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Demand shifting analysis at high penetration of distributed generation in low voltage grids
Electrical Power and Energy Systems 44 (2013) 540–546
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Demand shifting analysis at high penetration of distributed generation in low voltage grids Ioulia T. Papaioannou ⇑, Arturs Purvins, Evangelos Tzimas European Commission1, DG JRC, Institute for Energy and Transport, Postbus 2, 1755 ZG Petten, The Netherlands
a r t i c l e
i n f o
Article history: Received 22 November 2011 Received in revised form 11 July 2012 Accepted 25 July 2012 Available online 26 September 2012 Keywords: Flexible demand Demand shifting Renewable energy sources Distributed generation Photovoltaic Smart grids
a b s t r a c t One of the main challenges that Europe has to face is to ensure the swift deployment of renewable energy sources by increasing their share in the energy generation mix to 20% by 2020, considering the large-scale deployment of new electricity generators in low voltage (LV) grids. The article highlights the contribution of electricity end users to achieving this target as the European Union is eager to unlock their potential in the energy sector. This article examines the penetration of distributed generation from a technical point of view and explores the possible barriers that may arise under high penetration conditions. Specifically, in the critical case of low demand and high distributed generation, the voltage could exceed the acceptable range in the LV feeder, and this can lead to the disconnection of the generator. Thus, a simple approach is used to calculate the voltage profile along the LV feeder and to estimate losses and loading. As the estimation takes the demand into account, this is followed by a sensitivity analysis – using the Monte Carlo technique – in order to track the optimal topology of flexible demand. The article suggests that, in critical cases, customers at the end of the LV feeder would be the main contributors to ensuring the uninterrupted operation of distributed generation within power quality standards. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction In 2008, the European Union (EU) adopted an energy and climate action plan, which sets ambitious targets for 2020, namely the reduction of greenhouse gas emissions by 20% from 1990 levels, an increase in the share of renewable energy sources (RESs) to 20% of gross energy consumption and a 20% improvement in energy efficiency [1]. Meeting these targets should be seen as just the first step in the transition to a low carbon society. The EU has made a long-term commitment to cutting European greenhouse gas emissions by 80–95% by 2050 [2], which will be achieved with the near-complete decarbonisation of the power sector [3]. In this context, it is expected that RES, mainly wind and solar, will provide about half of the electricity generated in the EU in 2050 [4], which implies that the installed capacities of such energy technologies are likely to increase dramatically in the years to come. Indeed, 62% of electricity generation capacity installed in 2009 in the EU was RES power, mainly in the form of wind farms, but also solar plants [5]. A large number of these RES plants, as distributed generation (DG) units, will be connected to the low voltage (LV) grid. However, the success of European energy and climate policies also depends on the active involvement of the energy end user ⇑ Corresponding author. Tel.: +31 224565171. E-mail address: [email protected] (I.T. Papaioannou). The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission. 1
0142-0615/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijepes.2012.07.054
[6–8]. Therefore, measures have been taken to increase energy savings, disseminate innovative solutions, such as electrification of transport and real time energy pricing, and to improve energy efficiency and energy autonomy in buildings. As part of the same approach, the EU is taking forward a major European initiative on ‘smart grids’ to interlink the whole electricity grid system, while making power grids more intelligent, efficient and reliable [2]. The major issues relating to the penetration of DG include the technical constraints and the tolerance of LV grids to adopt new dispersed power generators. The most significant challenge that is emerging as a result of the increasing penetration of DG is that of voltage rise [9]. The literature proposes methods of voltage control in areas where DG is deployed in order to resolve violations of voltage limits [10–13]. However, so far this issue has been addressed only from the perspective of power generation [14–16] or the distributed network operator (DNO) [17]. The present article explores this issue from consumer perspective, with a view to identifying the potential impact of demand management in LV feeders with high penetration of DG. The analysis is based on a scenario that deploys the integration of photovoltaic (PV) units in LV grids to address the issue and assess the optimal shifting of flexible demand along the feeder. Under conditions of high PV generation and low demand along the LV feeder, the risk that the voltage will exceed the upper limit at some points becomes more likely [18]. Conventionally the PV inverter, by detecting an overvoltage, obliges the PV systems connected to the respective points to be disconnected until the voltage
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is back within the acceptable range [16,19,20]. This disconnection prevents PV systems from producing their peak power most of the time [21]. Therefore, this analysis was considered essential, since – in order to increase the feasibility as well as the installed capacity – the maximum energy yield of distributed PV systems, i.e. the MWh/year, needs to be ensured [14]. The present analysis considers power quality restrictions imposed by the EN 50160 [22] and IEEE 1547 [23] standards, with acceptable voltage range: +15% and 20% of the nominal value. Furthermore, the conclusions of this analysis will be applicable to other DGs from uncontrollable RES such as small wind farms. Under the above concept, and in support of the effort to boost the integration of DG in compliance with power quality standards, the present article firstly addresses the technical issues arising from the connection of DG in LV feeders. Given that a significant fraction of the household demand cannot be met in real time by PV generation [24], the article explores the role of demand shifting in diminishing the voltage rise effects of DG. Explicitly the article focuses on the optimal topology of the flexible demand along the LV feeder. Thus, demand management is seen from a technical point of view, beyond the economic aspects which have already been analysed [25–28]. Considering the practical difficulties in changing the demand behaviour, optimization is defined as the solution in which the least amount of demand shifting along the feeder is needed in order to ensure the maximum effect on the voltage management. It should be noted that demand shifting does not mean the increasing of the total load, but changing the time of day when the load is switched on. Thus, the overall demand of the user at the end of the day remains the same as if it was being inflexible. This demand shifting can be achieved in ‘smart grids’ where communication between flexible loads and voltage levels in the LV feeder is possible [29]; or in a feeder without centralized control where demand is simply shifted to a specific time of the day, e.g. when both low demand and high generation are highly likely. These ‘smart’ flexible loads, e.g. smart washing machines, are currently undergoing demonstration trials as part of various ‘smart grid’ projects [30]. In order to carry out this analysis, the authors develop a simple analytical approach to calculate the voltage profile along a radial LV feeder with connected DG systems. In addition, feeder losses and loading data are calculated, which also raises significant issues of DG integration [31,32]. The approach takes into account demand and PV generation along the feeder, and also the configuration of the distribution transformer and the subject line. The approach is implemented in common spreadsheets and tested against detailed simulations in a power system modelling tool, NEPLAN [33]. As a case study, a 10 node feeder is used where the operation of PV systems is examined firstly under inflexible demand and then by deploying demand shifting.
2. Analytical approach The following analytical approach is developed for load flow analysis in a radial LV feeder. This approach can be applied for a single-phase as well as for a three-phase line. For explanation reasons of the approach a line diagram with N nodes and with a transformer as shown in Fig. 1 is used. At the line, N loads and N DG systems are connected with PLOADj and QLOADj being active and reactive load respectively and PDGj and QDGj being active and reactive power generation respectively at node j. Additionally, PLOSSj,j+1 and QLOSSj,j+1 are respectively the active and reactive power losses on the line for the branch between the nodes j and j + 1. The distance between nodes j and j + 1 is lj,j+1. The voltage U0 at the secondary terminals at node 0 of the distribution transformer is considered to be the reference voltage. The voltage at node j is
Uj. In the practical situations that are encountered in LV feeders supplying households, the loads can be single phase connected alternately in different phases. However, when DG systems are connected at any node, the utility – depending on the country of installation – may require them to be three-phase in order to avoid imbalances. It should be noted that node quantities are expressed by a single indicator equal to the number of the specific node, whereas branch quantities are expressed by two indicators expressing the two nodes between which the specific branch is found. The voltage drop across the branch from node j to node j + 1 can be calculated with the aid of the phasor diagram.
