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Design criteria for a power management system for microgrids with renewable sources
Electric Power Systems Research 122 (2015) 168–179
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Design criteria for a power management system for microgrids with renewable sources P. Pinceti a,∗ , M. Vanti a , C. Brocca b , M. Carnesecchi b , G.P. Macera b a DITEN Department of Electrical, Electronic and Telecommunication Engineering and Naval Architecture of University of Genoa, via all’Opera Pia 11a, 16145 Genova, Italy b NIDEC-ASI SpA, Corso Perrone 11, 16152 Genova, Italy
a r t i c l e
i n f o
Article history: Received 24 March 2014 Received in revised form 5 December 2014 Accepted 13 January 2015 Keywords: Power management system Load-shedding Generator-shedding Microgrid Renewable Energy Fuzzy Logic
a b s t r a c t The paper describes the control functions that a power management system (PMS) needs for controlling a microgrid, with both conventional and renewable sources. According to the IEEE 1547.4, distributed resources island systems – or in brief “microgrids” – are active networks containing both loads and distributed generators, and may require a modification of their control logic if they are connected to a grid or not. A fast load or generator shedding actions may also be required to preserve system stability in case the microgrid switches from connected to islanded. Today, most industrial networks are designed to run also in islanded mode, while in public networks transmission system operators (TSO) generally do not allow islands. The presence of renewable sources that are partially not controllable requires the re-definition of the control logic compared with microgrids where only fully controllable generators are present. PMS of a microgrid has a double function: - to guarantee the stable operation of the system in presence of the unpredictable variations caused by renewable sources and loads, - to optimize the energy production of renewable and conventional sources. The logic described in the paper was implemented in a PMS that was tested with a software simulator prior to the installation in a real microgrid. The paper reports the results of tests. © 2015 Elsevier B.V. All rights reserved.
1. Introduction A power management system (PMS) is a supervisory control and data acquisition (SCADA) that implements a set of specific functions necessary for controlling an industrial power system, or in more general terms, any electrical system that contains both loads and generators. A typical industrial power system is composed by one or more connections to the national grid at high or medium voltage, one or more step-down transformers, a distribution network at medium and low voltage, and one or more generators both from conventional sources (gas or steam turbines) and from renewable sources (mainly photovoltaic). In some cases, a battery storage system may be present. If the installed power of the power system is below few MWs and its size within few kilometers, it is sometime called a microgrid.
∗ Corresponding author. Tel.: +39 010 353 2205; fax: +39 010 353 2700. E-mail address: [email protected] (P. Pinceti). http://dx.doi.org/10.1016/j.epsr.2015.01.010 0378-7796/© 2015 Elsevier B.V. All rights reserved.
The power management system of a microgrid has several goals that include the safety of the plants, the service continuity, the optimization of the power flows, the fulfillment of the contract with the TSO, etc. These goals are achieved with the implementation of different specific functions, such as: • Control and regulation: these are the functions that allow obtaining the desired power exchange when the system is connected with the grid, stabilizing the system when it runs islanded, controlling the re-synchronization of the system with the grid (to switch from islanded mode to parallel mode), etc. While performing these functions, the PMS must also optimize the energy efficiency, maximize the production from renewable sources and minimize the conventional generators wear; • Emergency management: the PMS shall actuate the countermeasures against events that may jeopardize the system integrity. The emergency functions are intended to preserve the system stability and to guarantee the power supply to loads that are vital for
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Fig. 2. PMS main functions related with the possible microgrid configurations. Fig. 1. Operating modes of a microgrid.
the personnel safety and the plant integrity. If intelligent protections are used, the PMS may update their setting to the current conditions of the plant. Other functions exist dedicated to services that are typical of a generic SCADA, such as: • Supervision: through an HMI for real-time monitoring of the system and for storing the relevant data for off-line analysis (historian); • Alarms management: for collecting and presenting the alarms from the plant to the operator(s); • Back-up management: for increasing the availability of the PMS and for facing failures and abnormal operating modes.
These subsystems are functionally and geographically separated and are hierarchically organized following a top-down logic (from the power plants to the loads). The TSO coordinates and supervises the different subsystems for stabilizing the entire system. Today the different stakeholders of a power system can freely associate to form a “smart grid” where generation and load distributed across the entire network are integrated together. Microgrids optimize the power exchange within the main grid and, in many cases, can run separated from the main grid (islanded mode). The expected benefits of microgrids are: 1. 2. 3. 4.
increase of the availability of the electrical supply, improvement of the power quality, reduction of pollutant emissions, energy cost reduction.
By means of all these functions the PMS can supervise and control the power system in all its operating modes shown in Fig. 1. In case of failures, the microgrid may switch from its normal operating mode (in parallel with the grid) [1,2] into an emergency mode (in parallel with some violation of operating limits for one or more equipment) or into islanded mode (not connected to the grid) [3]. The operator may intentionally command the transition into islanded mode. The synchronization with the national grid leads the islanded microgrid back to parallel mode. To achieve satisfactory operation, the PMS must identify the current operating mode of the microgrid, and it must actuate the specific control logic for each mode. The relevant parameters of the microgrid must be acquired (typically frequency, voltage, and active/reactive power flows), and the proper logic activated to obtain the required goals that are different according to the operating mode. Basically:
Often, the various targets do not converge; reducing the energy cost may reduce the availability of the system, or improving the power quality may increase the machinery wear, and so on. According to the current operating mode, the PMS shall find the best compromise between these targets [4]. When the microgrid is in parallel with the grid, the control is focused mainly on maximizing the renewable source [5,6] to reduce the energy cost, while in case the microgrid is islanded the control is focused mainly toward the system stabilization. The transitions between these two steady states may require emergency actions, that is load or generator shedding. The PMS runs different functions for each of the four operating conditions of the microgrid, as shown in Fig. 2 and detailed in Section 4.
• in parallel mode: the target is the power exchange control, the reactive power balance, the maximization of the renewable sources; • in islanded mode: the target is regulating the island frequency and voltage.
