MWh Battery Energy Storage System Research Articles

Improved rule-based power distribution algorithm for hybrid battery storage systems and real-world validation

Large-scale battery energy storage systems (BESS) can serve many applications and are already widely used for grid services. The rapidly growing BESS market and the recent interest in their deployment accentuate the need for safe, reliable, and highly available energy management systems (EMS) for automated control. However, the EMS and their integrated power distribution algorithms (PDA) can still be optimized to adapt various characteristics of the BESS. This study investigates a new version of a PDA with a particular focus on battery aging and system efficiency. The rule-based PDA has been validated on a 6 MW/7.5 MWh BESS system with five battery technologies providing frequency containment reserve to the German power grid. The results underline the PDA's capability to exploit the individual strengths of each battery technology. The PDA sets objectives for the state of charge, energy throughput, and power of the batteries to extend battery life. The distribution of energy throughputs among batteries can be selected in advance through the new implementation of the PDA. At the same time, the inverters are significantly less often activated and used in the optimal efficiency range, increasing the overall system efficiency to approximately 82 %. The optimized switching behavior leads to less frequent power switching between individual battery units and longer phases with more constant power. In addition, the operational efficiency of BESS can be improved by the choice of battery technology and the overall system layout on the hardware side. The improvements on the software side are only possible by increasing the overall power requests through multi-use operation by about 6 % compared to our benchmark test. The results can be used by BESS operators to increase operational profits due to longer battery life and fewer efficiency losses.

Strategic Implicit Balancing With Energy Storage Systems via Stochastic Model Predictive Control

Battery Energy Storage Systems (BESS) may exploit the increasing price volatility in imbalance settlement mechanisms via inter-temporal arbitrage. However, participating in these markets requires a careful trade-off between expected profits, accounting for the impact of BESS actions on prevailing imbalance prices, the financial risks and the incurred battery degradation costs. This paper introduces a novel forecast-informed Model Predictive Control (MPC) methodology in which a strategic and potentially risk-averse BESS performs implicit balancing by taking out-of-balance positions in near-real time. Thereby it anticipates expected imbalance prices in a European-style balancing market, and takes into account state of charge-dependent battery degradation costs. To this end, an attention-based recurrent neural network forecasting technique is leveraged to predict the System Imbalance. The proposed methodology is tested on a real-life case study of the Belgian balancing market. Expected profits of a 2 MW/2 MWh BESS (21,784 MW/month) are shown to exceed those of different benchmarks available in the literature, including the profit associated with participating in the day-ahead energy market with perfect price foresight (7,082 /MW/month). From a system perspective, these implicit balancing actions performed by the BESS owner reduce the system imbalance in 75% of all cases, thus improving the cost-efficiency of power systems.

Power quality enhancement for Thailand's wind farm using 5 MWh Li-ion battery energy storage system

Several studies have stated that an increase in wind power plants and unpredictable wind energy generation face several issues during over-voltage. In this study, an operational 8 MW wind farm in Nakhon Ratchasima province faced severe annual feeder trips 146 times, which is not permissible according to the manufacturers. The feeder trips are mainly attributed to high grid voltage caused by low load demand. This study developed a Battery Energy Storage System (BESS) to minimise feeder trips using DigiSILENT and utilized the higher feeder trip period of September to optimise BESS capacity with a 10 % grid load. Notably, a 5 MWh BESS maintained the grid voltage within an allowable range compared to the 1–4 MWh (increment of 1 MWh) throughout the operational period. Furthermore, a 5 MWh BESS was tested during low and high wind periods to assess the stability of over-voltage management. We found that the 5 MWh BESS controlled over-voltage and prevented feeder trips, resulting in enhanced power generation on selective days with high feeder trips, low wind speed, and high wind speed, generating 28.34 MWh, 0.33 MWh, and 76.67 MWh, respectively, compared to conditions without BESS. Additionally, we recommend that the 5 MWh BESS can enhance wind farm power stability and uphold the manufacturer's warranty.

