1. Introduction
Due to the increasing concern over the greenhouse effect and the possible harmful impact of fossil-fuel-based power generation on human health, the European Union (EU) seeks a common long-term energy strategy to decarbonize the power sector [
1]. Renewable energy sources, including photovoltaic (PV) systems, are key technologies in the pursuit of carbon-free electricity production [
2]. Currently, fossil-fuel-based units can offer electricity on the market at a generally lower production cost as compared to solar PV and wind [
3]. However, they are the source of emissions and their generation costs are expected to increase as the emission allowance costs will rise due to the implementation, into the EU Emission Trading Scheme (EU ETS) [
4], of a mechanism of Market Stability Reserve [
5], which is a tool for achieving long-term decarbonization, as declared in the EU Energy Roadmap 2050. The intermittency of renewable energy generators based on solar and wind energy resources is challenging for effective power system control [
6], while their share in the electricity mix is expected to steadily increase over the next decades [
7]. To limit the impact of their variability in power generation on the power system, energy storage systems (ESS) are installed to create hybrid PV-ESS systems [
8]. Battery energy storage (BES) systems (BESS) are currently developing rapidly and are perceived as a promising solution in power sector [
9]. The major barrier for their wide implementation is high BESS cost [
10]. Further endeavors to foster the use of variable renewable energy sources (RES) and subsequent development of electric vehicles (EVs) should be the main drivers for BESS technology development, although EVs may be a strong competition for the stationary application of batteries in the power sector, so their specific cost may decrease at a lower rate than desired and the second use of depleted batteries from EVs may become an option for power generators [
11].
Renewable energy sources can benefit from feed-in-tariffs. However, promotion mechanisms often have limited time horizon, e.g. 15 years in Poland [
12], and some of the renewable installations may not win auctions to get a preferential price and still decide to participate in the electricity market. To be an effective participant of the day-ahead market (DAM), the renewable source owner must be able to predict their hourly generation profile for the next day. Therefore, many intermittent renewable energy generators of different production profiles join their forces to form a balancing group offering a common scheduling unit (CSU). Still, the PV generator position within the balancing group can be strengthened as they decide to install battery energy storage to build hybrid PV-BES systems. The alternative for them would be to operate without BESS and incur the cost of electricity balancing in any case of failure in delivering committed electricity amounts. This is expected to be costly, as the inability to meet hourly commitments can occur frequently e.g. due to incorrect and imprecise weather forecasts. Having the above in mind, the authors raise the question of whether the operation of hybrid PV-BES system within the balancing group to offer electricity within common scheduling unit for the day ahead electricity market is viable from the technical and economic point of view and how to size BESS for that purpose.
The major difficulty in sizing BES for cooperation with the PV system is that the committed energy—a contribution to the CSU—must be delivered at a specific time, whereas the PV power output on a day with partially clouded sky can vary rapidly. While the commitments rely on the weather forecasts from a preceding or earlier day, this puts the operation of PV on an electricity market at risk of not meeting the declared amounts. The most straightforward way is to design a battery able to discharge power equal to the peak power output of the PV system, taking into consideration the battery depth of discharge and ramp rate limitations, and capable of delivering maximum achievable hourly electricity production from PV. However, the high cost of batteries would lead to the unprofitability of the system, since balancing group would not accept increased prices of electricity from PV-BESS in fear of being unable to sell it on the DAM. Instead, the operator of the PV system must seek for a BES that stabilizes their hourly electricity production at minimum cost of electricity offered. Modeling tools can support the sizing of BES and simulations of PV-BESS participation to the DAM. However, they are usually unable to take into account all aspects of real-life PV-BESS cooperation to meet hourly commitments. This requires tests conducted on an existing PV-BESS system. Because of the commercial character of such installations, laboratory-built hybrid systems, featuring a real PV system along with real and emulated BES can be applied instead to conduct analyzes. The biggest challenge is the cost of the experiment, as this requires a laboratory equipped in a manner providing flexibility in building microgeneration systems containing BES and PV.