DU j;jþ1 ¼ jU j j jU jþ1 j ¼ jU jþ1 j þ Ij;jþ1 Rj;jþ1 cos /jþ1 þ Ij;jþ1 X j;jþ1 sin ujþ1 jU jþ1 j ¼ Ij;jþ1 cos /jþ1 ðRj;jþ1 þ X j;jþ1 tan /jþ1 Þ
ð1Þ
where Rj,j+1 and Xj,j+1 are the branch resistance and reactance respectively, Ij,j+1 is the branch current between the nodes j and j + 1 and uj+1 is the angle between this current and Uj+1. If R0 is resistance and X0 is reactance per km of the line, (1) can be rewritten as:
DU j;jþ1 ¼ Ij;jþ1 cos /jþ1 lj;jþ1 ðR0 þ X 0 tan /jþ1 Þ
ð2Þ
By replacing
Ij;jþ1 ¼
P jþ1;N U jþ1 cos ujþ1
ð3Þ
Q jþ1;N Pjþ1;N
ð4Þ
and
tan ujþ1 ¼
the voltage change can be expressed as:
DU j;jþ1 ¼ lj;jþ1
Q jþ1;N Pjþ1;N R0 þ X 0 U jþ1 Pjþ1;N
ð5Þ
where the active power Pj+1,N includes all the active loads and PV systems and also the active losses in the branch between the nodes j + 1 and N. Pj+1,N is calculated with the following equation:
Pjþ1;N ¼
XN i¼jþ1
ðPLOADi PDGi Þ þ
XN1
P i¼jþ1 LOSSi;iþ1
ð6Þ
Relatively, Qj+1,N is the sum of all the reactive loads (QDGj is positive in case the DG system consumes reactive power and negative in case it generates) and reactive power losses in the branch between the nodes j + 1 and N:
Q jþ1;N ¼
XN i¼jþ1
ðQ LOADi þ Q DGi Þ þ
XN1 i¼jþ1
Q LOSSi;iþ1
ð7Þ
Obviously, both the sums of active and reactive losses have an upper limit of N 1 expressing the last losses along the line between N 1 and N node. In order to estimate the active and reactive losses of the line, the branch current is needed and can be also expressed as:
Ij;jþ1 ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P2jþ1;N þ Q 2jþ1;N U jþ1
ð8Þ
So, PLOSSj,j+1 and QLOSSj,j+1 of the branch between nodes j and j + 1 can now be estimated:
PLOSSj;jþ1 ¼ R0 lj;jþ1 I2j;jþ1
ð9Þ
Q LOSSj;jþ1 ¼ X 0 lj;jþ1 I2j;jþ1
ð10Þ
The voltage in node j is calculated with regard to the voltage change from all the previous nodes and the voltage drop on the transformer. Thus:
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Fig. 1. Single-line diagram of a radial LV feeder.
Uj ¼
Xj1
ðU 0 DU i;iþ1 Þ i¼1 XN 1 XN R0 k¼1 ðPLOADk PDGk Þ þ X 0 k¼1 ðQ LOADk þ Q DGk Þ þ U0 ð11Þ
R0 and X0 are the equivalent resistance and reactance of the distribution transformer, referred to the LV side. In order to solve the above equations, an iterative procedure has been used by starting from the last node N of the line and estimating the total active and reactive power from (6) and (7) as PN1;N ¼ P LOADN P DGN and Q N1;N ¼ Q LOADN þ Q DGN . The relative voltage change can be now calculated with the aid of (5), while an approximation of the branch current is made with (8). In the latter equation, Uj+1 is replaced by U0 in order to be solvable. The same procedure continues gradually in descending order for all the other nodes, i.e. N 1 to 1, until node 1 is reached. 3. Assumptions The analytical approach described in the previous section is solvable and applicable with the following assumptions: (1) The replacement of Uj+1 with U0, so as to make (5) and (8) solvable:
DU j;jþ1
Q jþ1;N P jþ1;N R0 þ X 0 ¼ lj;jþ1 U0 Pjþ1;N
Ij;jþ1;approx ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P2jþ1;N þ Q 2jþ1;N U0
ð12Þ
ð13Þ
This assumption introduces a simplification and leads to more conservative estimates. As regards the branch current, it is corrected later with the use of the calculated voltages, since they have already been estimated by the abovementioned procedure. In the case of the voltage, the assumption is based on the statement that calculations should be made for the worst case: the maximum voltage rise appears when all the DG systems in the line operate close to their nominal power and, at the same time, the loads are at minimum [7,12]. One could assume that all the loads are zero, but this is not realistic. A realistic assumption for a household feeder is to consider that, in each home, only the refrigerator is operating. A typical value for the refrigerator load is 200 W/phase, cos u = 0.7, at the rated phase voltage 230 V. In this regard, we can safely assume that the DG production is greater than the load demand of the feeder, causing reverse power flow [21,34]. Thus, the voltage will be greater than U0, which represents the voltage of the transformer on the LV side, even from the first node and beyond, and the voltage profile along the line will show a rise, as in Fig. 2. In Eq. (5), which is principally affected by the above replacement, the calculated voltage rise is greater and esti-
Fig. 2. Voltage profile in a LV line at energy flow from node N to node 0.
mations are more restricted, thus leading to more conservative and reliable results. (2) The approach does not take account of the voltage drop along the neutral and assumes a balanced three-phased system. Under circumstances of minimum load demand and high DG integration, the asymmetry introduced by the load is minor in relation to the symmetry of the three phased DG generation. Thus, the voltage drop along the neutral conductor is assumed to be zero. 4. Validation with NEPLAN In order to verify the proposed analytical approach, a comparison with NEPLAN modelling tool is performed. A single-phase LV radial line supplying 10 households and 10 DG systems, e.g. PV systems, as depicted in Fig. 3 is used. The three-phase transformer parameters are assumed to be: 250 kVA, secondary windings voltage 0.4 kV, Rtr = 7.04 mX and Xtr = 37.7 mX. The single-phase line connected to the one of the three secondary transformer windings is assumed to be an overhead 35 mm2 line (steel reinforced aluminium conductor, ACSR, R0 = 0.576 X/km, X0 = 0.397 X/km). Such a line is characterized with 224 A rated current and consequently with a 51.52 kW/phase capacity. The distance between nodes is considered to be 60 m. The minimum household load of 200 W (cos u = 0.7, see Section 3) and PV generation of 5 kW (cos u = 0) close to the nominal line capacity are assumed to be connected to the nodes from 1 to 10. In NEPLAN modelling, the ‘‘Current Iteration’’ method is used which is proper for power flows on the distribution level. The comparison of the NEPLAN modelling with the relevant results acquired by the proposed approach is shown in Tables 1 and 2 and includes: voltage at nodes, branch current and power losses in each branch. The relative deviation of each parameter is estimated as:
e¼
Aneplan Aapproach Aneplan
ð14Þ
where Aneplan and Aapproach are the results obtained from NEPLAN modelling and the proposed approach respectively. The phase voltage values at the nodes from 1 to 10, shown in Table 1, justify the first assumption of the previous section. Thus the voltage estimated with the approach on average is slightly
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Fig. 3. Single-line diagram with 10 households.
5.1. Identification of critical scenarios
Table 1 Comparison of node voltages. Node
1 2 3 4 5 6 7 8 9 10
Node voltage (V)
Voltage deviation (%)
Approach
NEPLAN
236.12 241.79 246.94 251.55 255.57 258.97 261.73 263.81 265.21 265.91
236.94 242.37 247.22 251.49 255.13 258.13 260.56 262.41 263.62 264.25
0.35 0.24 0.11 0.02 0.17 0.33 0.45 0.54 0.60 0.63
‘‘PV at all nodes’’: ten PV systems of 5 kW/phase are installed in each node from 1 to 10 (as in Section 4); ‘‘PV at node 10’’: one PV system of 30 kW/phase installed in the last node, i.e. node 10; ‘‘PV at node 1’’: one PV system of 30 kW/phase connected at the first node, i.e. node 1; ‘‘Without PV’’: baseline scenario without PV installations.