Cooperation Mode and Operation Strategy for the Union of Thermal Generating Unit and Battery Storage to Improve AGC Performance

With the growing penetration of intermittent renewable energy resources in power systems, it is a challenge for automatic generation control (AGC) to maintain the required control performance. In recent years, battery energy storage systems (BESSs) have been installed in thermal power plants to provide frequency regulation service bundled with the traditional thermal generating units (TGUs). However, in real projects, the installed BESS typically works as parasitic equipment of the generating unit, which limits the coordination between the TGU and the BESS. In this paper, a complementary cooperation pattern is proposed for the TGU-BESS union to improve the dispatchability of its response to the AGC signal. Then, the correlation between the BESS's energy demand and the TGU's operation states is described by a data-driven method, which combines fuzzy c-means cluster, r-vine copula, and random forest. Finally, a rolling-horizon energy balance strategy is developed to make the control decisions for the TGU-BESS union in response to the stochastic AGC signal. The effectiveness of the proposed method is demonstrated using the historical data from a real union with a 9MW/4.5MWh BESS and a 350MW coal-fired generator.

A novel hybrid optimization framework for sizing renewable energy systems integrated with energy storage systems with solar photovoltaics, wind, battery and electrolyzer-fuel cell

This study proposes a novel approach to evaluate the integration of solar photovoltaic (PV) and wind turbine renewable energy systems (RES) with Electrolyzer-Fuel Cell Energy Storage System (EFCS) and Battery Energy Storage System (BESS). The objective is to minimize the weighted average cost of energy (waCOE) while maintaining a specific renewable energy fraction (FRES). To achieve this objective, a new hybrid optimization system that combines Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is proposed to simultaneously optimize the capacity of PV, wind turbine, battery, electrolyzer, hydrogen tank, and fuel cell, which makes it a complex and nonlinear optimization problem. The proposed method produces more practical outcomes by implementing some constraints on PSO and strengthens its ability to exploit optimization opportunities. Six scenarios representing different integrated systems are investigated and compared technically and economically, including PV + BESS, PV + EFCS, Wind + BESS, Wind + EFCS, PV + Wind + BESS, and PV + Wind + EFCS. A case study is conducted on a university campus situated on a Mediterranean island, where electricity production relies on imported fossil fuel. The findings indicate that a PV-wind hybrid system consisting of a 1.15 MW wind turbine, a 2.89 MW PV, and a 2.31 MWh BESS has the lowest waCOE of 0.1838 €/kWh. This system is capable of providing a demand–supply fraction (DSF) of 44.63% with a FRES of 60.1%. The study found that a hybrid system consisting of PV and wind turbines showed promise in the examined region due to their complementary characteristics. Additionally, combining various RES with BESS with approximately 33–35% lower waCOE was found to be more economically viable and resulted in 16–20% higher DSF compared to EFCS.

Optimal intra-day operations of behind-the-meter battery storage for primary frequency regulation provision: A hybrid lookahead method

Battery energy storage systems (BESSs) are being widely installed behind-the-meter to reduce electricity bill. By providing grid ancillary services, behind-the-meter BESSs can increase potential revenue streams. This study targets the simultaneous electricity bill reduction and primary frequency regulation (PFR) provision. With the expansion of the application spectrum, the intra-day operations become more and more complicated. In this paper, a hybrid lookahead method with value function approximation strategy is proposed for intra-day operations, wherein the concept of “offline calculation—online application” is devised and implemented. The approximate value function is trained offline to represent the expected long-term benefit. A two-stage robust approximate dynamic programming (ADP) model is formulated for one day operation which is optimized to adjust the power baseline with a forward rolling horizon. Furthermore, multi-dimensional indicators are introduced to evaluate the proposed strategy. Simulations and benchmarking comparisons are performed for a 0.5 MW/1.0 MWh BESS to verify the superior performance of the proposed strategy. The results show that the approximate value function can be obtained offline with 99.07% convergence precision. Moreover, the proposed strategy can ensure the economic benefit and PFR provision within a short online computing time. The resulting intra-day economic benefit can reach 95.55% of the theoretical optimum, and the online optimization consumes only 4.65s for a prediction horizon of 5 min, which ensures the feasibility of real-time predictive optimization.

