Battery Energy Storage System Installation Research Articles

Optimal Siting and Sizing of Battery Energy Storage Systems for Distribution Network of Distribution System Operators

In this work, optimal siting and sizing of a battery energy storage system (BESS) in a distribution network with renewable energy sources (RESs) of distribution network operators (DNO) are presented to reduce the effect of RES fluctuations for power generation reliability and quality. The optimal siting and sizing of the BESS are found by minimizing the costs caused by the voltage deviations, power losses, and peak demands in the distribution network for improving the performance of the distribution network. The simulation results of the BESS installation were evaluated in the IEEE 33-bus distribution network. Genetic algorithm (GA) and particle swarm optimization (PSO) were adopted to solve this optimization problem, and the results obtained from these two algorithms were compared. After the BESS installation in the distribution network, the voltage deviations, power losses, and peak demands were reduced when compared to those of the case without BESS installation.

An intelligent energy management system to use parking lots as energy storage systems in smoothing short-term power fluctuations of renewable resources

Renewable energy sources (RES) provide significant environmental benefits, but are highly variable. Intelligent Parking Lots (IPL) can be utilized for smoothing renewable sources, thus reducing the need for large battery energy storage systems (BESS). However, the integration of intermittent RES with IPLs can be challenging. A proper energy management system (EMS) is need to optimize resource operations, reduce investment costs, and support higher penetrations of renewable energy. This paper presents a novel, heuristics-based EMS for an IPL coupled with wind turbines, photovoltaic systems, and expansion turbines, which avoids the need for BESS installation. Extensive simulation results for the case of the city of Isfahan show that the proposed EMS can smooth the output power of RES with a maximum variation of 5% during each 10-minute window. The method utilizes a small number of electric vehicles (EVs), and preserves the EVs battery lifetime by reducing the number of switching actions to an average of 0.2 for each EV, while satisfying the requested EV charge level.

An Integrated Transmission Expansion and Sectionalizing-Based Black Start Allocation of BESS Planning Strategy for Enhanced Power Grid Resilience

This paper proposes a new comprehensive integrated planning strategy for the resilience enhancement of power system, including determining the transmission expansion and sectionalizing-based optimal black start (BS) resources allocation of battery energy storage system (BESS) during extreme events. The planning model comprises of two stages, namely the normal stage and resilience stage. The first stage is to make the collaborative planning decisions, i.e., constructing transmission lines and installation of BESS as BS sources. The second stage minimizes the power system generation cost and load shedding cost under disaster conditions. The planning algorithm is developed to describe the uncertainty of transmission lines outage status, which can be affected by the normal stage expansion states. In algorithm ways, the model was solved with a duality-based column and constraint generation (D-CCG) method. Taking IEEE 30-bus and 39-bus system for examples and GUROBI/CPLEX was utilized to solve proposed model. Numerical cases show the effectiveness of the model and the superiority of the solution strategy.

Increasing Benefits in High PV Penetration Distribution System by Using Battery Enegy Storage and Capacitor Placement Based on Salp Swarm Algorithm

This work aims to maximize the benefit of the low-voltage (LV) level distribution system with high photovoltaic (PV) penetration by using an optimal installation of a battery energy storage system (BESS) and capacitor. The 41-bus practical distribution system located in Thailand was focused on. The comprehensive objective function regarding the focused system was proposed. The Salp Swarm and Genetic Algorithms were applied to solve the optimization problem. The total net present value (NPV) of utility was performed as a beneficial indicator, and it was determined by the overall costs and benefits of BESS installation and capacitor placement. A comparison of total NPV in the cases of centralized BESS installation, BESS installation with LV capacitor placement, and decentralized BESS installation was indicated. The results showed that all cases of BESS installation could increasingly flatten the load on the transformer; meanwhile, the voltage profile of the system was significantly improved. Optimal installation of centralized BESS simultaneously with LV capacitor placement provides higher NPV than the case with only centralized BESS installation. In particular, the highest NPV was obtained in the case of installing decentralized BESS. The results can be utilized to maximize the benefits of the utility in the distribution system at a high PV penetration level.