Table 2 Comparison of branch current and active power losses. Branch
0–1 1–2 2–3 3–4 4–5 5–6 6–7 7–8 8–9 9–10
Branch current (A) Approach
NEPLAN
188.97 168.76 148.90 129.39 110.22 91.48 72.84 54.43 36.19 18.07
189.00 169.00 149.00 130.00 111.00 92.00 73.00 55.00 36.00 18.00
Current deviation (%)
Branch losses (W/phase) Approach
NEPLAN
0.02 0.14 0.07 0.47 0.70 0.56 0.22 1.04 0.53 0.38
1234.08 984.26 766.25 578.62 419.83 289.22 183.35 102.37 45.26 11.28
1236.33 986.00 768.33 581.00 422.33 290.67 184.67 103.33 45.67 11.33
Initially, load flow analysis in the feeder is performed in sunny weather and under minimum load (200 W/phase, cos u = 0.7, in each node, Section 3). Aim is to identify the critical cases in which demand flexibility could be applied. Thus three different topology scenarios of PV penetration and one without PV installations are examined:
Losses deviation (%) 0.18 0.18 0.27 0.41 0.59 0.50 0.71 0.93 0.89 0.46
The output of the load flow is shown in Figs. 4–6. Figs. 4 and 5 present the current and the active phase losses in each branch of the line respectively; whereas Fig. 6 presents the phase voltages along the line. As expected, results differ significantly according to each configuration. Total line losses, for example, have increased from 168.68 W/phase in the scenario ‘‘PV at node 1’’ to 503 W/ phase in the scenario ‘‘PV at node 10’’ and to 4614.53 W/phase in the scenario ‘‘PV at all nodes’’. In the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’ the current and so the losses increased in all branches along the line compared with the baseline scenario without PV; whereas in the scenario ‘‘PV at node 1’’ – only the branch 0–1 is mainly affected (Figs. 4 and 5). Additionally, there is a rise in the voltage profile along the line in all scenarios, but more intense in the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’. For these scenarios, as a violation of the upper voltage limit (15% overvoltage, 1.15 230 V = 264.5 V) occurs, a demand flexibility is further investigated.
higher than with NEPLAN. Table 2 shows that branch current and power losses both differ from simulation results by less than 1% in all branches. The above validation has proved that, using the proposed approach, the load flow analysis of the radial LV feeder – taking into account demand and DG – can be performed accurately and simply without the need to run detailed power flow simulations.
5. Demand shifting analysis and results This section examines the effect of demand shifting in the integration of DG in radial LV feeder. The analysis is performed for a single-phase line with the same technical configuration as described in Section 4 and depicted in Fig. 3. The load flow analysis is performed using the analytical approach proposed in Section 2. PV systems are chosen for the analysis as they could lead to high probability of the critical case, i.e. maximum generation and low demand. The shifting of demand is aimed at keeping the line voltage within the limits and the PV systems in operation, which would otherwise have been switched off due to the inverter detecting faulty voltage conditions in the grid.
Fig. 4. Branch loading for different PV topology scenarios.
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Fig. 5. Active losses for different PV topology scenarios.
Fig. 6. Node voltages for different PV topology scenarios.
5.2. Application of flexible demand Considering the previous subsection, the flexible demand is adjusted to smooth the PV penetration effects in the grid. In voltage violation conditions flexible loads are triggered to shift their consumption. Thus, the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’ are further analysed. The aim here is to find out how many of these flexible loads and where should be shifted at the time of overvoltage in order to keep the voltage within an acceptable range.
5.2.1. Cases Three cases of load adjustment are studied for each of the two scenarios (‘‘PV at all nodes’’ and ‘‘PV at node 10’’): ‘‘Flexibility at all nodes’’: flexible loads are evenly distributed to all nodes; ‘‘Flexibility at node 10’’: flexible load is connected at node 10; ‘‘Flexibility at node 1’’: flexible load is connected at node 1. The required flexible loads are defined when the voltage profile falls back within the permissible limits, thus ensuring the operation of the PV systems in the affected nodes, which would otherwise be disconnected due to the voltage violation. Moreover, the three cases aim to present the optimal topology of the flexible load in terms of the least load to be shifted.
5.2.2. Results The results of the scenario ‘‘PV at all nodes’’ are presented in Table 3. In the ‘‘Flexibility at all nodes’’ case in order to prevent the disconnection of the PV systems, loads of 1100 W/phase (110 W/ phase in each node) should be shifted in that time. This value is the difference between the values in the ‘‘Nonflexible load’’ column and the ‘‘Flexibility at all nodes’’ column, representing the absolute amount of flexible load needed for voltage management. In the ‘‘Flexibility at node 10’’ case, on the other hand, at node 10 the user should shift 600 W/phase of its demand. The highest difference is presented in the last case where the demand should raise by 275% in total in the line, i.e. shifting 5500 W/phase in node 1. Obviously, adjustment of the demand also resulted in a decrease in line losses in all three cases. Nevertheless, the voltage in the affected node has been successfully pushed below the upper limit. Furthermore, Table 4 shows the relevant results for the scenario ‘‘PV at node 10’’ with the same load adjustment cases. Here, shifting in total 2050 W/phase (205 W/phase load at each node, ‘‘Flexibility at all nodes’’) or 1200 W/phase at node 10 (‘‘Flexibility at node 10’’) will decrease the voltage within the acceptable limits. On the other hand, in the ‘‘Flexibility at node 1’’ case, an extremely high shift of the load is needed at node 1 in order to decrease the voltage (10500 W/phase). Similarly to the scenario ‘‘PV at all nodes’’, demand adjustments in all three cases result in the decrease of line losses. Both scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’ showed that the less demanding case in terms of the degree of demand shifting is the ‘‘Flexibility at node 10’’ case, i.e. the load in the last node is adjusted. In this case the total demand as seen from the transformer is increased by 30% and 60% respectively, causing approximately the same results, i.e. voltage drop and losses decrease, as in the other cases. Considering the stiffness of the consumption behaviour, the feasibility of demand shifting triggers a deeper analysis in the optimal topologies to adopt flexibility schemes. 5.3. Sensitivity analysis At this point, the article proceeds with a more detailed sensitivity analysis in order to track the optimal topology of flexible demand in terms of the least load that needs to be shifted with the highest effect on the line voltage magnitude. 5.3.1. Cases The results in Tables 3 and 4 are validated by executing three new load shifting strategies in both ‘‘PV at all nodes’’ and ‘‘PV at node 10’’ scenarios. It is considered in both scenarios that flexible 5 kW load (DPtotal) is available for load shifting in the line as a constant amount. This flexible load is assumed to be either evenly distributed, or linearly distributed with an increasing tendency towards the end or the beginning of the line. Thus three cases are examined: ‘‘Even load flexibility’’, ‘‘More flexibility at the end’’ and ‘‘More flexibility at the beginning’’. Monte Carlo simulation technique is used so that several hundred repetitions, each time with a new randomly generated dispersion of the load along the line, are considered for reliable results [35]. For each case the load at node j and in repetition n is calculated as follows. ‘‘Even load flexibility’’: the average flexible load in all repetitions is evenly distributed along the line between nodes 1 and 10; For n = 1 to M, where M is the quantity of repetitions,
an;j DPLOADn;j ¼ DPtotal PN j¼1 an;j
ð15Þ
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I.T. Papaioannou et al. / Electrical Power and Energy Systems 44 (2013) 540–546 Table 3 Effect of the flexible demand topology in the ‘‘PV at all nodes’’ scenario. PV at all nodes
Nonflexible load
Flexibility at all nodes
Difference (%)
Flexibility at node 10
Difference (%)
Flexibility at node 1
Difference (%)
Line load (W/phase) Line losses (W/phase) Node 10 voltage (V)
2000.00 4614.53 265.91
3100.00 4436.30 264.47
55.00 3.86 0.54
2600.00 4480.61 264.49
30.00 2.90 0.53
7500.00 4374.27 264.51
275.00 5.20 0.50
Table 4 Effect of the flexible demand topology in the ‘‘PV at node 10’’ scenario. PV at node 10
Nonflexible load
Flexibility at all nodes
Difference (%)
Flexibility at node 10
Difference (%)
Flexibility at node 1
Difference (%)
Line load (W/phase) Line losses (W/phase) Node 10 voltage (V)
2000.00 4064.61 267.17
4050.00 3812.28 264.50
102.50 6.21 1.00
3200.00 3799.85 264.45
60.00 6.51 1.02
12500.00 3882.32 264.49
525.00 4.48 1.00
where N is the quantity of loaded nodes in the subject line and aj is a randomly generated variant from 0 to 1. ‘‘More flexibility at the end’’: the average flexible load in all repetitions is distributed linearly along the line with an increasing tendency along the line from node 1 to 10; For n = 1 to M
an;j ðA þ jÞ DPLOADn;j ¼ DPtotal PN j¼1 ðan;j ðA þ jÞÞ
ð16Þ
where A is a parameter which determines the rate of increasing or decreasing distribution tendency of the flexible load along the line. ‘‘More flexibility at the beginning’’: the average flexible load in all repetitions is distributed linearly along the line with a decreasing tendency along the line from node 1 to 10; For n = 1 to M
an;j ðAðN þ 1 jÞÞ DPLOADn;j ¼ DPtotal PN j¼1 ðan;j ðAðN þ 1 jÞÞÞ
ð17Þ
regards the voltage before applying the flexibility is estimated. Besides, this is the node with the highest voltage violation in both scenarios (Fig. 6). By decreasing this voltage within the limits, no overvoltage in any other node along the line is encountered as presented in [18]. In the scenario ‘‘PV at all nodes’’, the highest voltage reduction is achieved applying the ‘‘More flexibility at the end’’ case. In this case the voltage from 265.91 V is reduced to 258.68 V in average values, i.e. 2.72% decrease. In the scenario ‘‘PV at node 10’’, also applying the ‘‘More flexibility at the end’’ case leads to the highest voltage drop: from 267.17 V to 260.03 V (2.67% down). Applying other cases (‘‘Even load flexibility’’ and ‘‘More flexibility at the beginning’’), lower voltage reduction results are achieved: between 2.23% and 2.49%. Thus the highest effect on voltage reduction in both scenarios among the cases is reached in the ‘‘More flexibility at the end’’ case. In order to support this statement, a new scenario ‘‘50 kW PV at node 1’’ is studied assuming PV generation only at node 1. This scenario is similar to the scenario ‘‘PV at node 1’’ examined in Section 5.1, but in the scenario ‘‘50 kW PV at node 1’’ more extreme situations have been considered in order to encounter a voltage violation in the feeder:
Representative distribution of the average flexible load along the line after numerous repetitions (M) for each of the cases is presented in Fig. 7. In the figure and for all of the following analysis the parameter A is equated to 10. Depending on the case the average flexible load has even, increasing or decreasing distribution along the line with a total sum of 5 kW for all the cases.