The research dealing with both the BESS-only and the RES-BESS hybrid system participation in electricity market has been presented to date in the literature. The studies mostly focused on modeling. Gomes et al. [
13] used two-stage stochastic programming problem to find optimal bid submission by jointly operated PV and wind farm with energy storage for the DAM in the Iberian Peninsula. The case of wind-BESS participation in the German spot market was presented by Cai et al. [
14], who applied a genetic algorithm to optimize battery size, while BESS itself was proposed to use the benefits of price variations in the DAM and intraday market, as well as to minimize the costs of forecasts errors. Ding et al. [
15] proposed ESS as a reserve capacity for a wind farm operating on the DAM and maximized expected profits using a mixed integer nonlinear programming model. Yang et al. [
16] developed a mixed-integer linear programming model to optimize scheduling of the battery performance to minimize the total cost of a hybrid system also containing PV and a wind power plant. There were also studies of sole operation of BESS on electricity markets and dealing with the optimization of bidding strategies of variable RES. Zhai et al. [
17] proposed a model of battery operating on the Australian electricity market and cost estimator to analyze the effects of market participation on the battery life. Pandžić and Kuzle [
18] developed a bi-level profit maximization model to evaluate the effects of energy storage on day-ahead market prices and the potential response of conventional plant operators. Fedjaev et al. [
19] built an optimization model using linear programming to manage a lithium-ion battery in an industrial microgrid. Mohsenian-Rad [
20] proposed a design framework for battery energy storage systems to optimize bidding and scheduling in California’s day-ahead market. Kazemi et al. [
21] considered battery energy storage simultaneously participating in the day-ahead, spinning reserve and regulation markets. Krishnamurthy et. al [
22] developed a stochastic model to maximize profit being subject to uncertainty, when the storage owner participates in the day-ahead and real-time markets. He et al. [
23] studied the optimal bidding strategy of the battery energy storage operating on electricity markets, taking into account performance-based regulation and battery lifespan. Hesse et al. [
24] optimized a dispatch strategy for a storage participating in German arbitrage energy market using mixed-integer programming model. Levelized cost of electricity (LCOE) calculations of PV systems were presented by International Energy Agency and Nuclear Energy Agency [
3], while more recent report on the subject was published by International Renewable Energy Agency (IRENA) [
25]. LCOE computation for energy storage systems was the subject of the paper by Obi et al. [
10]. This literature review shows that both the joint operation of the variable RES-BESS hybrid and battery-only participation in the day-ahead market is a widely addressed problem. However, to our best knowledge, there was no past attempt to apply a comprehensive methodology combining simulation models with live tests in the laboratory on real devices and economic analysis methods to assess the techno-economic viability of PV-BESS services offered to the day-ahead electricity market. In addition, the authors have not found any previous works providing detailed characteristics of DAM-participating PV-BES hybrid system parameters measured on real devices to verify simulation models. Finally, published research on levelized cost of electricity (LCOE) focused separately on PV or BES systems, while there was no reports on the LCOE of hybrid PV-BESS operating on the DAM, which involved both balancing costs and battery ageing.
To answer research questions raised in this paper, the simulation model of PV-BESS, using DIgSILENT PowerFactory environment was developed and BESS was sized on that basis. Subsequently, the bidding strategy was proposed and PV-BESS cooperation was simulated in PowerFactory, knowing the weather forecasts and PV generation profiles. To validate simulation models and show differences between the simulations and real life PV-BESS operation, live tests were conducted in LINTE^2—a laboratory for innovative power technologies and integration of renewable energy sources at Gdańsk University of Technology, Poland. Finally, the costs analysis of PV-BESS was conducted and presented in the context of varying DAM prices. The PV power generation hourly profile, covering all year, was developed and applied to reflect market operations during a representative year. Ageing of the battery and PV degradation were taken into account to calculate the annual costs throughout the 25-year PV system lifetime. This served as a basis for levelized cost calculation. The major contributions of the paper are: 1) the methodology of battery sizing and the simulation of its operation in a hybrid system with PV to submit bids to the common scheduling unit offered by the balancing group in a day-ahead market; 2) the methodology of real-life validation of the simulation models using laboratory-scale PV and BES systems, 3) the methodology of hybrid PV-BES cost analysis relying on hourly profile of electricity production, taking into account randomly generated error in the forecasted hourly production and costs of electricity balancing resulting from not meeting committed hourly electricity production. This paper summarizes and advances authors’ past work [
26]. Real-live experiments and cost analysis constitute a novelty in relation to previous publications.
3. Simulation Modeling
In order to verify BESS parameters, determined on the basis of a five-step methodology and with the use of the assumptions made in
Section 2, simulation studies were conducted.
A power grid model with BESS representation, based on work by Kottick et al. [
35], Medora and Kusko [
36], Barsali and Ceraolo [
37] and embedded in the Power Factory software [
38], was applied in simulations, and a PV model was added. The power of PV-BESS hybrid system was controlled at the point of common coupling (PCC). The topology of the test power system is presented in
Figure 3.
A detailed description of the experiment was presented in [
26], where two methods of participation in the DAM were considered:
Method #1—the committed generation power was constant over daily participation Δ
t =
T (
Figure 4a);
Method #2—the committed generation power varied every hour Δ
t = 1 h (
Figure 4b).
Both methods assumed that the PV-BESS hybrid participates in the DAM for T period daily.