Reliable Dispatch of Active Distribution Networks via a Two-Layer Grid-Aware Model Predictive Control: Theory and Experimental Validation

Dispatching active distribution networks (ADNs) is an energy-intensive application that, if implemented via battery-energy storage systems (BESSs), can require a large capacity of these assets in order to fully balance the uncertainties caused by the stochastic demand and generation. The insufficient capacity of the BESSs often leads to their state-of-charge (SOC) saturation; this results in unreliable dispatch tracking. In this work, we propose and experimentally validate a real-time control scheme that achieves a highly-reliable dispatching of ADNs and ensures that the BESSs’ SOC is not saturated during the daily operation. Our proposed scheme uses a two-layer model predictive control (MPC). The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">upper-layer</i> MPC, running every 5 minutes, optimizes the BESSs’ SOC trajectories while minimizing the tracking error, considering the prosumption forecast of the whole day. Then, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">lower layer</i> MPC, running every 30 seconds, takes the BESSs’ SOC trajectories as constraints while achieving a high-resolution tracking of the dispatch plan over the current 5-minute time horizon. Both layers account for the grid constraints by using the augmented relaxed optimal power-flow (AR-OPF) model; an exact convex relaxation of the original AC-OPF and used in this paper (for the first time in the literature) to solve a real-time constrained control problem for ADNs. Our proposed framework was experimentally validated using a 1.5 MVA/2.5 MWh BESS connected to an actual 24-node medium-voltage (MV) ADN that, in Aigle, Switzerland, hosted an uncontrollable 3.2 MWp distributed photovoltaic generation, 3.4 MVA hydro-power generations, and a 2.8 MW base demand.

Case study of power allocation strategy for a grid‐side lead‐carbon battery energy storage system

Battery energy storage system (BESS) is an important component of future energy infrastructure with significant renewable energy penetration. Lead-carbon battery is an evolution of the traditional lead-acid technology with the advantage of lower life cycle cost and it is regarded as a promising candidate for grid-side BESS deployment. However, inconsistency among lead-carbon batteries in a BESS is a major concern which has to be carefully considered in practical operation. One of the available approaches to relieve this issue is to develop a sophisticated power allocation strategy (PAS) among multiple converters inside the BESS. This work conducts a comprehensive case study on the impact of PAS in a grid-side 12 MW/48 MWh BESS recently constructed in Zhejiang, China (Zhicheng energy storage station, the first grid-side lead-carbon BESS in China). Three different PASs (i.e. averaged, state weighted and state prioritized) are investigated and benchmarked with two typical BESS application scenarios of peak shaving and frequency regulation, from real-world experiments using the aforementioned BESS. The performance of the strategies is quantitatively evaluated by three indices defined in this work. The state prioritized strategy is found to be the most effective for this lead-carbon BESS.

Efficiency Comparison of DC and AC Coupling Solutions for Large-Scale PV+BESS Power Plants

In large-scale photovoltaic (PV) power plants, the integration of a battery energy storage system (BESS) permits a more flexible operation, allowing the plant to support grid stability. In hybrid PV+BESS plants, the storage system can be integrated by using different power conversion system (PCS) layouts and different charge–discharge strategies. In the AC-coupling layout, the BESS is connected to the ac-side of the system through an additional inverter. In the DC-coupling layout, the BESS is connected to the dc-side, with or without a dedicated dc–dc converter, and no additional inverter is needed. Referring to a 288 MWp PV plant with a 275 MWh BESS, this paper compares the PCS efficiency between AC- and DC-coupling solutions. The power injected into the grid is obtained considering providing primary power-frequency regulation services. A charging and discharging strategy of the BESS is proposed to ensure cyclic battery energy shifting. The power flows in the different components of the system that are obtained under realistic operating conditions, and total energy losses and annual average efficiency are calculated accordingly. Finally, results show a higher efficiency of DC-coupling compared to the AC-coupling layout.

