Battery Energy Storage System Installation Research Articles

Impact of intermittent electricity supply on a conceptual process design for microbial conversion of CO2 into hexanoic acid

Combining intermittent renewable electricity (IRE) with carbon capture and utilisation is urgently needed in the chemical sector. In this context, microbial electrosynthesis (MES) has gained attention. It can electrochemically produce hexanoic acid, a value-added chemical, from CO2. However, there is a lack of understanding regarding how the intermittency of renewable electricity could impact the design of a MES plant. We studied this using Aspen Plus models.A MES plant that was powered by constant grid electricity could operate from 100% down to 70% of its nominal capacity, at which point the heat exchangers and the internal geometrical design of the distillation towers became bottlenecks. The levelised production cost of hexanoic acid (LPCC6A) was estimated at 4.0 €/kg. Switching to IRE supply increased LPCC6A to 5.3 €/kg (for wind electricity) and 4.7 €/kg (for hybrid renewable electricity).A battery energy storage system (BESS) was deployed. The lowest LPCC6A was found at a BESS installation of 29 GJ/h for wind electricity (5.1 €/kg) and at 12 GJ/h for hybrid renewable electricity (4.7 €/kg). In both situations, the volume flexibility of the MES plant was not improved. At the investigated market and operating conditions, coupling IRE to the MES plant was economically infeasible.

Lithium-Ion Batteries on Board: A Review on Their Integration for Enabling the Energy Transition in Shipping Industry

The emission reductions mandated by International Maritime Regulations present an opportunity to implement full electric and hybrid vessels using large-scale battery energy storage systems (BESSs). lithium-ionion batteries (LIB), due to their high power and specific energy, which allows for scalability and adaptability to large transportation systems, are currently the most widely used electrochemical storage system. Hence, BESSs are the focus of this review proposing a comprehensive discussion on the commercial LIB chemistries that are currently available for marine applications and their potential role in ship services. This work outlines key elements that are necessary for designing a BESS for ships, including an overview of the regulatory framework for large-scale onboard LIB installations. The basic technical information about system integration has been summarized from various research projects, white papers, and test cases mentioned in available studies. The aim is to provide state-of-the-art information about the installation of BESSs on ships, in accordance with the latest applicable rules for ships. The goal of this study is to facilitate and promote the widespread use of batteries in the marine industry.

Optimal sizing and scheduling of battery energy storage system with solar and wind DG under seasonal load variations considering uncertainties

Battery energy storage systems (BESS) are integrated with renewable distribution generators (DG) within the distribution network (DN) to mitigate active power loss and improve the bus voltage profile through optimal placement and sizing. This work identifies the optimal location for BESS and DGs placement by deriving a loss sensitivity factor by considering the power flow through the branches and bus losses. With optimal location, a novel approach for selecting an optimal charging/discharging time schedule is proposed. This method aims to determine the optimal size and scheduling of BESS through the minimization of the voltage deviation and real power loss in the DN. Following the installation of BESS, the wind and solar DG optimal sizes are determined at maximum power generating hours. To address the uncertainties present in DN, Hong’s (2m+1) point estimation method is utilized to optimize the network operation incorporated with BESS and DGs. Furthermore, a techno-economic analysis is conducted to examine the energy savings resulting from integrating DGs and BESS in the DN. The power losses are further reduced by implementing network reconfiguration to reduce the energy dependency on the grid. The effectiveness of the proposed approach is tested on a 33-bus, 69-bus, and 118-bus DN under seasonal load variations. Incorporating the renewable DG with BESS into the DN reduces the grid energy supply by 30%–40%. The results of this study pave the way for more sustainable and efficient power systems by contributing to the development of techniques for integrating renewable energy sources into DNs.

Optimal BESS Sizing for Industrial Facilities Participating in RTP DR

The predictability of their manufacturing lines allows industrial facilities to optimize their production scheduling and to participate in demand response (DR), in day-ahead, real-time pricing (RTP) electricity markets. Battery energy storage systems (BESSs) make the electrical demand of industrial facilities more flexible and increase their potential to benefit from DR. The BESS sizing problem, for industrial facilities participating in RTP DR, is complex due to the discreteness of their manufacturing lines and the stochastic nature of electricity pricing. In this paper, an approach to BESS sizing is proposed. Scenario extraction using k-means clustering is used to reduce the problem complexity, and the extracted scenarios are preprocessed to reduce the search space for the optimal size of the BESS. The steps involved in the proposed approach are demonstrated, in detail, through a case study that uses a generic model of an industrial unit. The results of the case study show the effectiveness and validity of the problem reduction techniques used and highlight the role of electricity storage in maximizing the profits of the industrial unit. Finally, a sensitivity analysis is carried out to illustrate the impact of the BESS installation cost on the results.