Table 1 presents the results of battery sizing for a PV-BESS hybrid example. The required values of energy and real power of the battery, shown in
Table 1, were determined for generation profile “B” (
Figure 1), maximum PV farm power
Pmax(PV) = 4 MW, and the duration of electricity market participation
T = 10 h.
On the basis of conducted analysis, the advantages and disadvantages of both methods were indicated. The advantage of method #1 is the constant production of hybrid system power throughout the entire daily PV generation period. This enables to limit the variability of voltages and power flows in the examined area of the network. The biggest disadvantage of this method is the investment expenditure requirements. Compared with method #2, the energy storage capacity must be several dozen times greater, which practically disqualifies this method. In addition to economic reasons, the use of method #2 enables us to apply a more accurate short-term forecast of weather conditions, which translates into a more precise determination of production. This method allows for periodic (here Δt = 1 h) stabilization of active power flows in the examined area of the network. In addition, the use of converter systems enables to use the solutions that allow the regulation of reactive power flow or voltage level. Thus, it is possible for the analysed hybrid system to provide ancillary services in the scope of reactive power or voltage control at PCC.
To summarize the data gathered in
Section 2 and results obtained from simulation tests, the following steps are recommended:
Knowing the nature of the DAM and taking into account significant difference in capital expenditures, method #2 of bidding varying hourly electricity production should be adopted;
To size the battery power and energy capacity, the generation profile with the lowest instantaneous power variation, the maximum amplitude, and the maximum effective operation time should be chosen.
Considering the above, method #2 was chosen for the tests using real photovoltaic power plant and batteries.
4. Real-Time Tests
The results of the simulation tests described above were obtained assuming a small momentary variability of generation and 100% correctness of the solar irradiation forecast. For full verification of the proposed solution, two real-time experiments were performed with the use of LINTE^2 research laboratory infrastructure. In each of these tests the Li-ion battery was the subject of control. A scaled-down battery, connected to the low voltage power system, was used in the tests. Battery parameters are presented in
Table 2.
Tests were performed in two stages:
Stage #1—the PV generated power variation was emulated by laboratory load model based on power frequency converter. It allows, inter alia, us to freely shape the load / generation curve. Detailed information on the research capabilities of this device was provided in [
39,
40].
Stage #2—the experiment using a real PV power plant installed on the roof of the LINTE^2 laboratory (
Figure 5) was conducted.
The tests were carried out on the systems shown in
Figure 6, and the states of the switches were as follows:
Stage #1: switch S1 was ON, switch S2 was OFF;
Stage #2: the switch S1 was OFF and the switch S2 was ON.
The places of measurements were circled in
Figure 6 and were given symbols, which were used as indices of measured variables, presented in Figure 10a–d. All values were expressed in relative units (pu, per unit). The active power was referred to the rated power of the PV installation, the values of the battery current were referenced in the C-Rate scale i.e. the current related to the rated battery capacity.
4.1. Stage #1 - Test with Emulated PV and Real Battery Energy Storage
One of the important aspects related to PV operation control is generation predictability. To eliminate the problem of stochasticity of PV power generation in the first stage of research, the PV generation was emulated using a laboratory load model based on power frequency converter [
39]. This device modeled the variability of power generation according to the curve
PPV(
t), presented in
Figure 7a. This curve was also used to develop the characteristics of the set power variation
Pref(
t), also shown in
Figure 7a along with the characteristics of the power at the point of common coupling
PPCC(t).
The control of active power was performed adequately in every hour of the test. The temperature of battery modules did not exceed 30 ℃.
Figure 7b depicts the state of charge of the battery energy storage, whereas in
Figure 7c the battery current was presented. Measured power levels in selected points of the system (see
Figure 6) were shown in
Figure 7d.
The smallest generation of hybrid PV-BESS system was registered in the first hour, reaching 0.16 pu, and the largest generation was in the fifth hour i.e. 0.93 pu. As expected, slightly more than half of the battery energy capacity was used, which results from keeping the SOC in the range of 0.4–0.8 pu. Not using the entire range of available stored energy is caused by oversizing battery parameters in relation to the PV power. The battery selected in this way has a much larger capacity than would result from the energy demand in the control process.
In relation to the rated power of the hybrid power plant, the largest share of battery power was 0.15 pu.
Figure 8 shows the variability of battery voltage with characteristic sudden voltage changes occurring at full hours of the experiment. This behavior is related to the change in the power setpoint of the hybrid power generation system (
Pref) and thus the transition between charging and discharging modes.
Despite charging and discharging with 0.5C current, the 243 V voltage level, which triggers the maximum battery voltage limitation, was not exceeded.
The results shown in
Figure 7 and
Figure 8 confirm the correctness of the assumptions made. After a positive course of the first test, the test with a real solar plant was initiated.