The PV generation in node 1 has been increased to 50 kW/ phase; The distance between node 0 and 1 has been increased to 300 m (the other distances between successive nodes have remained the same, i.e. 60 m).
5.3.2. Results Voltage reduction results in the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’ applying the new demand shifting cases (‘‘Even load flexibility’’, ‘‘More flexibility at the end’’ and ‘‘More flexibility at the beginning’’) are presented in Fig. 8. For all the repetitions of the case concerned the average voltage decrease in node 10 as
Differently from the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’, voltage violation in the scenario ‘‘50 kW PV at node 1’’ appears at the beginning of the line in node 1. Applying the demand shifting cases ‘‘Even load flexibility’’, ‘‘More flexibility at the end’’ and ‘‘More flexibility at the beginning’’ to the scenario ‘‘50 kW PV at node 1’’, voltage in node 1 is reduced. Average results of this voltage reduction are presented also in Fig. 8. Similarly to the scenarios
Fig. 7. Representative average distribution of flexible load along the line in three cases.
Fig. 8. Voltage reduction results: at node 10 in the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’; at node 1 in the scenario ‘‘50 kW PV at node 1’’.
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‘‘PV at all nodes’’ and ‘‘PV at node 10’’, even if the PV generation is at the beginning of the line, a higher voltage decrease in the affected node 1 is achieved applying the flexible load at the end of the line: ‘‘More flexibility at the end’’ case. As a result, voltage dropped within the limit by 2.32% (to 258.37 V).. In contrast to the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’, in the scenario ‘‘50 kW PV at node 1’’ the topology of the flexible demand practically has no influence on voltage reduction. Voltage is decreased by approximately 2.3% in all cases. Nevertheless this implies that, in general, for a more direct and intense effect on the voltage management flexible load schemes should be mainly adopted at the end of the LV feeders. 6. Conclusions The present article addresses one of the major issues, namely the voltage violation, which is introduced by high DG penetration in LV radial feeders. Voltage violation can appear at minimum demand and high generation. In order to ensure the maximum energy yield of DG, there is a need to find a way of keeping the generation units connected without exceeding the voltage limits. Thus, the importance of demand shifting was assessed, confirming it as a useful strategy to keep the voltage along the feeder within the acceptable range without switching off the DG systems. Furthermore, and with regard to the difficulties in changing demand behaviours and patterns, the article examines the optimal topology of flexible demand along the feeder. In this way, the authors put forward a suggestion as to which customers along the line could be encouraged to shift their demand and more specifically at which nodes attention should be paid. In addition, the analytical approach developed for load flow analysis can be used in the planning of DG integration in LV radial feeders, since it is easy to implement and provides highly accurate results. Results showed that flexible demand is recommended to be deployed at the end of the feeder. In this case, there is less need for demand shifting in order to keep the voltage in a range while ensuring the maximum production of DG systems. As a result, innovative integrated energy solutions to be adopted in local level, as indicated in [2], and strategies should consider the influence of the loads in the end of LV feeders as they could make a major contribution to ensure high DG penetration in respect to power quality standards. References [1] Commission of the European communities. An energy policy for Europe, COM (2007) 1 final, Brussels, 2007.; 2010 [consulted 11.11]. [2] European commission. Energy 2020, a strategy for competitive, sustainable and secure energy. COM (2010) 639 final, Brussels. ; 2010 [consulted 11.11]. [3] European commission. A roadmap for moving to a competitive low carbon economy in 2050, COM (2011) 112 final, Brussels. ; 2011 [consulted 11.11]. [4] European commission. Impact assessment, a roadmap for moving to a competitive low carbon economy in 2050, COM (2011) 288 final, Brussels. ; 2011 [consulted 11.11]. [5] Eurostat. Energy statistics. [consulted 01.11]. [6] European commission, directorate-general for energy. european energy and transport. Trends 2030 – update 2009. . [7] European commission. Energy 2020, a strategy for competitive, sustainable and secure energy, COM(2010) 639 final, Brussels. ; 2010 [consulted 11.11].