Quantification of Efficiency Improvements from Integration of Battery Energy Storage Systems and Renewable Energy Sources into Domestic Distribution Networks

Due to the increasing use of renewable, non-controllable energy generation systems energy storage systems (ESS) are seen as a necessary part of future power delivery systems. ESS have gained research interest and practical implementation over the past decade and this is expected to continue into the future. This is due to the economic and operational benefits for both network operators and customers, battery energy storage system (BESS) is used as the main focus of this research paper. This paper presents an analytical study of the benefits of deploying distributed BESS in an electrical distribution network (DN). The work explores the optimum location of installing BESS and its impact on the DN performance and possible future investment. This study provides a comparison between bulk energy storage installed at three different locations; medium voltage (MV) side and low voltage (LV) side of the distribution transformer (DT) and distributed energy storage at customers’ feeders. The performance of a typical UK DN is examined under different penetration levels of wind energy generation units and BESS. The results show that the minimum storage size is obtained when BESS is installed next to the DT. However, the power loss is reduced to its minimum when BESS and wind energy are both distributed at load busbars. The study demonstrates that BESS installation has improved the loss of life factor of the distribution transformer.

Sizing Battery Energy Storage Systems: Using Multi-Objective Optimization to Overcome the Investment Scale Problem of Annual Worth

The financial objective, when sizing a Battery Energy Storage System (BESS) for installation in a microgrid, is to maximise the difference between discounted BESS benefits and discounted BESS costs. This may be described as maximising Annual Worth (AW). However, one drawback of sizing microgrid BESS using AW is that the scale of investment is not taken into consideration. This can lead to unrealistic BESS sizes. This article presents two multi-objective optimisation (MOO) models to account for the scale of investment required in sizing BESS. The first model, Paired Comparison, utilises two objective functions: Daily Worth (DW), which maximises daily benefit cost differences a BESS installation provides a microgrid; and Daily Cost (DC), which minimises the daily cost of a BESS installation. The second model, called Rating Method, uses the objective functions DW and Daily Benefit-Cost Ratio (DBCR), the latter of which maximises the relative measure of BESS benefit and BESS cost. Both models are solved for a test microgrid system under three different scenarios using Compromise Programming (CP). For system designers who rank objective functions by importance, the Rating Method is the appropriate approach, whereas system designers who rank objective functions by absolute values should use Paired Comparison.

Characterization of a Fast Battery Energy Storage System for Primary Frequency Response

In response to increasing integration of renewable energy sources on electric grid systems, battery energy storage systems (BESSs) are being deployed world-wide to provide grid services, including fast frequency regulation. Without mitigating technologies, such as BESSs, highly variable renewables can cause operational and reliability problems on isolated grids. Prior to the deployment of a BESS, an electric utility company will typically perform modeling to estimate cost benefits and determine grid impacts. While there may be a comparison of grid operations before and after BESS installation, passive monitoring typically does not provide information needed to tune the BESS such that the desired services are maintained, while also minimizing the cycling of the BESS. This paper presents the results of testing from a live grid using a method that systematically characterizes the performance of a BESS. The method is sensitive enough to discern how changes in tuning parameters effect both grid service and the cycling of the BESS. This paper discusses the application of this methodology to a 1 MW BESS regulating the entire island of Hawaii (180 MW peak load) in-situ. Significant mitigation of renewable volatility was demonstrated while minimizing BESS cycling.

Evaluation of a 1 MW, 250 kW-hr Battery Energy Storage System for Grid Services for the Island of Hawaii

Battery energy storage systems (BESSs) are being deployed on electrical grids in significant numbers to provide fast-response services. These systems are normally procured by the end user, such as a utility grid owner or independent power producer. This paper introduces a novel research project in which a research institution has purchased a 1 MW BESS and turned ownership over to a utility company under an agreement that allowed the institution to perform experimentation and data collection on the grid for a multi-year period. This arrangement, along with protocols governing experimentation, has created a unique research opportunity to actively and systematically test the impact of a BESS on a live island grid. The 2012 installation and commissioning of the BESS was facilitated by a partnership between the Hawaii Natural Energy Institute (HNEI) and the utility owner, the Hawaiian Electric and Light Company (HELCO). After the test period ended, HELCO continued to allow data collection (including health testing). In 2018, after 8500 equivalent cycles, the BESS continues to operate within specifications. HNEI continues to provide HELCO with expertise to aid with diagnostics as needed. Details about the BESS design, installation, experimental protocols, initial results, and lessons learned are presented in this paper.

Line Loss Reduction by Optimal Location of Battery Energy Storage System for the Daily Operation in Microgrid with Distributed Generations

Distributed generations (DGs) such as solar and wind generations are used as generation source in the microgrid. Due to the fluctuation of renewable energy sources, the battery energy storage system (BESS) is one of the essential components to control and improve the quality of power microgrid. However, a placement for BESS installation with minimizing line loss is one of the most concern problems. This paper aims to determine the optimal location of the BESS by using the analytical method with the line loss sensitivity index. A multi-period optimal power flow (OPF) and line loss analysis with BESS parameters were investigated considering the daily operation of a microgrid in connected mode. The simulation performed on the microgrid that wants to keep total power generation from DGs in BESS and low energy consumption from the utility. Microgrid includes 3 DGs (biomass, solar and wind turbine generators) to assess the robustness of BESS placement. The results confirmed the effectiveness of the presented method. The optimal location of BESS can reduce line power loss and power consumption from the utility.