4.2. Stage #2—The Test with Real PV and Real Battery Energy Storage
4.2.1. Setting the Setpoint Schedule
Commercial implementation of the proposed way of operation of the discussed hybrid system would require the use of advanced generation forecasting methods. The experiment presented in this paper did not cover issues related to one-minute average PV power output forecasting. The battery operation schedule was prepared on the basis of data from several days preceding the day of the experiment and was corrected on-line during the experiment, by the operator, whose decisions relied on the observations of the changing weather conditions and the state of the battery. It means the power setpoint (Pref) may have been different that the value of power declared for each hour of the day (Pdecl) and the PV-BESS hybrid system operator preferred to incur the cost of balancing shortages in delivered power to exposing the battery to a risk of accelerated ageing.
Observing the weather forecasts and the course of solar irradiation from the weather station, a test was planned for 27 July 2018. The course of insolation, registered by the weather station from the 23 to 26 July 2018, was illustrated in
Figure 9a, while the corresponding per-unit power output was presented in
Figure 9b. In the analyzed period, the insolation level (
Figure 9a) was characterized by high variability and the peak value was significant as for Polish conditions. A visible (around 12–1 pm) cyclical decrease in the level of insolation is the effect of shading the weather station by another object on the roof. Using the measurement data (
Figure 9a) a schedule of reference power (
Pref) values was determined for the mentioned three days and presented in
Figure 9b, while the schedule for the day of the test was determined as the average of the three preceding days.
4.2.2. Real-Time Test Realization and Results
The real-time test started at 7.15 am. Before starting the test the battery was discharged to the initial SOC value amounting to 0.55 pu. The test duration was 11.5 hours until 7 PM, and the curves were presented in
Figure 10.
The battery power waveforms (
Figure 10a) show what power the adjustment required in periods of cloud cover in the afternoon. The highest discharge power was 0.62 pu and the charge power was 0.46 pu. The above forced the battery current flow (
Figure 10c) to reach a maximum of 0.8C - a value that is greater than the 0.5C limit. However, this did not cause the battery to be disconnected. In the case of a lithium-ion battery, the operation with currents higher than 0.5C for a long time will not result in surpassing the permissible operating states. The critical moment from the point of view of the test was the occurrence of heavy cloud cover (about ninth hour of the experiment). A significant reduction in PV generation resulted in an increase in battery power transferred to the system. In order to avoid decreasing the SOC to the values below 0.4 pu, a significant adjustment of
Pref was introduced. This enabled fast rebuilding of the energy potential of the storage for further regulation.
In the event of sudden long-term cloudiness, in the case of real participation in active power control, an algorithm should be developed that changes the set point in such a way as to minimize losses resulting from failure to meet the declared power. Such an algorithm will be presented in subsequent publications of the authors.
6. Conclusions
The results obtained from the real-time control experiment have shown that energy storage cooperation with PV on a day-ahead market is technically feasible. However, developing a control strategy to follow hourly commitments is a complex problem. The laboratory experiment have proven that the real-life operation with set hourly values of average power requires frequent battery charging and discharging operations and constant control of battery parameters. Operators of the hybrid photovoltaic-battery energy storage system must bear in mind the limitations in the battery power output, capacity, state of charge and temperature to avoid its accelerated ageing. However, this requires their constant involvement in the control process. No less important issue is the development of forecasting mechanisms and behavior in situations of significant weather collapse. Algorithms with an in-built capability of weather forecasting could limit the extent of operator involvement and reduce the cost of market clearance with other members of the balancing group.
The cost of the battery energy storage system (per unit of electricity delivered to the point of common coupling) must be lower than the cost of electricity purchased on the balancing market to guarantee BESS profitability. In a current market situation, using battery is not profitable if a PV system offers electricity to the day-ahead market. The levelized cost of electricity is several times higher than the annual average day-ahead market price. Future changes in market conditions, involving the increase in electricity price, especially in specific times of the day (peak-time) will promote energy storage technologies. However, offering electricity at peak time requires batteries of capacities guaranteeing a storage of energy produced for several hours and would only be possible in a case of further battery-price decrease, since the capital component constitutes the highest share in the cost of electricity generated and offered to the market.
Battery use for voltage control is considered in the future research due to its excellent capabilities in terms of voltage and reactive power control. BESS allows independent control of active power and voltage at the point of common coupling. To make voltage control possible, the DC converter circuit must be supplied with active power, usually amounting to a dozen percent of the inverter rated power [
50]. This power either can flow from the grid or can be discharged from the BESS. Currently available converter systems are able to switch with very low power losses between the power consumption from the network and the storage-discharging mode. Bearing in mind the above, research on the method of controlling active and reactive power and voltage levels in hybrid power grids involving, for example, PV, wind farm, biogas plants, energy storage, etc. will be continued by the authors.