[8] DIRECTIVE 2009/28/EC of the European parliament and of the council of 23 April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing directives 2001/77/EC and 2003/30/EC. Official journal of the European union; 2009. [9] International energy agency (IEA). Empowering variable renewables: options for flexible electricity systems, Paris.; 2008 [consulted 11.11]. [10] Oshiro M, Tanaka K, Uehara A, Senjyu T, Miyazato Y, Yona A, et al. Optimal voltage control in distribution systems with coordination of distribution installations. Elect Power Energy Syst 2010;32:1125–9. [11] IEA. Impacts of power penetration from photovoltaic power systems in distribution networks, IEA Report PVPS T5-10. ; 2002 [consulted 11.11]. [12] Katiraei F, Mauch K, Dignard-Bailey L. Integration of photovoltaic power systems in high penetration. Int J Distrib Energy Res 2006;3(3):207–16. [13] Oshiro Masato, Tanaka Kenichi, Senjyu Tomonobu, Toma Shohei, Yona Atsushi, Saber Ashmed Yousuf, et al. Optimal voltage control in distribution systems using PV generators. Elect Power Energy Syst 2011;33:485–7. [14] Mogos EF, Guillaud X. A voltage regulation system for distributed generation. Power Syst Conf Expos IEEE PES 2004;2:787–97. [15] Kiprakis AE, Wallace AR. Hybrid control of distributed generators connected to weak rural networks to mitigate voltage variation. In: CIRED meeting Barcelona; 2003. [16] Dai C, Baghzouz Y. On the voltage profile of distribution feeders with distributed generation. Conver Deliv Elect Energy 21st Cent 2008:1–8. [17] Zhang J, Cheng H, Wanga C. Technical and economic impacts of active management on distribution network. Elect Power Energy Syst 2009;3:130–8. [18] Papaioannou I, Alexiadis M, Demoulias C, Labridis D, Dokopoulos P. Modeling and field measurements of photovoltaic units connected to LV grid. Study of penetration scenarios. IEEE Trans Power Deliv 2011;26(2):979–88. [19] The association of home appliance manufacturers. Smart grid white paper: the home appliance industry’s principles and requirements for achieving a widely accepted smart grid, Washington. ; 2009 [consulted 11.11]. [20] Belhomme R, Sebastian M, Diop A, Entem M, Bouffard F, Valtorta G, et al. ADDRESS technical and commercial conceptual architectures.; 2009 [consulted 11.11]. [21] Ueda Y, Korokawa K, Tanabe T, Kimatura T, Sugihara H. Analysis results of output power loss due to the grid voltage rise in grid-connected photovoltaic power generation systems. IEEE Trans Indust Electron 2008;55(7):2744–7. [22] Voltage characteristics of electricity supplied by public distribution system. Standard EN 50160; 2004. [23] Standard for interconnecting distributed resources with electric power systems. IEEE standard 1547; 2003. [24] Pearce JM. Expanding photovoltaic penetration with residential distributed generation from hybrid solar photovoltaic and combined heat and power systems. Energy 2009;34(11):1947–57. [25] Clastres C, Ha Pham TT, Wurtz F, Bacha S. Ancillary services and optimal household energy management with photovoltaic production. Energy 2010;35(1):55–9. [26] Zangiabadi M, Feuillet R, Lesani H, Hadj-Said N, Kvaløy JT. Assessing the performance and benefits of customer distributed generation developers under uncertainties. Energy 2011;36(3):1703–9. [27] Affonso Carolina M, Da Silva Luiz CP. Potential benefits of implementing load management to improve power system security. Elect Power Energy Syst 2010;32:704–6. [28] Nikhil Gudi, Lingfeng Wang, Vijay Devabhaktuni. A demand side management based simulation platform incorporating heuristic optimization for management of household appliances. Elect Power Energy Syst 2012;43:185–8. [29] Leão RPS, Barroso GC, Sampaio RF, Almada JB, Lima CFP, Rego MCO, et al. The future of low voltage networks: moving from passive to active. Elect Power Energy Syst 2011;33:1506–16. [30] Giordano V, et al. Smart grid projects in Europe: lessons learned and current developments. European commission. Joint Research Centre, Institute for Energy. ; 2011 [consulted 11.11]. [31] Marinopoulos AG, Alexiadis MP, Dokopoulos PS. A correlation index to evaluate impact of PV installation on Joule losses. IEEE Trans Power Syst 2010;99:1564–8. [32] Bouhouras AS, Marinopoulos AG, Labridis DP, Dokopoulos PS. Installation of PV systems in Greece – reliability improvement in the transmission and distribution system. Elect Power Syst Res 2008;80:547–8. [33] NEPLAN version 5.5.0 Copyright Ó 1988–2012. . [34] DISPOWER. Distributed generation with high penetration of renewable energy sources. ; 2005 [consulted 11.11]. [35] Singh R, Manitsas E, Pal BC, Strbac G. A recursive Bayesian approach for identification of network configuration changes in distribution system state estimation. IEEE Trans Power Syst 2010;25(3):1329–37.
Contents lists available at SciVerse ScienceDirect
Electrical Power and Energy Systems journal homepage: www.elsevier.com/locate/ijepes
Demand shifting analysis at high penetration of distributed generation in low voltage grids Ioulia T. Papaioannou ⇑, Arturs Purvins, Evangelos Tzimas European Commission1, DG JRC, Institute for Energy and Transport, Postbus 2, 1755 ZG Petten, The Netherlands
a r t i c l e
i n f o
Article history: Received 22 November 2011 Received in revised form 11 July 2012 Accepted 25 July 2012 Available online 26 September 2012 Keywords: Flexible demand Demand shifting Renewable energy sources Distributed generation Photovoltaic Smart grids
a b s t r a c t One of the main challenges that Europe has to face is to ensure the swift deployment of renewable energy sources by increasing their share in the energy generation mix to 20% by 2020, considering the large-scale deployment of new electricity generators in low voltage (LV) grids. The article highlights the contribution of electricity end users to achieving this target as the European Union is eager to unlock their potential in the energy sector. This article examines the penetration of distributed generation from a technical point of view and explores the possible barriers that may arise under high penetration conditions. Specifically, in the critical case of low demand and high distributed generation, the voltage could exceed the acceptable range in the LV feeder, and this can lead to the disconnection of the generator. Thus, a simple approach is used to calculate the voltage profile along the LV feeder and to estimate losses and loading. As the estimation takes the demand into account, this is followed by a sensitivity analysis – using the Monte Carlo technique – in order to track the optimal topology of flexible demand. The article suggests that, in critical cases, customers at the end of the LV feeder would be the main contributors to ensuring the uninterrupted operation of distributed generation within power quality standards. Ó 2012 Elsevier Ltd. All rights reserved.
1. Introduction In 2008, the European Union (EU) adopted an energy and climate action plan, which sets ambitious targets for 2020, namely the reduction of greenhouse gas emissions by 20% from 1990 levels, an increase in the share of renewable energy sources (RESs) to 20% of gross energy consumption and a 20% improvement in energy efficiency [1]. Meeting these targets should be seen as just the first step in the transition to a low carbon society. The EU has made a long-term commitment to cutting European greenhouse gas emissions by 80–95% by 2050 [2], which will be achieved with the near-complete decarbonisation of the power sector [3]. In this context, it is expected that RES, mainly wind and solar, will provide about half of the electricity generated in the EU in 2050 [4], which implies that the installed capacities of such energy technologies are likely to increase dramatically in the years to come. Indeed, 62% of electricity generation capacity installed in 2009 in the EU was RES power, mainly in the form of wind farms, but also solar plants [5]. A large number of these RES plants, as distributed generation (DG) units, will be connected to the low voltage (LV) grid. However, the success of European energy and climate policies also depends on the active involvement of the energy end user ⇑ Corresponding author. Tel.: +31 224565171. E-mail address: [email protected] (I.T. Papaioannou). The views expressed are purely those of the authors and may not in any circumstances be regarded as stating an official position of the European Commission. 1
0142-0615/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijepes.2012.07.054
[6–8]. Therefore, measures have been taken to increase energy savings, disseminate innovative solutions, such as electrification of transport and real time energy pricing, and to improve energy efficiency and energy autonomy in buildings. As part of the same approach, the EU is taking forward a major European initiative on ‘smart grids’ to interlink the whole electricity grid system, while making power grids more intelligent, efficient and reliable [2]. The major issues relating to the penetration of DG include the technical constraints and the tolerance of LV grids to adopt new dispersed power generators. The most significant challenge that is emerging as a result of the increasing penetration of DG is that of voltage rise [9]. The literature proposes methods of voltage control in areas where DG is deployed in order to resolve violations of voltage limits [10–13]. However, so far this issue has been addressed only from the perspective of power generation [14–16] or the distributed network operator (DNO) [17]. The present article explores this issue from consumer perspective, with a view to identifying the potential impact of demand management in LV feeders with high penetration of DG. The analysis is based on a scenario that deploys the integration of photovoltaic (PV) units in LV grids to address the issue and assess the optimal shifting of flexible demand along the feeder. Under conditions of high PV generation and low demand along the LV feeder, the risk that the voltage will exceed the upper limit at some points becomes more likely [18]. Conventionally the PV inverter, by detecting an overvoltage, obliges the PV systems connected to the respective points to be disconnected until the voltage
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is back within the acceptable range [16,19,20]. This disconnection prevents PV systems from producing their peak power most of the time [21]. Therefore, this analysis was considered essential, since – in order to increase the feasibility as well as the installed capacity – the maximum energy yield of distributed PV systems, i.e. the MWh/year, needs to be ensured [14]. The present analysis considers power quality restrictions imposed by the EN 50160 [22] and IEEE 1547 [23] standards, with acceptable voltage range: +15% and 20% of the nominal value. Furthermore, the conclusions of this analysis will be applicable to other DGs from uncontrollable RES such as small wind farms. Under the above concept, and in support of the effort to boost the integration of DG in compliance with power quality standards, the present article firstly addresses the technical issues arising from the connection of DG in LV feeders. Given that a significant fraction of the household demand cannot be met in real time by PV generation [24], the article explores the role of demand shifting in diminishing the voltage rise effects of DG. Explicitly the article focuses on the optimal topology of the flexible demand along the LV feeder. Thus, demand management is seen from a technical point of view, beyond the economic aspects which have already been analysed [25–28]. Considering the practical difficulties in changing the demand behaviour, optimization is defined as the solution in which the least amount of demand shifting along the feeder is needed in order to ensure the maximum effect on the voltage management. It should be noted that demand shifting does not mean the increasing of the total load, but changing the time of day when the load is switched on. Thus, the overall demand of the user at the end of the day remains the same as if it was being inflexible. This demand shifting can be achieved in ‘smart grids’ where communication between flexible loads and voltage levels in the LV feeder is possible [29]; or in a feeder without centralized control where demand is simply shifted to a specific time of the day, e.g. when both low demand and high generation are highly likely. These ‘smart’ flexible loads, e.g. smart washing machines, are currently undergoing demonstration trials as part of various ‘smart grid’ projects [30]. In order to carry out this analysis, the authors develop a simple analytical approach to calculate the voltage profile along a radial LV feeder with connected DG systems. In addition, feeder losses and loading data are calculated, which also raises significant issues of DG integration [31,32]. The approach takes into account demand and PV generation along the feeder, and also the configuration of the distribution transformer and the subject line. The approach is implemented in common spreadsheets and tested against detailed simulations in a power system modelling tool, NEPLAN [33]. As a case study, a 10 node feeder is used where the operation of PV systems is examined firstly under inflexible demand and then by deploying demand shifting.