Economic evaluation of operation strategies for battery systems in football stadiums: A Norwegian case study

This paper describes a techno-economic evaluation of case studies performed at the Skagerak EnergyLab. The EnergyLab consists of a 1.1 MWh battery energy storage system (BESS) and a 800 kWp photovoltaic (PV) power plant installed in a football stadium. The aim of this paper is to analyse the installation’s performance by studying a variety of cases involving operation strategies for peak shaving, self-consumption maximisation, energy arbitrage and feed-in limitation. The software tool SimSES is used to simulate BESS degradation. Moreover, the Norwegian economic and regulatory framework is used as a basis for an economic evaluation. An important outcome of this work is that a BESS that offers stacked value by combining peak shaving, energy arbitrage, self-consumption and the replacement of a backup diesel generator, may represent a feasible option in Norway. The techno-economic analysis also demonstrates that the profitability is heavily dependent on the operation strategy of the BESS.

Optimal Sizing and Performance Assessment of a Hybrid Diesel and Photovoltaic with Battery Storage based on Take-or-Pay of Power Purchase Agreement

In remote and rural areas where diesel generators are usually employed for electricity production, the photovoltaic (PV) panels combined with battery energy storage systems (BESS) can lead affordable and reliable power generation. In this work, a real case study in Nusa Penida Island, Bali Province, Indonesia, is conducted for studying the optimal sizing and performance assessment of a hybrid diesel-PV-BESS system limited by a take or pay of Power Purchase Agreement (PPA). The island’s solar irradiance is 5,36 kWh/m 2 /day and 7 x 1.7 MW diesel power plant stations are currently run for fulfilling the island’s electricity demand. The stations are embedded into an existing 20 kV distribution grid. Using the electricity demand projection of several representative days in a year, the software is utilized in this work for designing and optimizing the size of PV and BESS integrated to the diesel power generators. In this study, the performance of configurations with four different sizes of PV and BESS is assessed and evaluated using load flow analysis, short circuit analysis and transient stability analysis. The simulation results demonstrate that the optimal sizing of the hybrid system consists of 10 MWp PV and 10 MWh BESS with Levelized Cost of Energy of 9.45 c USD/kWh. It lowers 40% of the current cost. Considering the initial, maintenance, replacement and fuel costs, the net present cost of the optimal configuration is 135,306,800 USD. This study confirms that the renewable energy penetration in remote and rural islands can be increased by optimally utilizing energy storage.

Demonstrating Stacked Services of a Battery in a Wind R&amp;D Park

This paper describes the demonstration and evaluation of stacking wind power time-shifting and regulation by a 1 MW/2 MWh battery energy storage system (BESS) within a 10 MW wind park. The BESS time-shifted 15.8 MWh of wind power to peak periods while responding to the automatic generation control (AGC) signals that provide regulation over the 24 day test period. Its fast response time and accurate output allowed the BESS to provide both services simultaneously. Limiting the charging to periods when wind power was available lowered the amount of time-shifting and AGC that could be provided. Some form of AGC was delivered from the BESS for 78.5% of the test period and, if it were remunerated at the PJM rate when the test was performed, it would have earned 8627 USD, with 97% from regulation and the rest from time-shifting wind power. Using PJM's performance template, the BESS averaged a performance score of 70.5% during hours when regulation was performed. This work adds to the growing empirical data that is informing models of and policy for grid storage.