A Model-Aware Comprehensive Tool for Battery Energy Storage System Sizing

This paper presents a parametric procedure to size a hybrid system consisting of renewable generation (wind turbines and photovoltaic panels) and Battery Energy Storage Systems (BESS). To cope with the increasing installation of grid-scale BESS, an innovative, fast and flexible procedure for evaluating an efficient size for this asset has been developed. The tool exploits a high-fidelity empirical model to assess stand-alone BESS or hybrid power plants under different service stacking configurations. The economic performance has been evaluated considering the revenue stacking that occurs when participating in up to four distinct energy markets and the degradation of the BESS performances due to both cycle- and calendar-aging. The parametric nature of the tool enables the investigation of a wide range of system parameters, including novel BESS control logic, market prices, and energy production. The presented outcomes detail the techno-economic performances of a hybrid system over a 20-year scenario, proposing a sensitivity analysis of both technical and economic parameters. The case study results highlight the necessity of steering BESS investment towards the coupling of RES and accurate planning of the service stacking. Indeed, the implementation of a storage system in an energy district improves the internal rate of return of the project by up to 10% in the best-case scenario. Moreover, accurate service stacking has shown a boost in revenues by up to 44% with the same degradation.

Optimal battery energy storage planning and control strategy for grid modernization using improved genetic algorithm

The flexible operation of battery energy storage systems (BESS) to support electricity grid modernization requires optimal planning and an efficient control strategy. This paper proposes the optimal allocation of BESS with photovoltaic systems for microgrids to enhance grid reliability and flexibility. An adaptive BESS control strategy is developed to allow the BESS to operate in both redundant and peak shaving modes. An evolutionary programming-based genetic algorithm implemented with an optimal power flow control is proposed to determine the BESS’s optimal location, sizing, and charge/discharge operation. The objective function is to maximize the benefits of energy loss reduction and peak shaving enhancement while minimizing the installation cost. The proposed approach is conducted with MATLAB and DIgSILENT PowerFactory software, which uses an intelligent automatic data exchange process to solve the optimal solution. A practical 22 kV grid-connected microgrid of Thailand is used as a test system to demonstrate the effectiveness of the planning and control strategy for the BESS installation. The simulation test results show that the proposed optimal BESS allocation and control strategy can significantly reduce the microgrid’s energy loss and peak demand and increase energy shaving leading to enhanced grid resiliency and reliability.

Participation of battery energy storage system for frequency control in wind dominated power systems: An analytical approach

The frequency performance of a power grid is effectively maintained through the utilization of inertia and power reserve provided by synchronous generators. The growing concerns surrounding global warming and the greenhouse effect have led to a significant increase in the integration of wind energy into the grid. But the system may face frequency instability following a contingency due to lack of sufficient inertia and headroom of wind generators. Therefore, the grid operator may require shedding some loads to prevent the system from severe frequency excursion. In this paper, we have estimated proper amount of load shedding through the formulation of analytical expression that will keep a highly wind penetrated & Battery Energy Storage System (BESS) integrated system stable. For this purpose, the maximum amount of wind power penetration level (WPPL) is first calculated using a fast analytical approach which utilizes two frequency response performance metrics, frequency nadir and Rate of Change of Frequency (ROCOF). In scenarios where the wind penetration level exceeds the calculated allowable threshold, it becomes necessary to implement load shedding measures following a contingency event. After installation of BESS, grid frequency response is much enhanced, hence, the required load shedding amount is also different. Therefore, we have derived an analytical expression for a quick measurement of frequency response enhancement attained by BESS. Finally, a frequency nadir-based load shedding scheme, being the goal of this paper, is proposed for a heavily wind penetrated grid with BESS, using the previously derived expression, to retain the grid at its nominal operating condition following a severe contingency. Our proposed scheme incorporates an analytical method to prevent over load shed. We have used DIgSILENT PowerFactory to validate our proposed analytical approaches through dynamic simulation. Results obtained from the proposed approaches nearly resemble the simulated one. Hence, this paper can help generating simplified yet effective models to conduct analysis on a wind integrated grid. This paper can also be regarded as a guide to ensure a wind penetrated resilient grid in view of frequency stability.