2. Analytical approach The following analytical approach is developed for load flow analysis in a radial LV feeder. This approach can be applied for a single-phase as well as for a three-phase line. For explanation reasons of the approach a line diagram with N nodes and with a transformer as shown in Fig. 1 is used. At the line, N loads and N DG systems are connected with PLOADj and QLOADj being active and reactive load respectively and PDGj and QDGj being active and reactive power generation respectively at node j. Additionally, PLOSSj,j+1 and QLOSSj,j+1 are respectively the active and reactive power losses on the line for the branch between the nodes j and j + 1. The distance between nodes j and j + 1 is lj,j+1. The voltage U0 at the secondary terminals at node 0 of the distribution transformer is considered to be the reference voltage. The voltage at node j is
Uj. In the practical situations that are encountered in LV feeders supplying households, the loads can be single phase connected alternately in different phases. However, when DG systems are connected at any node, the utility – depending on the country of installation – may require them to be three-phase in order to avoid imbalances. It should be noted that node quantities are expressed by a single indicator equal to the number of the specific node, whereas branch quantities are expressed by two indicators expressing the two nodes between which the specific branch is found. The voltage drop across the branch from node j to node j + 1 can be calculated with the aid of the phasor diagram.
DU j;jþ1 ¼ jU j j jU jþ1 j ¼ jU jþ1 j þ Ij;jþ1 Rj;jþ1 cos /jþ1 þ Ij;jþ1 X j;jþ1 sin ujþ1 jU jþ1 j ¼ Ij;jþ1 cos /jþ1 ðRj;jþ1 þ X j;jþ1 tan /jþ1 Þ
ð1Þ
where Rj,j+1 and Xj,j+1 are the branch resistance and reactance respectively, Ij,j+1 is the branch current between the nodes j and j + 1 and uj+1 is the angle between this current and Uj+1. If R0 is resistance and X0 is reactance per km of the line, (1) can be rewritten as:
DU j;jþ1 ¼ Ij;jþ1 cos /jþ1 lj;jþ1 ðR0 þ X 0 tan /jþ1 Þ
ð2Þ
By replacing
Ij;jþ1 ¼
P jþ1;N U jþ1 cos ujþ1
ð3Þ
Q jþ1;N Pjþ1;N
ð4Þ
and
tan ujþ1 ¼
the voltage change can be expressed as:
DU j;jþ1 ¼ lj;jþ1
Q jþ1;N Pjþ1;N R0 þ X 0 U jþ1 Pjþ1;N
ð5Þ
where the active power Pj+1,N includes all the active loads and PV systems and also the active losses in the branch between the nodes j + 1 and N. Pj+1,N is calculated with the following equation:
Pjþ1;N ¼
XN i¼jþ1
ðPLOADi PDGi Þ þ
XN1
P i¼jþ1 LOSSi;iþ1
ð6Þ
Relatively, Qj+1,N is the sum of all the reactive loads (QDGj is positive in case the DG system consumes reactive power and negative in case it generates) and reactive power losses in the branch between the nodes j + 1 and N:
Q jþ1;N ¼
XN i¼jþ1
ðQ LOADi þ Q DGi Þ þ
XN1 i¼jþ1
Q LOSSi;iþ1
ð7Þ
Obviously, both the sums of active and reactive losses have an upper limit of N 1 expressing the last losses along the line between N 1 and N node. In order to estimate the active and reactive losses of the line, the branch current is needed and can be also expressed as:
Ij;jþ1 ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P2jþ1;N þ Q 2jþ1;N U jþ1
ð8Þ
So, PLOSSj,j+1 and QLOSSj,j+1 of the branch between nodes j and j + 1 can now be estimated:
PLOSSj;jþ1 ¼ R0 lj;jþ1 I2j;jþ1
ð9Þ
Q LOSSj;jþ1 ¼ X 0 lj;jþ1 I2j;jþ1
ð10Þ
The voltage in node j is calculated with regard to the voltage change from all the previous nodes and the voltage drop on the transformer. Thus:
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Fig. 1. Single-line diagram of a radial LV feeder.
Uj ¼
Xj1
ðU 0 DU i;iþ1 Þ i¼1 XN 1 XN R0 k¼1 ðPLOADk PDGk Þ þ X 0 k¼1 ðQ LOADk þ Q DGk Þ þ U0 ð11Þ
R0 and X0 are the equivalent resistance and reactance of the distribution transformer, referred to the LV side. In order to solve the above equations, an iterative procedure has been used by starting from the last node N of the line and estimating the total active and reactive power from (6) and (7) as PN1;N ¼ P LOADN P DGN and Q N1;N ¼ Q LOADN þ Q DGN . The relative voltage change can be now calculated with the aid of (5), while an approximation of the branch current is made with (8). In the latter equation, Uj+1 is replaced by U0 in order to be solvable. The same procedure continues gradually in descending order for all the other nodes, i.e. N 1 to 1, until node 1 is reached. 3. Assumptions The analytical approach described in the previous section is solvable and applicable with the following assumptions: (1) The replacement of Uj+1 with U0, so as to make (5) and (8) solvable:
DU j;jþ1
Q jþ1;N P jþ1;N R0 þ X 0 ¼ lj;jþ1 U0 Pjþ1;N
Ij;jþ1;approx ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P2jþ1;N þ Q 2jþ1;N U0
ð12Þ
ð13Þ
This assumption introduces a simplification and leads to more conservative estimates. As regards the branch current, it is corrected later with the use of the calculated voltages, since they have already been estimated by the abovementioned procedure. In the case of the voltage, the assumption is based on the statement that calculations should be made for the worst case: the maximum voltage rise appears when all the DG systems in the line operate close to their nominal power and, at the same time, the loads are at minimum [7,12]. One could assume that all the loads are zero, but this is not realistic. A realistic assumption for a household feeder is to consider that, in each home, only the refrigerator is operating. A typical value for the refrigerator load is 200 W/phase, cos u = 0.7, at the rated phase voltage 230 V. In this regard, we can safely assume that the DG production is greater than the load demand of the feeder, causing reverse power flow [21,34]. Thus, the voltage will be greater than U0, which represents the voltage of the transformer on the LV side, even from the first node and beyond, and the voltage profile along the line will show a rise, as in Fig. 2. In Eq. (5), which is principally affected by the above replacement, the calculated voltage rise is greater and esti-
Fig. 2. Voltage profile in a LV line at energy flow from node N to node 0.