Price development and bidding strategies for battery energy storage systems on the primary control reserve market

Decreasing prices on the German primary control reserve (PCR) market lead to an uncertain economic situation for battery energy storage systems (BESS) providing PCR. In a simulation-based approach, which takes into consideration application-specific aging, an economic assessment of a 1.5 MWh BESS providing PCR is conducted. Different bidding strategies for PCR auctions have been developed and their impact on revenues and battery aging has been investigated. Furthermore, following an option value approach, we analyzed how different PCR price paths and the time of investment affect the economic feasibility of BESS providing PCR.The results show that the choice of strategies developed in this paper do not have a substantial influence on revenues and battery aging. However, the development of PCR market prices and battery system costs is crucial for the economic feasibility of BESS providing PCR. Investments come with a high risk due to the volatility of PCR market prices and the uncertainty of future battery system prices.

Model-based Economic Assessment of Stationary Battery Systems Providing Primary Control Reserve

Rapidly decreasing battery prices and high capacity prices on the German primary control reserve (PCR) market promote the attractiveness of battery energy storage systems (BESS) for primary control provision. In order to assess the economic feasibility in this application field, two case studies based on a 2 MWh BESS are performed. By coupling a PCR simulation model with a battery aging model, battery lifetimes are estimated. Costs and revenues occurring during the lifetime are calculated using the net present value approach. The results indicate that a BESS with a power-to-energy ratio of 1:2 is not economically feasible under the current framework. A BESS with a power-to-energy ratio of 1:1 will break even after approximately nine years of operation. Decreasing battery system prices are likely to increase the price pressure on the PCR market leading to decreasing revenues for PCR supply. Battery aging results suggest similar aging behavior for both systems presented due to the prevalence of shallow DoD cycles and the resulting predominance of calendar aging.

Demonstration of a Large-Scale Energy Storage System for Peak Shaving in the Electric Power System

The penetration level of renewable energy (RE) resources used to supply electricity is expected to increase rapidly in the coming years. This growth is strongly encouraged by the government through various policies such as renewable portfolio standards and feed-in tariffs. [1]However, because the performance of a power system is critically constrained by many factors that impact its stability, having a high penetration of RE resources with an unpredictable nature in bulk power systems is very challenging for system operators. [2]To address the stability issues of RE, it has been proposed that large-scale energy storage systems (ESS) be applied to bulk power systems. ESS can be controlled to supply quickly the exact amount of power required in securing the stability of the power system, even with a very high penetration of RE resources that can negatively impact the dynamic performance of the power system. In addition, ESS’s can also be used to provide ancillary services, such as frequency regulation, and bulk energy services, such as peak-shaving and load-leveling, in power systems. Load-leveling and peak-shaving are ESS applications that provide long-term services, wherein the charging and discharging of power takes place within several hours. These services involve charging the ESS during periods when the loads of electric power are low and discharging the stored energy to the power system when the loads are high. [3]In this work, a demonstration of a large-scale, grid-connected 4 MW/8 MWh battery ESS (BESS) using lithium-ion batteries (LiB), has been implemented. The 4 MW/8 MWh BESS is simultaneously connected to a 22.9 kV substation bus and distribution line in the Jocheon substation on Jeju Island. Operation strategies of the BESS have also been developed for peak-shaving (or electric energy time-shift). The peak-shaving operation uses the expected load for the next day. Also, the effects of peak-shaving are also analyzed in this work.In this work, 60Ah(Ampere hour) LiB cell was employed, and 16 cells were assembled to 1.8kWh-class module. A tray consisted of two modules, and one rack was installed using 16 battery trays, a rack BMS(Battery Management System), and a switch gear. One container consisted of 18 racks connected in parallel which summed up to 1MWh capacity. The developed energy storage system was based on a technology of small lithium rechargeable battery. The BESS consisted of three-stage control system as Tray, Rack, and System. The smallest component of BESS is battery cell. The rated capacity of battery cell is 60Ah and 3.7V. BESS is available to change battery capacity by connecting the battery cells in series or parallel. The 1MWh LiB system consisted of eighteen battery racks in parallel. BMS is responsible for monitoring the individual control and protection functions for the entire circuit unit cells. The system BMS is in charge of calculating a state of charge, state of health, power prediction, and internal impedance of the system. This can support the communication protocols of CAN 2.08, RS-485, and MODbus-TCP/IP. The rack BMS is used for monitoring the voltage and the current of the rack and calculating a state of charge, state of health, power prediction, and internal impedance of the rack. In addition, this in charge of the switching control and the cell balancing in the rack. Finally, the tray BMS can measure the voltage and the temperature of each cell, and control the cell balancing in the tray. The ESS of a 4MW PCS and 8MWh batteries installed in Jocheon substation, Jeju Island. There are four 1MW PCS configured to have a total capacity of 4MW. Each 1MW PCS is connected to two containers of 1MWh batteries with a total of 2MWh capacity paired in one PCS. This makes the discharge duration of 2 hours. In addition, the BESS may be charged from the grid and discharge power to the grid thru the PCS as dictated by the PMS. Using a large scale energy storage device can give numerous benefits such as load factor improvement, peak shaving and load leveling, improve quality of distributed renewable energy, support emergency power supply, and offer high-quality power service to customers. The introduction of a large scale energy storage system to the grid can enhance the smart grid to respond efficiently to the demand of electricity from consumers with real-time power output control. Fig. 1 shows the original load and shaved one by ESS operation. From ESS operation for peak shaving, the 5.5 percent and 4.8 percent of peak shaving could be obtained in winter and summer peak time respectively. Figure 1