Optimal Design and Operation of a Remote Hybrid Microgrid

High operational costs, environmental concerns and fuel handling challenges in diesel-based remote off-grid systems have prompted the application of alternative sources of energy and energy storage systems. Based on these drives, operators of isolated microgrids have been seeking out these alternatives. In response, a Canadian utility is investigating the application of utility scale photovoltaic (PV) generation and Battery Energy Storage Systems (BESS) to supplement existing Diesel Generators (DiGs) in an off-grid community. This paper presents the design, operation, and dispatch strategy for this hybrid PV/BESS/DiG isolated microgrid. A Northern remote off-grid community in Canada is used as a case study. Custom models to accurately represent all components of the hybrid microgrid in the Northern climate are developed first. Then, optimization algorithm that minimizes the Annual System Cost (ASC) are developed to size the PV and BESS. The algorithm incorporates the cost of the BESS, the rated power limits of PV and BESS, and the prime rating capability of DiGs. Finally, the paper proposes to optimally site the BESS by minimizing the total system loss and optimizing the voltage profile along the feeders. The study reports both cost saving and power quality improvement with the installation of PV and BESS, and presents guidelines on how to generalize these results to other hybrid isolated microgrids.

Siting and sizing of distributed energy storage to mitigate voltage impact by solar PV in distribution systems

This work explores the allocation question of battery energy storage systems (BESS) in distribution systems for their voltage mitigation support in integrating high penetration solar photovoltaics (PV). A genetic algorithm (GA)-based bi-level optimization method is developed that reduces the voltage fluctuations caused by PV penetration through deploying BESS among permitted nodes of a distribution system while accounting for their capital, land-of-use and installation costs using a qualitative cost model. The optimization problem considers BESS capacity and installation points in the distribution system as decision variables. Each BESS operation is determined using a linear programming (LP) routine that minimizes the daily coincident peak demand. A comprehensive validation study is carried out through exhaustive enumeration with the IEEE 8500-Node test feeder showing that the proposed method results in consistent decisions that appear to be globally optimal. Further sensitivity studies are conducted to showcase the behavior of the method under varying sizing costs, siting costs and PV penetrations.

Optimization of a battery energy storage system using particle swarm optimization for stand-alone microgrids

The main challenge in integrating a Battery Energy Storage System (BESS) into a microgrid is to evaluate an optimum size of BESS to prevent the microgrid from instability and system collapse. The installation of BESS at a random size or non-optimum size can increase in cost, system losses and larger BESS capacity. Thus, this paper proposes the new method to evaluate an optimum size of BESS at minimal total BESS cost by using particle swarm optimization (PSO)-based frequency control of the stand-alone microgrid. The research target is to propose an optimum size of BESS by using the PSO method-based frequency control in order to prevent the microgrid from instability and system collapse after the loss of the utility grid (e.g., blackout or disasters) and minimize the total cost of BESS for 15years installation in the microgrid. Then, the economical performance of BESS with modern different storage technologies is investigated and compared in the typical microgrid. Results show that the optimum size of BESS-based PSO method can achieve higher dynamic performance of the system than the optimum size of BESS-based analytic method and the conventional size of BESS. In terms of BESS economical performance with modern storage technologies, the installation of the polysulfide–bromine BESS is likely to be more cost-effective than the installation of the vanadium redox BESS for 15years installation in the typical microgrid. It is concluded that the proposed PSO method-based frequency control can improve significantly power system stability, grid security, and planning flexibility for the microgrid system. At the same time, it can fulfill the frequency control requirements with a high economic profitability.

Determination of the installation site and optimal capacity of the battery energy storage system for load leveling

This study aims to show methods of determining the installation site and the optimal capacity of a battery energy storage system (BESS) to attain load leveling. The methods are based on the hardware characteristics of 20 kW/100 kWh and 1 MW/4 MWh prototype BESSs, which are already developed and are being developed, respectively. The candidate site of BESS installation is the secondary side of a distribution substation's main transformer (MTR). These tasks are performed by first classifying the load pattern of an MTR and comparing it to the load pattern of a total power system. If the load factor improves, then the location is determined to be a BESS installation site. Subsequently, the optimal BESS capacity for an MTR is determined using the given operation pattern, the charging/discharging characteristics and efficiency. Computational experimentation was performed on an actual distribution system in Korea. After determining the optimal capacity, the authors verified that installing the BESS on the selected MTR improved both daily and nightly load factors.