mations are more restricted, thus leading to more conservative and reliable results. (2) The approach does not take account of the voltage drop along the neutral and assumes a balanced three-phased system. Under circumstances of minimum load demand and high DG integration, the asymmetry introduced by the load is minor in relation to the symmetry of the three phased DG generation. Thus, the voltage drop along the neutral conductor is assumed to be zero. 4. Validation with NEPLAN In order to verify the proposed analytical approach, a comparison with NEPLAN modelling tool is performed. A single-phase LV radial line supplying 10 households and 10 DG systems, e.g. PV systems, as depicted in Fig. 3 is used. The three-phase transformer parameters are assumed to be: 250 kVA, secondary windings voltage 0.4 kV, Rtr = 7.04 mX and Xtr = 37.7 mX. The single-phase line connected to the one of the three secondary transformer windings is assumed to be an overhead 35 mm2 line (steel reinforced aluminium conductor, ACSR, R0 = 0.576 X/km, X0 = 0.397 X/km). Such a line is characterized with 224 A rated current and consequently with a 51.52 kW/phase capacity. The distance between nodes is considered to be 60 m. The minimum household load of 200 W (cos u = 0.7, see Section 3) and PV generation of 5 kW (cos u = 0) close to the nominal line capacity are assumed to be connected to the nodes from 1 to 10. In NEPLAN modelling, the ‘‘Current Iteration’’ method is used which is proper for power flows on the distribution level. The comparison of the NEPLAN modelling with the relevant results acquired by the proposed approach is shown in Tables 1 and 2 and includes: voltage at nodes, branch current and power losses in each branch. The relative deviation of each parameter is estimated as:
e¼
Aneplan Aapproach Aneplan
ð14Þ
where Aneplan and Aapproach are the results obtained from NEPLAN modelling and the proposed approach respectively. The phase voltage values at the nodes from 1 to 10, shown in Table 1, justify the first assumption of the previous section. Thus the voltage estimated with the approach on average is slightly
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Fig. 3. Single-line diagram with 10 households.
5.1. Identification of critical scenarios
Table 1 Comparison of node voltages. Node
1 2 3 4 5 6 7 8 9 10
Node voltage (V)
Voltage deviation (%)
Approach
NEPLAN
236.12 241.79 246.94 251.55 255.57 258.97 261.73 263.81 265.21 265.91
236.94 242.37 247.22 251.49 255.13 258.13 260.56 262.41 263.62 264.25
0.35 0.24 0.11 0.02 0.17 0.33 0.45 0.54 0.60 0.63
‘‘PV at all nodes’’: ten PV systems of 5 kW/phase are installed in each node from 1 to 10 (as in Section 4); ‘‘PV at node 10’’: one PV system of 30 kW/phase installed in the last node, i.e. node 10; ‘‘PV at node 1’’: one PV system of 30 kW/phase connected at the first node, i.e. node 1; ‘‘Without PV’’: baseline scenario without PV installations.
Table 2 Comparison of branch current and active power losses. Branch
0–1 1–2 2–3 3–4 4–5 5–6 6–7 7–8 8–9 9–10
Branch current (A) Approach
NEPLAN
188.97 168.76 148.90 129.39 110.22 91.48 72.84 54.43 36.19 18.07
189.00 169.00 149.00 130.00 111.00 92.00 73.00 55.00 36.00 18.00
Current deviation (%)
Branch losses (W/phase) Approach
NEPLAN
0.02 0.14 0.07 0.47 0.70 0.56 0.22 1.04 0.53 0.38
1234.08 984.26 766.25 578.62 419.83 289.22 183.35 102.37 45.26 11.28
1236.33 986.00 768.33 581.00 422.33 290.67 184.67 103.33 45.67 11.33
Initially, load flow analysis in the feeder is performed in sunny weather and under minimum load (200 W/phase, cos u = 0.7, in each node, Section 3). Aim is to identify the critical cases in which demand flexibility could be applied. Thus three different topology scenarios of PV penetration and one without PV installations are examined:
Losses deviation (%) 0.18 0.18 0.27 0.41 0.59 0.50 0.71 0.93 0.89 0.46
The output of the load flow is shown in Figs. 4–6. Figs. 4 and 5 present the current and the active phase losses in each branch of the line respectively; whereas Fig. 6 presents the phase voltages along the line. As expected, results differ significantly according to each configuration. Total line losses, for example, have increased from 168.68 W/phase in the scenario ‘‘PV at node 1’’ to 503 W/ phase in the scenario ‘‘PV at node 10’’ and to 4614.53 W/phase in the scenario ‘‘PV at all nodes’’. In the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’ the current and so the losses increased in all branches along the line compared with the baseline scenario without PV; whereas in the scenario ‘‘PV at node 1’’ – only the branch 0–1 is mainly affected (Figs. 4 and 5). Additionally, there is a rise in the voltage profile along the line in all scenarios, but more intense in the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’. For these scenarios, as a violation of the upper voltage limit (15% overvoltage, 1.15 230 V = 264.5 V) occurs, a demand flexibility is further investigated.
higher than with NEPLAN. Table 2 shows that branch current and power losses both differ from simulation results by less than 1% in all branches. The above validation has proved that, using the proposed approach, the load flow analysis of the radial LV feeder – taking into account demand and DG – can be performed accurately and simply without the need to run detailed power flow simulations.
5. Demand shifting analysis and results This section examines the effect of demand shifting in the integration of DG in radial LV feeder. The analysis is performed for a single-phase line with the same technical configuration as described in Section 4 and depicted in Fig. 3. The load flow analysis is performed using the analytical approach proposed in Section 2. PV systems are chosen for the analysis as they could lead to high probability of the critical case, i.e. maximum generation and low demand. The shifting of demand is aimed at keeping the line voltage within the limits and the PV systems in operation, which would otherwise have been switched off due to the inverter detecting faulty voltage conditions in the grid.
Fig. 4. Branch loading for different PV topology scenarios.
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Fig. 5. Active losses for different PV topology scenarios.
Fig. 6. Node voltages for different PV topology scenarios.
5.2. Application of flexible demand Considering the previous subsection, the flexible demand is adjusted to smooth the PV penetration effects in the grid. In voltage violation conditions flexible loads are triggered to shift their consumption. Thus, the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’ are further analysed. The aim here is to find out how many of these flexible loads and where should be shifted at the time of overvoltage in order to keep the voltage within an acceptable range.
5.2.1. Cases Three cases of load adjustment are studied for each of the two scenarios (‘‘PV at all nodes’’ and ‘‘PV at node 10’’): ‘‘Flexibility at all nodes’’: flexible loads are evenly distributed to all nodes; ‘‘Flexibility at node 10’’: flexible load is connected at node 10; ‘‘Flexibility at node 1’’: flexible load is connected at node 1. The required flexible loads are defined when the voltage profile falls back within the permissible limits, thus ensuring the operation of the PV systems in the affected nodes, which would otherwise be disconnected due to the voltage violation. Moreover, the three cases aim to present the optimal topology of the flexible load in terms of the least load to be shifted.