Optimal Control of Li-Ion Battery Energy Storage System for Frequency Regulation

The usage of renewable energy to supply electricity demands is expected to increase drastically in the coming years. This is attribute to the encouragement of the government through policies such as RPS(renewable energy portfolio standards) and FIT(feed-in-tariffs). However, the performance of power system is sometimes critically constrained by stability characteristics. It is very challenging for system operators to manage a high penetration of renewable energy resources in a bulk power system, as they are known to deteriorate the dynamic performance of power systems.Therefore, it has been proposed that the large-scale Energy Storage System (ESS) of which power output can be controlled accurately and quickly can be applied to a bulk power system for securing the stability of the system despite a high penetration of the renewable energy resources. By increasing deployment of renewable energy, importance of power grid stability has been increased. For example, Wind Power has characteristics of difficult prediction and rapid variation depending on the regional climate characteristics. Energy Storage System aims to transform an uncontrollably variable and partially unpredictable renewable energy into a controlled and predictable one. For these purpose, a quickly responsive and highly efficient control-algorithm is essential. It is for using such a high performance of ESS when a disturbance occurs on a electrical grid system.KEPCO implemented a demonstration project on large-scale grid connected 4 MW / 8 MWh Battery ESS (BESS) using Lithium-Ion Battery (LIB). Fig. 1 shows the interconnection of ESS at the demonstration site. The 4 MW / 8 MWh BESS is connected to both the 22.9kV substation bus and the distribution line in Jocheon, Jeju Island for offshore wind turbines. In this study, Operation strategies for the BESS were developed for frequency regulation of the grid-system. Fig. 1 Interconnection of ESS at Jocheon Substation For power system frequency regulation, There are two kinds of control strategies through ESS here. One is for the normal status that the ratio of frequency change is not bigger than reference ratio of frequency change(ξ). The reference ratio is frequency changes per second when the smallest power supply was failed from the power system. The other is for the dynamic status that the ratio of frequency change is bigger than the reference ratio. In case of South Korea, it is about -0.306 Hz/sec. It could be variable every year because the total amount of power supply in the grid-system would be different. In this paper, we researched briefly about the normal status.At normal control mode, the power output(P) of the ESS is proportional to the change in frequency(f). kd is a proportional coefficient set by the droop characteristics of a battery generation.P=kd(60-f) In order to distribute output power of each battery, this study established a SOC(State Of Charge) weighted control strategy that can consider the SOC of each battery. The following factors were considered to provide frequency regulation service while considering the SOC :1) Set proportional coefficient (kd) for calculating total output demand2) Set priority at output distribution according to SOC3) Consider rating output of each battery when distributing outputAt normal status, the proportional coefficient(kd) was set by applying the droop of a general generator. This is to control the ESS output with a performance similar to the droop of the general generator. When allocating output demand determined by each battery SOC through this strategy, the battery with a higher SOC have priority in distribution. This is more efficient way to fulfill the total output demand cost-effectively. The SOC weighted control result is shown in Figure 2.Fig. 2 Result of battery output during SOC weighted control (simulation)It can be found that the distributed quantity of output was provided depending on the SOC level of each battery. It's likely to be seen that a battery with a higher SOC has priority in the distribution of output.SOC management effect of the control algorithm was analyzed through a 5-hour too. The result obtained from a simulation frequency of five hours before and after a credible accident. We can find that, in the range within dead band, the control of battery was conducted in order to reach a SOC sustainment section. When the frequency is in the dead band, ESS is not working for frequency regulation. In the outside range of the frequency dead band, it was observed that control capacity was distributed according to SOC in order to provide frequency regulation.