3.1. Software architecture
Starting from the circuit breakers position, the PMS determines how the bus bars are aggregated and which generators and loads are connected to the same cluster. 2. Target of the PMS A large-scale electrical power system is conventionally divided into homogeneous subsystems according to their main function: producers, transmission and distribution networks and consumers.
3. PMS architecture
The control logics summarized in Fig. 2 are the “core” of PMS system. To run properly, this core needs other ancillary functions to manage the input data, to support control logics decisions, and to increase the reliability of the system. The supporting functions for control logics are: • Configuration detection: this function identifies the current microgrid configuration and activates the proper control logic (involving only the elements that constitute the microgrid); • Protection management: this function evaluates the short circuit current for the current configuration of the microgrid and optimizes the tripping thresholds of the relays (intelligent electronic device are requested).
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• Redundancy and back-up: in case anomalies in the input data are detected these functions determine a reasonable value of analogue measures necessary to the PMS. If a data restoration is not possible, some functions of the PMS are stopped. As shown in Fig. 3, an integrated HMI and a supervisory system complete the architecture of the software. These two tools are necessary for setting-up the PMS and for the operator to supervise the entire electrical system of the Microgrid. The supervisory system is also equipped with additional tools for medium-long time analysis on power flows. All the data and commands from/to the PMS and the field flow through a fieldbus communication system. 3.2. Hardware architecture The PMS functions have been tested in the Smart MicroGrid realized at the NIDEC-ASI facility in Montebello Vicentino (VI-Italy). Fig. 5 shows the structure of the facility that includes:
Fig. 3. PMS software architecture.
• • • • • • •
a conventional diesel generator (20 kW) a variable load (24 kVA) a PV plant (50 kWp) a three steps sheddable loads (15 kVA each one) a simulator of a wind generator(15 kWp) an energy storage system (BESS) [7] (23 kW 38 Ah) the interconnection with the grid
The functions for data management and reliability are: • Renewable max. capability: this function calculates the maximum power production of renewable sources at the current weather conditions. The model of the plant cross-correlates the historic weather data with the produced power, and it is customized for each generating plant; • Data validation: this function validates the input data by correlating different measures and statuses (e.g. sum of generators/loads currents, coherence between analog and digital data, etc.);
The PMS is based on a virtual machine running the VMware® package for virtualization in two nodes, with a high availability configuration. The PMS is interfaced with the power equipment via a fieldbus connection (mostly Modbus TCP). Each node of the microgrid is equipped with a digital meter that sends to the PMS the measures of all the electrical parameters. Fig. 4 shows the generals screen of the PMS that displays the configuration of the micro-grid and the most relevant data for assessing
Fig. 4. Screen shot of the summary display of the PMS.
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Fig. 5. Layout of the test-bed and PMS.
the quality of operation. Each device is controlled into details with a dedicated display screen that can be accessed with a double-click from the summary screen. 4. Control algorithms As explained above, the configuration detection function activates the control logic suitable for the current configuration of the microgrid. The core control logic is split into four sub-sets that match the microgrid operating modes: - Operating statuses: grid connected, islanded, - Transition statuses: emergency and synchronization. When the microgrid is connected to the national grid the basic goal of the PMS is the tie line control (Fig. 6 shows the design criteria and the detailed algorithm). This function calculates the total amount of active e reactive power that the generators running inside the microgrid must produce to obtain the desired value of exchanged active and reactive power in the point(s) of common coupling with the national grid. The tie line control schedules the power exchange according to the contract between the microgrid and the TSO. The PMS calculates the required total production with the mix of generators that are currently active in the microgrid. Since the microgrid is paralleled with the grid, there is no need of voltage/frequency stabilization, and the source selection is based on economic and environmental criteria. In this condition the PMS tries to set the renewable sources in maximum power point tracking mode (MPPT), so minimizing the production from the conventional sources. At the same time, conventional generators have a lower threshold of power that can be produced continuously, so the PMS may decide to reduce the production from renewable sources to fulfill these limits. The amount of power produced by the conventional sources can be split in equal parts between all the active generators (proportionally to
their rated power) or saturating the sources step by step following a predefined ranking. The first approach (“Equal Load Sharing”) maximizes the life cycle of the conventional generators, while the second approach (“Ranked Load Sharing”) may reduce the energy cost if the most efficient sources are privileged. The user may choose between these two strategies through the HMI. Further possibilities of regulation are possible if a energy storage system is available. In the considered configuration, the electrical connection between the microgrid and the national grid avoids all the problems related with the stability of the system. The connection with the national grid guarantees the power balance of the microgrid and stabilizes the frequency and the voltage. If this connection is lost, the microgrid becomes islanded, and only the generators running inside the microgrid can satisfy the load demand. Large variations of frequency and voltage are possible. In an islanded network the speed governors regulate the generators output according to the system frequency (droop control), and the exciters control the voltage. This is the so-called “primary regulation”, and it is effective only until the power demand remains within the capability of the generators [8,9]. During the transition from “Grid Connected” to “Islanded” (that is in “Emergency” condition) the PMS must actuate the interventions necessary to respect this constrain (see Fig. 7). The “Emergency” functions work as follow: • all the events (mainly circuit breaker opening) that switch the microgrid into islanded condition are identified and monitored cyclically; • a “virtual” power balance of the islanded system originated by each considered event is performed at every cycle; • the results of this power balance are used to define all the actions necessary if any critical event occurs; • if a critical event is detected, the pre-defined actions related to this event are instantaneously actuated.
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Fig. 6. Functions for active power in “grid connected” condition.
