-version-110. pdf > . [13] Solomon AA, Bogdanov D, Breyer C. Solar driven net-zero emission electricity supply with negligible GHG cost, Israel as a case study. Energy 2018;155:87–104. [14] Cosic B, Krajacic G, Duic N. A 100% renewable energy system in the year 2015: the case of Macedonia. Energy 2012;48:80–7. [15] Gulagi A, Bogdanov D, Breyer Ch. The role of storage technologies in energy transition pathways towards achieving a fully sustainable energy system for India. J Energy Storage 2018;17:525–39. [16] Blakers A, Lu B, Stocks M. 100% renewable electricity in Australia. Energy 2017;133:471–82. [17] Child M, Breyer C. The role of energy storage solutions in a 100% renewable Finnish energy system. Energy Proc 2016;99:25–34. [18] Bogdanov D, Breyer C. North-East Asian Super Grid for 100% renewable energy supply: optimal mix of energy technologies for electricity, gas and heat supply options. Energy Convers Manage 2016;112:176–90.

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