Dynamic Available AGC Based Approach for Enhancing Utility Scale Energy Storage Performance

With ever-increasing penetration of non-dispatchable intermittent generation resources in electric grids all over the world, the system operators are facing more challenges to meet the system AGC requirements which aim to maintain the target grid frequency and scheduled tie flows. The utility scale energy storage applications have been often referred to as one of the potential solutions for improving the system frequency response, especially the speed of response. A new concept relating to the use of Dynamic Available AGC (DAA) of the Battery Energy Storage System (BESS) is proposed in this paper and applied in conjunction with the priority and proportional AGC signal distribution strategies. Additionally, this paper proposes an independent AGC control strategy based on Area Control Error (ACE) signal distribution to further enhance the impact of the fast response capability of the BESS. The same is accomplished by means of implementing an independent Proportional Integral (PI) controller without low-order filter typically associated with the ACE signal distribution. The AGC simulation results based on generation trip and normal load variance events, as tested on the El Salvador system model, indicate significant benefits to the system AGC performance when using the concept of the DAA for the BESS and the independent AGC control strategy. The AGC simulation results also indicate that the utilization of 10 MW/3.66 MWh BESS can replace about 36 MW conventional AGC units on the tested system model without compromising on the AGC performance of the system for day-to-day variations experienced in the system load.

Design and commissioning of a valve-regulated lead/acid battery energy-storage system for backing up critical environmental loads

Momentary and sustained electrical power interruptions and voltage depressions represent two of the most difficult and important power quality and delivery problems that face many industrial and commercial users. There is a definite need at many industrial processing plants and commercial users of electrical power to have a dependable, efficient and controllable source of real and reactive power that is available instantly to support large electrical loads (greater than 5 MVA), even if the incoming utility a.c. connection is lost. When power is interrupted or lost, the results can be extremely disruptive for critical processes and cause lost production, costly downtime and loss of customer good will, and in certain industries, can lead to environmental damage through the release of toxic emissions into the air. Recently, this challenge was faced by GNB Technologies at its lead reclaiming and smelting facility in Vernon, CA, USA. This study describes a versatile, cost-effective, workable solution to the problem that has resulted in the design and installation of a 5 MVA, 3.5 MWh battery energy storage system (BESS) which provides uninterruptible power to the critical environmental control equipment throughout the plant. The BESS at Vernon provides the required power, combined with both voltage and frequency control, to allow the plant to tolerate disconnection from the utility grid without suffering unacceptable impacts on critical loads. The system also provides the company with a demand-side energy management system for conducting daily peak shaving of energy demand and, thereby, reduces its electrical bills.