The emergency actions planned by the PMS include the modulation of the storage system output and, if necessary, a load shedding (if the microgrid was importing power from the grid), or a generator shedding (if the microgrid was exporting power). These operations, together with the primary regulation of the conventional generators, guarantee that the system is able to overcome the emergency and to reach the stable condition of “Islanded Microgrid”. A similar event-based load shedding is actuated in Islanded condition if one or more generators trip. The event-based shedding is much faster than the traditional frequency-based shedding, so reducing the perturbations on the system. A shedding system based on frequency thresholds is provided as backup in case of failure of the event-based shedding. When the microgrid is islanded the target of the PMS is to achieve stable operation with adequate margins of regulating capacity and with an acceptable power quality. After these conditions are reached, the PMS tries to increase the energy efficiency and to reduce energy costs. Fig. 8 shows the design criteria and the detailed algorithms for system stabilization and secondary frequency regulation. Renewable sources may represent a heavy disturbance to the stable operation of the microgrid, since their production depends
on the weather conditions and it is partially not controllable. If the weather conditions change the power generated from renewable sources changes, and this may unbalance the system. In this case the blackout can be avoided only if the conventional generators or the energy storage system are able to compensate the variation in renewable sources. The PMS limits the power output of renewable sources to a value smaller than the spinning reserve instantaneously available from the active conventional generators plus the possible stored power (if available). The operator can set via HMI the level of coverage of the power variations of the renewable sources according to the current weather conditions. In special operating conditions (e.g. no emergency loads are present), the operator may decide to set the renewable sources into MPPT mode even without back-up power. In every condition, the PMS limits the renewable sources power output if the conventional generators produce less than the 110% of their minimum load. The functions “Load Sharing” and “Ranked Load Sharing” run also in “Islanded Microgrid” mode. The primary regulation (droop control) introduces a frequency error if the generator set points and the load demand are not equal. To maintain frequency and voltage to the desired values, the PMS operates a secondary regulation that involves conventional
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terms of speed and direction). This means that the decision is based on the current condition of the system (deviation) and on a forecast on the condition of the system in the next future. For example, if the deviation is significant but it is getting smaller, no actions are requested. This approach minimizes the number of operations performed on the speed governors and the exciters of conventional generators (increasing their expected life). The most important phases of this decisional process are: • the identification of the control variables, • their “fuzzification”, • the definition of a “fuzzy rule tables”. To “fuzzificate” a variable means to divide its range of variation in a number of steps (usually five) and then to associate its current value to each of them with a weight factor. To define a “fuzzy rule tables” means to identify a predefined action for each combination of fuzzificated values of the considered variable. For example, for frequency control the considered variables are the deviation of the system frequency from the rated value and its rate of change. The results of this process are the power set points to all the generators running in the microgrid, as shown in Fig. 9. 6. Validation of control logics Fig. 7. Functions for “Emergency” condition.
generators and the energy storage system. PMS acquires the real-time values of frequency and voltage, and modifies the set points to generators and to the storage system for compensating the possible deviations from the desired values. To minimize the stress for the generators, a fuzzy logic approach (see Section 5) is preferred to a more common proportional-integral control (PI). The “Synchro” mode is only a temporary case of “Islanded Microgrid” mode: in this mode the set points of the secondary regulation are the current frequency and voltage of the national grid. The Energy Storage System reacts to rapid voltage and/or frequency variations with the goal of stabilizing the system and minimizing the control actions requested to renewable and conventional generators. 5. Fuzzy logics for island regulations The acceptable variations of voltage and frequency in islanded power systems are larger than typical variation in interconnected grids. The standard EN 50160 states that the expected variations in islanded systems are: • Frequency: (a) ±2% of rated value for 95% of the time; (b) ±15% of rated value for 100% of the time • Voltage: +10%/−15% of the rated value. Limited voltage and frequency errors are acceptable in an isolated network, and this fact leads to more relaxed constraints. For this reason, we decided to use a fuzzy controller for voltage and frequency regulation during islanded operation [10,11]. The main advantages of this approach are: • reducing the stress of the prime movers of generators, • increasing the stability and the reliability (as a consequence of the lower stress). The controller identifies the kind and the amount of the corrections requested by the system considering the deviation of the controlled variable from the desired value and its changing rate (in
6.1. Simulator development The PMS software was implemented on a programmable logic controller (PLC), and a dynamic simulator was implemented to carry-out the following activities: • • • •
debugging of software routines, validation of the control logics, verification of I/O, testing of PMS performances.
According to the suggestion of IEC 62603-1, the simulator receives the set points calculated by the PMS, and it generates realistic feedbacks in terms of power, voltage, and frequency of the microgrid. The simulator is implemented in Simulink environment, and it calculates the real-time parameters that affect and are affected by the PMS, i.e.: • the active or reactive power flows in the microgrid, • the dynamic response of rotating generators considering the electromechanical time constants, • the response of speed governors and exciters of the rotating generators, • the frequency and voltage dynamic in islanded condition. The scope of the simulator is to obtain realistic real-time feedback, so a simplified model of the microgrid is implemented. A so-called “decoupled” model is implemented, where the active power balance influences the system frequency, and the reactive power balance influences the system voltage [12,13]. The following equations explain these relationships:
PGi +
PLi = 2 × H ×
df dt
(1)
where PGi is the active power generator “i”, PLi is the active power load “i”, H is the inertia of all the rotating machines (generators or motors not equipped with drives) running on the microgrid and f is the frequency of islanded microgrid.
QGi +
QLi = Asc ×
dV dt
(2)
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Fig. 8. Functions for active power control in “Islanded Microgrid” condition.
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Fig. 9. Fuzzy logic.
where QGi is the reactive power generator “i”, QLi is the r reactive power load “i”, Asc is the r short circuit power of the microgrid and V is the r voltage of islanded microgrid. The time frame of the actions of the PMS is of several minutes, with a resolution of about 100 ms. Therefore, the fast electrical transient are neglected, and only the electromechanical parameters of rotating generators are considered. A reduced model with fast calculation time is necessary to guarantee the real-time response of the simulator. The simulator runs on a personal computer (PC) together with its own HMI, while the PMS runs on a PLC. An OPC platform (OLE for Process Control) connects these two systems as Fig. 10 shows
and allows a standardized real-time data exchange. The simulator calculates all the variables of the microgrid under test, and stores them on the OPC server. The variables that are exchanged between the simulator and the PMS can be divided into two groups:
- control signals: (opening commands to circuit breakers and setpoints to the machines) generated by the PMS, - the operational variables describing the current status of the microgrid (circuit breakers status, active and reactive power, frequency, voltage, etc.) calculated by the simulator.