A CFD based methodology to design an explosion prevention system for Li-ion based battery energy storage system

This work developed a performance-based methodology to design a mechanical exhaust ventilation system for explosion prevention in Li-Ion-based stationary battery energy storage systems (BESS). The design methodology consists of identifying the hazard, developing failure scenarios, and providing mitigation measures to detect the battery gas and maintain its global concentration lower than 25% of the lower flammability limit (LFL) to meet the prescriptive performance criterion of NFPA 69 – Standard on Explosion Prevention Systems. Representative UL 9540A test data is used to define the battery gas composition, release rate, and release duration to describe the failure scenario involving thermal runaway propagation. In addition, an exemplar BESS enclosure geometry is defined to model the failure scenarios using a computational fluid dynamics (CFD) solver. A grid convergence study is performed to estimate the grid resolution required to perform the CFD analysis. In addition, sensitivity studies for different input parameters are performed to understand the impact of inputs on the detection times and ventilation performance. The approach used in this work provides a systematic procedure for the fire protection engineering community to understand the explosion prevention requirement for a BESS installation. The explosion prevention system functionality presented in this work is limited to removing flammable battery gas generated due to the non-flaring decomposition of batteries.

Best Practice in Battery Energy Storage for Photovoltaic Systems in Low Voltage Distribution Network: A Case Study of Thailand Provincial Electricity Authority Network

This research investigated the increases of the voltage profile on the Provincial Electricity Authority (PEA)’s low voltage (LV) network due to the solar photovoltaic (PV) penetration. This study proposed the solution to maintain the voltage profile within the PEA’s standard limitation by using battery energy storage system (BESS) application. The algorithm using bisection method to figure out the optimal size and location of BESS was examined and simulated in different scenarios such as summer/winter and weekend/weekday behaviors. Furthermore, the allocation of a battery in various locations was also considered. DIgSILENT power factory with DPL script and Python are the tools used to cover diverse scenario cases. The results showed that the best practice of how to implement BESS to solve the voltage rise problem was the BESS installation at the distribution transformer and the BESS installation separately at the end of each feeder near the loads. However, the optimal size of BESS installation at the distribution transformer was almost double that of installation at the end of each feeder.

Technology balancing for reliable EV uptake in distribution grids: An Australian case study

The emergence of new technologies, such as photovoltaic (PV) solar systems, household Battery Energy Storage Systems (BESS) and electric vehicles (EVs), has introduced challenges for the Distribution Network Operators (DNOs) in the operation of power distribution networks. Uncontrolled renewable energy generation and storage, and EV charging can cause over/under voltage problems. Recently, there has been much effort, from control and scheduling of BESSs and EVs to PV curtailment, to address these issues. However, the knowledge about how much penetration of these technologies can be well-tolerated by the grid when all charging/discharging are uncontrolled, would still be of interest to DNOs. There are many depending factors such as customer consumption profiles, grid conditions and network constraints. In this paper, we propose a framework to determine the critical balance between PV, BESS and EV in a distribution grid. Using real data from 4000 customers in Victoria, Australia, we find that in the absence of advanced control and scheduling algorithms, the best approach to prevent voltage violation in the grid is to keep the installation of PV and BESS balanced with the EV penetration. We also show that power export to the grid by EVs using the vehicle-to-home (V2H) technology may contribute to keeping the grid voltage in the standard range if 40%–80% of EVs are in the discharge mode in critical peak times. While complete coordination of PV, EV and BESS has not yet been fully realized in many networks, our methodology provides a framework for DNOs to perform optimised planning.