5.2.2. Results The results of the scenario ‘‘PV at all nodes’’ are presented in Table 3. In the ‘‘Flexibility at all nodes’’ case in order to prevent the disconnection of the PV systems, loads of 1100 W/phase (110 W/ phase in each node) should be shifted in that time. This value is the difference between the values in the ‘‘Nonflexible load’’ column and the ‘‘Flexibility at all nodes’’ column, representing the absolute amount of flexible load needed for voltage management. In the ‘‘Flexibility at node 10’’ case, on the other hand, at node 10 the user should shift 600 W/phase of its demand. The highest difference is presented in the last case where the demand should raise by 275% in total in the line, i.e. shifting 5500 W/phase in node 1. Obviously, adjustment of the demand also resulted in a decrease in line losses in all three cases. Nevertheless, the voltage in the affected node has been successfully pushed below the upper limit. Furthermore, Table 4 shows the relevant results for the scenario ‘‘PV at node 10’’ with the same load adjustment cases. Here, shifting in total 2050 W/phase (205 W/phase load at each node, ‘‘Flexibility at all nodes’’) or 1200 W/phase at node 10 (‘‘Flexibility at node 10’’) will decrease the voltage within the acceptable limits. On the other hand, in the ‘‘Flexibility at node 1’’ case, an extremely high shift of the load is needed at node 1 in order to decrease the voltage (10500 W/phase). Similarly to the scenario ‘‘PV at all nodes’’, demand adjustments in all three cases result in the decrease of line losses. Both scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’ showed that the less demanding case in terms of the degree of demand shifting is the ‘‘Flexibility at node 10’’ case, i.e. the load in the last node is adjusted. In this case the total demand as seen from the transformer is increased by 30% and 60% respectively, causing approximately the same results, i.e. voltage drop and losses decrease, as in the other cases. Considering the stiffness of the consumption behaviour, the feasibility of demand shifting triggers a deeper analysis in the optimal topologies to adopt flexibility schemes. 5.3. Sensitivity analysis At this point, the article proceeds with a more detailed sensitivity analysis in order to track the optimal topology of flexible demand in terms of the least load that needs to be shifted with the highest effect on the line voltage magnitude. 5.3.1. Cases The results in Tables 3 and 4 are validated by executing three new load shifting strategies in both ‘‘PV at all nodes’’ and ‘‘PV at node 10’’ scenarios. It is considered in both scenarios that flexible 5 kW load (DPtotal) is available for load shifting in the line as a constant amount. This flexible load is assumed to be either evenly distributed, or linearly distributed with an increasing tendency towards the end or the beginning of the line. Thus three cases are examined: ‘‘Even load flexibility’’, ‘‘More flexibility at the end’’ and ‘‘More flexibility at the beginning’’. Monte Carlo simulation technique is used so that several hundred repetitions, each time with a new randomly generated dispersion of the load along the line, are considered for reliable results [35]. For each case the load at node j and in repetition n is calculated as follows. ‘‘Even load flexibility’’: the average flexible load in all repetitions is evenly distributed along the line between nodes 1 and 10; For n = 1 to M, where M is the quantity of repetitions,
an;j DPLOADn;j ¼ DPtotal PN j¼1 an;j
ð15Þ
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Nonflexible load
Flexibility at all nodes
Difference (%)
Flexibility at node 10
Difference (%)
Flexibility at node 1
Difference (%)
Line load (W/phase) Line losses (W/phase) Node 10 voltage (V)
2000.00 4614.53 265.91
3100.00 4436.30 264.47
55.00 3.86 0.54
2600.00 4480.61 264.49
30.00 2.90 0.53
7500.00 4374.27 264.51
275.00 5.20 0.50
Table 4 Effect of the flexible demand topology in the ‘‘PV at node 10’’ scenario. PV at node 10
Nonflexible load
Flexibility at all nodes
Difference (%)
Flexibility at node 10
Difference (%)
Flexibility at node 1
Difference (%)
Line load (W/phase) Line losses (W/phase) Node 10 voltage (V)
2000.00 4064.61 267.17
4050.00 3812.28 264.50
102.50 6.21 1.00
3200.00 3799.85 264.45
60.00 6.51 1.02
12500.00 3882.32 264.49
525.00 4.48 1.00
where N is the quantity of loaded nodes in the subject line and aj is a randomly generated variant from 0 to 1. ‘‘More flexibility at the end’’: the average flexible load in all repetitions is distributed linearly along the line with an increasing tendency along the line from node 1 to 10; For n = 1 to M
an;j ðA þ jÞ DPLOADn;j ¼ DPtotal PN j¼1 ðan;j ðA þ jÞÞ
ð16Þ
where A is a parameter which determines the rate of increasing or decreasing distribution tendency of the flexible load along the line. ‘‘More flexibility at the beginning’’: the average flexible load in all repetitions is distributed linearly along the line with a decreasing tendency along the line from node 1 to 10; For n = 1 to M
an;j ðAðN þ 1 jÞÞ DPLOADn;j ¼ DPtotal PN j¼1 ðan;j ðAðN þ 1 jÞÞÞ
ð17Þ
regards the voltage before applying the flexibility is estimated. Besides, this is the node with the highest voltage violation in both scenarios (Fig. 6). By decreasing this voltage within the limits, no overvoltage in any other node along the line is encountered as presented in [18]. In the scenario ‘‘PV at all nodes’’, the highest voltage reduction is achieved applying the ‘‘More flexibility at the end’’ case. In this case the voltage from 265.91 V is reduced to 258.68 V in average values, i.e. 2.72% decrease. In the scenario ‘‘PV at node 10’’, also applying the ‘‘More flexibility at the end’’ case leads to the highest voltage drop: from 267.17 V to 260.03 V (2.67% down). Applying other cases (‘‘Even load flexibility’’ and ‘‘More flexibility at the beginning’’), lower voltage reduction results are achieved: between 2.23% and 2.49%. Thus the highest effect on voltage reduction in both scenarios among the cases is reached in the ‘‘More flexibility at the end’’ case. In order to support this statement, a new scenario ‘‘50 kW PV at node 1’’ is studied assuming PV generation only at node 1. This scenario is similar to the scenario ‘‘PV at node 1’’ examined in Section 5.1, but in the scenario ‘‘50 kW PV at node 1’’ more extreme situations have been considered in order to encounter a voltage violation in the feeder:
Representative distribution of the average flexible load along the line after numerous repetitions (M) for each of the cases is presented in Fig. 7. In the figure and for all of the following analysis the parameter A is equated to 10. Depending on the case the average flexible load has even, increasing or decreasing distribution along the line with a total sum of 5 kW for all the cases.
The PV generation in node 1 has been increased to 50 kW/ phase; The distance between node 0 and 1 has been increased to 300 m (the other distances between successive nodes have remained the same, i.e. 60 m).
5.3.2. Results Voltage reduction results in the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’ applying the new demand shifting cases (‘‘Even load flexibility’’, ‘‘More flexibility at the end’’ and ‘‘More flexibility at the beginning’’) are presented in Fig. 8. For all the repetitions of the case concerned the average voltage decrease in node 10 as
Differently from the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’, voltage violation in the scenario ‘‘50 kW PV at node 1’’ appears at the beginning of the line in node 1. Applying the demand shifting cases ‘‘Even load flexibility’’, ‘‘More flexibility at the end’’ and ‘‘More flexibility at the beginning’’ to the scenario ‘‘50 kW PV at node 1’’, voltage in node 1 is reduced. Average results of this voltage reduction are presented also in Fig. 8. Similarly to the scenarios
Fig. 7. Representative average distribution of flexible load along the line in three cases.
Fig. 8. Voltage reduction results: at node 10 in the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’; at node 1 in the scenario ‘‘50 kW PV at node 1’’.
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‘‘PV at all nodes’’ and ‘‘PV at node 10’’, even if the PV generation is at the beginning of the line, a higher voltage decrease in the affected node 1 is achieved applying the flexible load at the end of the line: ‘‘More flexibility at the end’’ case. As a result, voltage dropped within the limit by 2.32% (to 258.37 V).. In contrast to the scenarios ‘‘PV at all nodes’’ and ‘‘PV at node 10’’, in the scenario ‘‘50 kW PV at node 1’’ the topology of the flexible demand practically has no influence on voltage reduction. Voltage is decreased by approximately 2.3% in all cases. Nevertheless this implies that, in general, for a more direct and intense effect on the voltage management flexible load schemes should be mainly adopted at the end of the LV feeders. 6. Conclusions The present article addresses one of the major issues, namely the voltage violation, which is introduced by high DG penetration in LV radial feeders. Voltage violation can appear at minimum demand and high generation. In order to ensure the maximum energy yield of DG, there is a need to find a way of keeping the generation units connected without exceeding the voltage limits. Thus, the importance of demand shifting was assessed, confirming it as a useful strategy to keep the voltage along the feeder within the acceptable range without switching off the DG systems. Furthermore, and with regard to the difficulties in changing demand behaviours and patterns, the article examines the optimal topology of flexible demand along the feeder. In this way, the authors put forward a suggestion as to which customers along the line could be encouraged to shift their demand and more specifically at which nodes attention should be paid. In addition, the analytical approach developed for load flow analysis can be used in the planning of DG integration in LV radial feeders, since it is easy to implement and provides highly accurate results. Results showed that flexible demand is recommended to be deployed at the end of the feeder. In this case, there is less need for demand shifting in order to keep the voltage in a range while ensuring the maximum production of DG systems. As a result, innovative integrated energy solutions to be adopted in local level, as indicated in [2], and strategies should consider the influence of the loads in the end of LV feeders as they could make a major contribution to ensure high DG penetration in respect to power quality standards. References [1] Commission of the European communities. An energy policy for Europe, COM (2007) 1 final, Brussels, 2007.
[8] DIRECTIVE 2009/28/EC of the European parliament and of the council of 23 April 2009 on the promotion of the use of energy from renewable sources and amending and subsequently repealing directives 2001/77/EC and 2003/30/EC. Official journal of the European union; 2009. [9] International energy agency (IEA). Empowering variable renewables: options for flexible electricity systems, Paris.