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server. The PMS reads the new status of the microgrid and actuates the control actions (if required) modifying the control signals on the OPC server. This procedure continues for the whole simulation time. The test manager can create events (e.g. circuit breaker opening or load variations) and supervise the behavior of the entire system through the HMI. 6.2. Test results
Fig. 10. Architecture of simulation system.
At each cycle the simulator reads the control signals and the current status of the microgrid from the OPC server and calculates the operational variables of the microgrid in the next cycle. The output of the simulation updates the status of the system on the OPC
The simulated system replicates the NIDEC-ASI Smart MicroGrid (see Section 3.2) with an additional conventional generator (added to verify the generator shedding logics). The performed tests are oriented to validate the PMS control logic and to evaluate its performances. The plan of the tests with the related tested functions is summarized in Table 1 that shows the studied configuration for each test. For example, Test 1 verifies the load-sharing function when the microgrid is in parallel with the grid, Test 2 verifies the functions of secondary control and of generator shedding when the microgrid switches from parallel to islanded, and so on. All
Fig. 11. Gen. shedding and load sharing with renewable maximization (Test 2).
Fig. 12. Primary and secondary frequency regulation during (Test 2).
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Fig. 13. Perturbed load and gen.shedding for tech.min after time out of 8 s (Test 4).
Fig. 14. Double load shedding due to islanding and generator lost (Test 5).
the PMS functions have been verified by the simulated tests. Figures from 11 to 15 show some examples of simulations results. Fig. 11 shows the result of Test no. 2; the microgrid is in parallel with the grid, and it is exporting a large amount of power. Table 1 Test plan: configuration and functions. PMS function
Microgrid status
Load sharing Tie line control Generator shedding Load shedding Sec. frequency control Sec. voltage control Load sharing Conventional backup Generator shedding Load shedding
In parallel In parallel From grid to island From grid to island Islanded Islanded Islanded Islanded Islanded Islanded + gen.lost
Test 1
2
3
4
5
× ×
× × ×
× ×
× ×
× ×
× × × ×
× × ×
× × × ×
× × ×
× ×
6
× × × ×
Around time 55 the tie-line opens, and the PMS trips the conventional generator G2 and set the storage system into “charge mode” for reducing the power unbalance. Renewable generators (# 1–2–3 that are identical, so only one line is displayed) almost instantaneously reduce their production, while the conventional generator G1 is slower in reacting. After few seconds, the PMS starts the “loadsharing function” to set the production from renewable sources to the maximum available power, and the “secondary frequency control function” for setting the island frequency to 50 Hz. Fig. 12 shows the result of secondary frequency control. Fig. 13 shows the results of Test no. 3; the microgrid is in parallel with the grid with a nil power exchange. The tie-line opens around time 208 s and a load is opened at the same time (to simulate a short-circuit on the load with a poor selectivity of the protections). From t = 210 s to t = 230 s other loads open, so the production of the conventional generators decreases toward the minimum acceptable value. The PMS set the battery in charge mode to keep the load demand as high as possible. When the minimum value of power for the conventional generators is reached (around time 230 s), the PMS sends an alarm to the operator and after a fixed time (in the
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Fig. 15. Test 5 frequency response (a) and details of OPC write/read cycles (b).
simulation equal to 5 s) opens conventional generator 2 and set the battery to demand to zero. When the system stabilizes, the PMS starts the load-sharing function to maximize the production from renewable sources with the conventional generator above its minimum production. Figs. 14 and 15 show the results for Test no. 4; the simulated sequence of events starts from the microgrid in parallel mode and the opening of the tie-line breaker. The microgrid imports a large amount of power, so when the tie-line opens the PMS activates a load-shedding action (around t = 57 s). Simultaneously, the PMS sets the battery storage into “generation mode”. At time 77 s the renewable generator no. 3 trips out, so the PMS activates a further step of load-shedding. Fig. 15a shows the frequency of the microgrid during this transient. It is apparent that the load-shedding is not sufficient to maintain the frequency above 47.5 Hz that is the threshold of the under-frequency relay that trips the conventional generators. This behavior is caused by the hardware/software architecture of the simulator and it is not so large in reality. The interface between the real-time simulator and the PMS under test goes through the OPC server that introduces a time delay of about 200 ms. Fig. 15b shows the sequence of events starting from the opening of the tie-line breaker (t = 56.65 s) to the command emission of the PMS (t = 56.75) to the execution of the command (t = 56.95). In reality, the PMS sends the load-shedding command within 100 ms after the critical event detection, and the opening of the breaker should be almost contemporaneous. The delay from 56.75 s to 56.95 s is caused by the OPC client/server mechanism, and such a delay reduces the effectiveness of the load-shedding action. This type of phenomenon is not present in digital simulators, but
it may become of the utmost importance when a real-time simulator is interfaced with a real automation system to test its dynamic behavior. 7. Conclusion The paper describes the functions and the architecture of a power management system for industrial or tertiary microgrids with renewable sources. Stabilizing a microgrid, especially in islanded mode, requires a coordinated real-time control of the power generated by conventional generators and by renewable sources, with control targets that may push toward divergent solutions. For example, reducing the energy cost requires maximizing the production of renewable sources, but safety may require a higher production by conventional sources. The PMS must find a reasonable compromise between all these targets according to a rank of priorities defined by the operators. All the control functions have been implemented in a PLC-based system and have been tested with a software simulator that is described in the paper. Results show a satisfactory performance of the PMS both during normal operation (in parallel with the grid) and in islanded mode. The PMS also detects all the events that may cause the separation of the microgrid from the national grid and actuates the necessary emergency actions, e.g. load shedding or generator shedding. When the microgrid is isolated the PMS regulates its voltage and frequency by means of a fuzzy controller to minimize the stress for conventional generators and to maximize the microgrid availability. The PMS is now under test in a real microgrid.
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Electric Power Systems Research journal homepage: www.elsevier.com/locate/epsr
Design criteria for a power management system for microgrids with renewable sources P. Pinceti a,∗ , M. Vanti a , C. Brocca b , M. Carnesecchi b , G.P. Macera b a DITEN Department of Electrical, Electronic and Telecommunication Engineering and Naval Architecture of University of Genoa, via all’Opera Pia 11a, 16145 Genova, Italy b NIDEC-ASI SpA, Corso Perrone 11, 16152 Genova, Italy
a r t i c l e
i n f o
Article history: Received 24 March 2014 Received in revised form 5 December 2014 Accepted 13 January 2015 Keywords: Power management system Load-shedding Generator-shedding Microgrid Renewable Energy Fuzzy Logic
a b s t r a c t The paper describes the control functions that a power management system (PMS) needs for controlling a microgrid, with both conventional and renewable sources. According to the IEEE 1547.4, distributed resources island systems – or in brief “microgrids” – are active networks containing both loads and distributed generators, and may require a modification of their control logic if they are connected to a grid or not. A fast load or generator shedding actions may also be required to preserve system stability in case the microgrid switches from connected to islanded. Today, most industrial networks are designed to run also in islanded mode, while in public networks transmission system operators (TSO) generally do not allow islands. The presence of renewable sources that are partially not controllable requires the re-definition of the control logic compared with microgrids where only fully controllable generators are present. PMS of a microgrid has a double function: - to guarantee the stable operation of the system in presence of the unpredictable variations caused by renewable sources and loads, - to optimize the energy production of renewable and conventional sources. The logic described in the paper was implemented in a PMS that was tested with a software simulator prior to the installation in a real microgrid. The paper reports the results of tests. © 2015 Elsevier B.V. All rights reserved.
1. Introduction A power management system (PMS) is a supervisory control and data acquisition (SCADA) that implements a set of specific functions necessary for controlling an industrial power system, or in more general terms, any electrical system that contains both loads and generators. A typical industrial power system is composed by one or more connections to the national grid at high or medium voltage, one or more step-down transformers, a distribution network at medium and low voltage, and one or more generators both from conventional sources (gas or steam turbines) and from renewable sources (mainly photovoltaic). In some cases, a battery storage system may be present. If the installed power of the power system is below few MWs and its size within few kilometers, it is sometime called a microgrid.
∗ Corresponding author. Tel.: +39 010 353 2205; fax: +39 010 353 2700. E-mail address: [email protected] (P. Pinceti). http://dx.doi.org/10.1016/j.epsr.2015.01.010 0378-7796/© 2015 Elsevier B.V. All rights reserved.
The power management system of a microgrid has several goals that include the safety of the plants, the service continuity, the optimization of the power flows, the fulfillment of the contract with the TSO, etc. These goals are achieved with the implementation of different specific functions, such as: • Control and regulation: these are the functions that allow obtaining the desired power exchange when the system is connected with the grid, stabilizing the system when it runs islanded, controlling the re-synchronization of the system with the grid (to switch from islanded mode to parallel mode), etc. While performing these functions, the PMS must also optimize the energy efficiency, maximize the production from renewable sources and minimize the conventional generators wear; • Emergency management: the PMS shall actuate the countermeasures against events that may jeopardize the system integrity. The emergency functions are intended to preserve the system stability and to guarantee the power supply to loads that are vital for
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Fig. 2. PMS main functions related with the possible microgrid configurations. Fig. 1. Operating modes of a microgrid.
the personnel safety and the plant integrity. If intelligent protections are used, the PMS may update their setting to the current conditions of the plant. Other functions exist dedicated to services that are typical of a generic SCADA, such as: • Supervision: through an HMI for real-time monitoring of the system and for storing the relevant data for off-line analysis (historian); • Alarms management: for collecting and presenting the alarms from the plant to the operator(s); • Back-up management: for increasing the availability of the PMS and for facing failures and abnormal operating modes.
These subsystems are functionally and geographically separated and are hierarchically organized following a top-down logic (from the power plants to the loads). The TSO coordinates and supervises the different subsystems for stabilizing the entire system. Today the different stakeholders of a power system can freely associate to form a “smart grid” where generation and load distributed across the entire network are integrated together. Microgrids optimize the power exchange within the main grid and, in many cases, can run separated from the main grid (islanded mode). The expected benefits of microgrids are: 1. 2. 3. 4.
increase of the availability of the electrical supply, improvement of the power quality, reduction of pollutant emissions, energy cost reduction.
By means of all these functions the PMS can supervise and control the power system in all its operating modes shown in Fig. 1. In case of failures, the microgrid may switch from its normal operating mode (in parallel with the grid) [1,2] into an emergency mode (in parallel with some violation of operating limits for one or more equipment) or into islanded mode (not connected to the grid) [3]. The operator may intentionally command the transition into islanded mode. The synchronization with the national grid leads the islanded microgrid back to parallel mode. To achieve satisfactory operation, the PMS must identify the current operating mode of the microgrid, and it must actuate the specific control logic for each mode. The relevant parameters of the microgrid must be acquired (typically frequency, voltage, and active/reactive power flows), and the proper logic activated to obtain the required goals that are different according to the operating mode. Basically:
Often, the various targets do not converge; reducing the energy cost may reduce the availability of the system, or improving the power quality may increase the machinery wear, and so on. According to the current operating mode, the PMS shall find the best compromise between these targets [4]. When the microgrid is in parallel with the grid, the control is focused mainly on maximizing the renewable source [5,6] to reduce the energy cost, while in case the microgrid is islanded the control is focused mainly toward the system stabilization. The transitions between these two steady states may require emergency actions, that is load or generator shedding. The PMS runs different functions for each of the four operating conditions of the microgrid, as shown in Fig. 2 and detailed in Section 4.
• in parallel mode: the target is the power exchange control, the reactive power balance, the maximization of the renewable sources; • in islanded mode: the target is regulating the island frequency and voltage.
3.1. Software architecture
Starting from the circuit breakers position, the PMS determines how the bus bars are aggregated and which generators and loads are connected to the same cluster. 2. Target of the PMS A large-scale electrical power system is conventionally divided into homogeneous subsystems according to their main function: producers, transmission and distribution networks and consumers.
3. PMS architecture
The control logics summarized in Fig. 2 are the “core” of PMS system. To run properly, this core needs other ancillary functions to manage the input data, to support control logics decisions, and to increase the reliability of the system. The supporting functions for control logics are: • Configuration detection: this function identifies the current microgrid configuration and activates the proper control logic (involving only the elements that constitute the microgrid); • Protection management: this function evaluates the short circuit current for the current configuration of the microgrid and optimizes the tripping thresholds of the relays (intelligent electronic device are requested).
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• Redundancy and back-up: in case anomalies in the input data are detected these functions determine a reasonable value of analogue measures necessary to the PMS. If a data restoration is not possible, some functions of the PMS are stopped. As shown in Fig. 3, an integrated HMI and a supervisory system complete the architecture of the software. These two tools are necessary for setting-up the PMS and for the operator to supervise the entire electrical system of the Microgrid. The supervisory system is also equipped with additional tools for medium-long time analysis on power flows. All the data and commands from/to the PMS and the field flow through a fieldbus communication system. 3.2. Hardware architecture The PMS functions have been tested in the Smart MicroGrid realized at the NIDEC-ASI facility in Montebello Vicentino (VI-Italy). Fig. 5 shows the structure of the facility that includes:
Fig. 3. PMS software architecture.
• • • • • • •
a conventional diesel generator (20 kW) a variable load (24 kVA) a PV plant (50 kWp) a three steps sheddable loads (15 kVA each one) a simulator of a wind generator(15 kWp) an energy storage system (BESS) [7] (23 kW 38 Ah) the interconnection with the grid
The functions for data management and reliability are: • Renewable max. capability: this function calculates the maximum power production of renewable sources at the current weather conditions. The model of the plant cross-correlates the historic weather data with the produced power, and it is customized for each generating plant; • Data validation: this function validates the input data by correlating different measures and statuses (e.g. sum of generators/loads currents, coherence between analog and digital data, etc.);
The PMS is based on a virtual machine running the VMware® package for virtualization in two nodes, with a high availability configuration. The PMS is interfaced with the power equipment via a fieldbus connection (mostly Modbus TCP). Each node of the microgrid is equipped with a digital meter that sends to the PMS the measures of all the electrical parameters. Fig. 4 shows the generals screen of the PMS that displays the configuration of the micro-grid and the most relevant data for assessing
Fig. 4. Screen shot of the summary display of the PMS.
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Fig. 5. Layout of the test-bed and PMS.
the quality of operation. Each device is controlled into details with a dedicated display screen that can be accessed with a double-click from the summary screen. 4. Control algorithms As explained above, the configuration detection function activates the control logic suitable for the current configuration of the microgrid. The core control logic is split into four sub-sets that match the microgrid operating modes: - Operating statuses: grid connected, islanded, - Transition statuses: emergency and synchronization. When the microgrid is connected to the national grid the basic goal of the PMS is the tie line control (Fig. 6 shows the design criteria and the detailed algorithm). This function calculates the total amount of active e reactive power that the generators running inside the microgrid must produce to obtain the desired value of exchanged active and reactive power in the point(s) of common coupling with the national grid. The tie line control schedules the power exchange according to the contract between the microgrid and the TSO. The PMS calculates the required total production with the mix of generators that are currently active in the microgrid. Since the microgrid is paralleled with the grid, there is no need of voltage/frequency stabilization, and the source selection is based on economic and environmental criteria. In this condition the PMS tries to set the renewable sources in maximum power point tracking mode (MPPT), so minimizing the production from the conventional sources. At the same time, conventional generators have a lower threshold of power that can be produced continuously, so the PMS may decide to reduce the production from renewable sources to fulfill these limits. The amount of power produced by the conventional sources can be split in equal parts between all the active generators (proportionally to
their rated power) or saturating the sources step by step following a predefined ranking. The first approach (“Equal Load Sharing”) maximizes the life cycle of the conventional generators, while the second approach (“Ranked Load Sharing”) may reduce the energy cost if the most efficient sources are privileged. The user may choose between these two strategies through the HMI. Further possibilities of regulation are possible if a energy storage system is available. In the considered configuration, the electrical connection between the microgrid and the national grid avoids all the problems related with the stability of the system. The connection with the national grid guarantees the power balance of the microgrid and stabilizes the frequency and the voltage. If this connection is lost, the microgrid becomes islanded, and only the generators running inside the microgrid can satisfy the load demand. Large variations of frequency and voltage are possible. In an islanded network the speed governors regulate the generators output according to the system frequency (droop control), and the exciters control the voltage. This is the so-called “primary regulation”, and it is effective only until the power demand remains within the capability of the generators [8,9]. During the transition from “Grid Connected” to “Islanded” (that is in “Emergency” condition) the PMS must actuate the interventions necessary to respect this constrain (see Fig. 7). The “Emergency” functions work as follow: • all the events (mainly circuit breaker opening) that switch the microgrid into islanded condition are identified and monitored cyclically; • a “virtual” power balance of the islanded system originated by each considered event is performed at every cycle; • the results of this power balance are used to define all the actions necessary if any critical event occurs; • if a critical event is detected, the pre-defined actions related to this event are instantaneously actuated.
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Fig. 6. Functions for active power in “grid connected” condition.
The emergency actions planned by the PMS include the modulation of the storage system output and, if necessary, a load shedding (if the microgrid was importing power from the grid), or a generator shedding (if the microgrid was exporting power). These operations, together with the primary regulation of the conventional generators, guarantee that the system is able to overcome the emergency and to reach the stable condition of “Islanded Microgrid”. A similar event-based load shedding is actuated in Islanded condition if one or more generators trip. The event-based shedding is much faster than the traditional frequency-based shedding, so reducing the perturbations on the system. A shedding system based on frequency thresholds is provided as backup in case of failure of the event-based shedding. When the microgrid is islanded the target of the PMS is to achieve stable operation with adequate margins of regulating capacity and with an acceptable power quality. After these conditions are reached, the PMS tries to increase the energy efficiency and to reduce energy costs. Fig. 8 shows the design criteria and the detailed algorithms for system stabilization and secondary frequency regulation. Renewable sources may represent a heavy disturbance to the stable operation of the microgrid, since their production depends
on the weather conditions and it is partially not controllable. If the weather conditions change the power generated from renewable sources changes, and this may unbalance the system. In this case the blackout can be avoided only if the conventional generators or the energy storage system are able to compensate the variation in renewable sources. The PMS limits the power output of renewable sources to a value smaller than the spinning reserve instantaneously available from the active conventional generators plus the possible stored power (if available). The operator can set via HMI the level of coverage of the power variations of the renewable sources according to the current weather conditions. In special operating conditions (e.g. no emergency loads are present), the operator may decide to set the renewable sources into MPPT mode even without back-up power. In every condition, the PMS limits the renewable sources power output if the conventional generators produce less than the 110% of their minimum load. The functions “Load Sharing” and “Ranked Load Sharing” run also in “Islanded Microgrid” mode. The primary regulation (droop control) introduces a frequency error if the generator set points and the load demand are not equal. To maintain frequency and voltage to the desired values, the PMS operates a secondary regulation that involves conventional
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terms of speed and direction). This means that the decision is based on the current condition of the system (deviation) and on a forecast on the condition of the system in the next future. For example, if the deviation is significant but it is getting smaller, no actions are requested. This approach minimizes the number of operations performed on the speed governors and the exciters of conventional generators (increasing their expected life). The most important phases of this decisional process are: • the identification of the control variables, • their “fuzzification”, • the definition of a “fuzzy rule tables”. To “fuzzificate” a variable means to divide its range of variation in a number of steps (usually five) and then to associate its current value to each of them with a weight factor. To define a “fuzzy rule tables” means to identify a predefined action for each combination of fuzzificated values of the considered variable. For example, for frequency control the considered variables are the deviation of the system frequency from the rated value and its rate of change. The results of this process are the power set points to all the generators running in the microgrid, as shown in Fig. 9. 6. Validation of control logics Fig. 7. Functions for “Emergency” condition.
generators and the energy storage system. PMS acquires the real-time values of frequency and voltage, and modifies the set points to generators and to the storage system for compensating the possible deviations from the desired values. To minimize the stress for the generators, a fuzzy logic approach (see Section 5) is preferred to a more common proportional-integral control (PI). The “Synchro” mode is only a temporary case of “Islanded Microgrid” mode: in this mode the set points of the secondary regulation are the current frequency and voltage of the national grid. The Energy Storage System reacts to rapid voltage and/or frequency variations with the goal of stabilizing the system and minimizing the control actions requested to renewable and conventional generators. 5. Fuzzy logics for island regulations The acceptable variations of voltage and frequency in islanded power systems are larger than typical variation in interconnected grids. The standard EN 50160 states that the expected variations in islanded systems are: • Frequency: (a) ±2% of rated value for 95% of the time; (b) ±15% of rated value for 100% of the time • Voltage: +10%/−15% of the rated value. Limited voltage and frequency errors are acceptable in an isolated network, and this fact leads to more relaxed constraints. For this reason, we decided to use a fuzzy controller for voltage and frequency regulation during islanded operation [10,11]. The main advantages of this approach are: • reducing the stress of the prime movers of generators, • increasing the stability and the reliability (as a consequence of the lower stress). The controller identifies the kind and the amount of the corrections requested by the system considering the deviation of the controlled variable from the desired value and its changing rate (in
6.1. Simulator development The PMS software was implemented on a programmable logic controller (PLC), and a dynamic simulator was implemented to carry-out the following activities: • • • •
debugging of software routines, validation of the control logics, verification of I/O, testing of PMS performances.
According to the suggestion of IEC 62603-1, the simulator receives the set points calculated by the PMS, and it generates realistic feedbacks in terms of power, voltage, and frequency of the microgrid. The simulator is implemented in Simulink environment, and it calculates the real-time parameters that affect and are affected by the PMS, i.e.: • the active or reactive power flows in the microgrid, • the dynamic response of rotating generators considering the electromechanical time constants, • the response of speed governors and exciters of the rotating generators, • the frequency and voltage dynamic in islanded condition. The scope of the simulator is to obtain realistic real-time feedback, so a simplified model of the microgrid is implemented. A so-called “decoupled” model is implemented, where the active power balance influences the system frequency, and the reactive power balance influences the system voltage [12,13]. The following equations explain these relationships:
PGi +
PLi = 2 × H ×
df dt
(1)
where PGi is the active power generator “i”, PLi is the active power load “i”, H is the inertia of all the rotating machines (generators or motors not equipped with drives) running on the microgrid and f is the frequency of islanded microgrid.
QGi +
QLi = Asc ×
dV dt
(2)
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Fig. 8. Functions for active power control in “Islanded Microgrid” condition.
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Fig. 9. Fuzzy logic.
where QGi is the reactive power generator “i”, QLi is the r reactive power load “i”, Asc is the r short circuit power of the microgrid and V is the r voltage of islanded microgrid. The time frame of the actions of the PMS is of several minutes, with a resolution of about 100 ms. Therefore, the fast electrical transient are neglected, and only the electromechanical parameters of rotating generators are considered. A reduced model with fast calculation time is necessary to guarantee the real-time response of the simulator. The simulator runs on a personal computer (PC) together with its own HMI, while the PMS runs on a PLC. An OPC platform (OLE for Process Control) connects these two systems as Fig. 10 shows
and allows a standardized real-time data exchange. The simulator calculates all the variables of the microgrid under test, and stores them on the OPC server. The variables that are exchanged between the simulator and the PMS can be divided into two groups:
- control signals: (opening commands to circuit breakers and setpoints to the machines) generated by the PMS, - the operational variables describing the current status of the microgrid (circuit breakers status, active and reactive power, frequency, voltage, etc.) calculated by the simulator.
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server. The PMS reads the new status of the microgrid and actuates the control actions (if required) modifying the control signals on the OPC server. This procedure continues for the whole simulation time. The test manager can create events (e.g. circuit breaker opening or load variations) and supervise the behavior of the entire system through the HMI. 6.2. Test results
Fig. 10. Architecture of simulation system.
At each cycle the simulator reads the control signals and the current status of the microgrid from the OPC server and calculates the operational variables of the microgrid in the next cycle. The output of the simulation updates the status of the system on the OPC
The simulated system replicates the NIDEC-ASI Smart MicroGrid (see Section 3.2) with an additional conventional generator (added to verify the generator shedding logics). The performed tests are oriented to validate the PMS control logic and to evaluate its performances. The plan of the tests with the related tested functions is summarized in Table 1 that shows the studied configuration for each test. For example, Test 1 verifies the load-sharing function when the microgrid is in parallel with the grid, Test 2 verifies the functions of secondary control and of generator shedding when the microgrid switches from parallel to islanded, and so on. All
Fig. 11. Gen. shedding and load sharing with renewable maximization (Test 2).
Fig. 12. Primary and secondary frequency regulation during (Test 2).
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Fig. 13. Perturbed load and gen.shedding for tech.min after time out of 8 s (Test 4).
Fig. 14. Double load shedding due to islanding and generator lost (Test 5).
the PMS functions have been verified by the simulated tests. Figures from 11 to 15 show some examples of simulations results. Fig. 11 shows the result of Test no. 2; the microgrid is in parallel with the grid, and it is exporting a large amount of power. Table 1 Test plan: configuration and functions. PMS function
Microgrid status
Load sharing Tie line control Generator shedding Load shedding Sec. frequency control Sec. voltage control Load sharing Conventional backup Generator shedding Load shedding
In parallel In parallel From grid to island From grid to island Islanded Islanded Islanded Islanded Islanded Islanded + gen.lost
Test 1
2
3
4
5
× ×
× × ×
× ×
× ×
× ×
× × × ×
× × ×
× × × ×
× × ×
× ×
6
× × × ×
Around time 55 the tie-line opens, and the PMS trips the conventional generator G2 and set the storage system into “charge mode” for reducing the power unbalance. Renewable generators (# 1–2–3 that are identical, so only one line is displayed) almost instantaneously reduce their production, while the conventional generator G1 is slower in reacting. After few seconds, the PMS starts the “loadsharing function” to set the production from renewable sources to the maximum available power, and the “secondary frequency control function” for setting the island frequency to 50 Hz. Fig. 12 shows the result of secondary frequency control. Fig. 13 shows the results of Test no. 3; the microgrid is in parallel with the grid with a nil power exchange. The tie-line opens around time 208 s and a load is opened at the same time (to simulate a short-circuit on the load with a poor selectivity of the protections). From t = 210 s to t = 230 s other loads open, so the production of the conventional generators decreases toward the minimum acceptable value. The PMS set the battery in charge mode to keep the load demand as high as possible. When the minimum value of power for the conventional generators is reached (around time 230 s), the PMS sends an alarm to the operator and after a fixed time (in the
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Fig. 15. Test 5 frequency response (a) and details of OPC write/read cycles (b).
simulation equal to 5 s) opens conventional generator 2 and set the battery to demand to zero. When the system stabilizes, the PMS starts the load-sharing function to maximize the production from renewable sources with the conventional generator above its minimum production. Figs. 14 and 15 show the results for Test no. 4; the simulated sequence of events starts from the microgrid in parallel mode and the opening of the tie-line breaker. The microgrid imports a large amount of power, so when the tie-line opens the PMS activates a load-shedding action (around t = 57 s). Simultaneously, the PMS sets the battery storage into “generation mode”. At time 77 s the renewable generator no. 3 trips out, so the PMS activates a further step of load-shedding. Fig. 15a shows the frequency of the microgrid during this transient. It is apparent that the load-shedding is not sufficient to maintain the frequency above 47.5 Hz that is the threshold of the under-frequency relay that trips the conventional generators. This behavior is caused by the hardware/software architecture of the simulator and it is not so large in reality. The interface between the real-time simulator and the PMS under test goes through the OPC server that introduces a time delay of about 200 ms. Fig. 15b shows the sequence of events starting from the opening of the tie-line breaker (t = 56.65 s) to the command emission of the PMS (t = 56.75) to the execution of the command (t = 56.95). In reality, the PMS sends the load-shedding command within 100 ms after the critical event detection, and the opening of the breaker should be almost contemporaneous. The delay from 56.75 s to 56.95 s is caused by the OPC client/server mechanism, and such a delay reduces the effectiveness of the load-shedding action. This type of phenomenon is not present in digital simulators, but
it may become of the utmost importance when a real-time simulator is interfaced with a real automation system to test its dynamic behavior. 7. Conclusion The paper describes the functions and the architecture of a power management system for industrial or tertiary microgrids with renewable sources. Stabilizing a microgrid, especially in islanded mode, requires a coordinated real-time control of the power generated by conventional generators and by renewable sources, with control targets that may push toward divergent solutions. For example, reducing the energy cost requires maximizing the production of renewable sources, but safety may require a higher production by conventional sources. The PMS must find a reasonable compromise between all these targets according to a rank of priorities defined by the operators. All the control functions have been implemented in a PLC-based system and have been tested with a software simulator that is described in the paper. Results show a satisfactory performance of the PMS both during normal operation (in parallel with the grid) and in islanded mode. The PMS also detects all the events that may cause the separation of the microgrid from the national grid and actuates the necessary emergency actions, e.g. load shedding or generator shedding. When the microgrid is isolated the PMS regulates its voltage and frequency by means of a fuzzy controller to minimize the stress for conventional generators and to maximize the microgrid availability. The PMS is now under test in a real microgrid.
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