Community Battery Storage Systems Planning for Voltage Regulation in Low Voltage Distribution Systems

The regulation of the grid voltage within operational limits becomes increasingly challenging as residential photovoltaic (PV) adoption rises. Therefore, this study proposes a method for the efficient planning of multiple community battery energy storage systems (BESS) in low voltage distribution systems embedded with high residential rooftop PV units. A bi-level optimization method based on a Neural Network Optimization Algorithm is developed to regulate the voltage in grid-connected solar PV. Since BESS characteristics are crucial for the reliable operation of the distribution networks, the objective of the bi-level optimization problem is to optimally place and operate BESS collectively at a distributed system level. The charging/discharging protocol of the batteries management system is obtained utilizing linear programming that minimizes the daily voltage signal. Simulations were carried out on a modified IEEE low voltage test feeder to examine the impact of PV integration and BESS installation on the voltage profile. Experimental results show the efficacy of the proposed method in enabling the utility to determine the optimal location, capacity, and number of BESS in the distribution system to keep the network voltage magnitude within acceptable bounds. In addition, results demonstrate that the network topology, load profiles, and amount of PV power highly influence the BESS characteristics.

Optimal Location and Sizing of BESS for Performance Improvement of Distribution Systems with High DG Penetration

This work proposes an optimal location and sizing of battery energy storage system (BESS) installation for performance improvement of distribution systems with high distributed generation (DG) penetration level where the DGs comprise photovoltaics (PV) and wind turbines (WT). The installation of the BESS can reduce costs incurred in the systems, alleviate reverse power flow when the systems are in the high DG penetration level, and also achieve peak shaving during high demand. To find the optimal location and sizing of the BESS, three optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), and salp swarm algorithm (SSA), are applied, and their performances are compared. The considered objective function is the system costs consisting of transmission loss cost, peak power cost, and voltage deviation cost. The system performance improvement is compared in terms of transmission loss, peak demand, and voltage regulation reductions. IEEE 33- and 69-bus distribution systems with high DG penetration are tested to investigate the performance improvement of the BESS installation. The results found that the installation of the BESS could successfully decrease system cost, improve voltage profile, reduce power losses, alleviate reverse power flow, and achieve peak shaving where PSO and SSA are found to be the best competitive algorithms. So, the proposed method can be further applied to find the optimal location and sizing of the BESS to improve the performance of practical systems in the future.

An investigation for battery energy storage system installation with renewable energy resources in distribution system by considering residential, commercial and industrial load models

Battery energy storage system technique work as alternative load during low demand situation by storing the excess generation and work as alternative power generation source by discharging the stored generation during peak demand. In this work, a comprehensive assessment is performed for battery energy storage system installation and their capacities selection by utilizing the Photovoltaics (PV) output in radial distribution network by considering commercial, residential and industrial time varying load models. The objective of proposed the work is to reduce annual energy losses, mitigate reverse power flow and overvoltage problem and provide peak power dispatch during peak demand in distribution network. A comparative investigation is performed by considering PV and PV-BESS case for each type of load model. Furthermore, the battery energy storage system (BESS) function developed that decide the time and capacity of charging and discharging in order to manage PV penetration and improve the voltage profile, minimize the daily energy losses and control the reverse power flow in the distribution system without deviating the operational limits. A voltage based sensitivity method is developed at initial step to find out the most prominent node in distribution network for BESS installation. The objective of the problem is resolved by genetic algorithm to find out the optimal solution and to assess the comparison of technical parameters between considered cases. The simulation results on IEEE 69 bus test system show that the proposed methodology for BESS placement decreases the annual energy losses, enhances the PV penetration and reduces the overvoltage and mitigate the reverse power flow. Results of this paper also shows that it is possible to dispatch peak power during the peak load hours for each type of load model.

Unbalanced Current Reduction Method of Microgrid Based on Power Conversion System Operation

In isolated areas such as islands with small power grids, the BESS (Battery energy storage system) can supply the standard voltage and frequency to the power system to achieve 100% of renewable sharing. In addition, the installation of additional BESS may be required in the microgrid due to technical limitations such as redundant operation and manufacturer specifications. Thus, the BESSs in a microgrid can be split into main and sub BESSs which play a role as the main source and auxiliary services, respectively. Generally, the ratio of unbalance current in microgrid system tends to be high, because of inherently unbalanced single phase load distribution. However, because the capacity of BESS is calculated under balanced conditions, the PCS (Power conversion system) of BESS may stop protecting its switching device from a single phase overcurrent in actual operation. From this perspective, this paper proposes that the sub BESSs perform dual current control to supply the unbalanced current instead of the main BESS. In the simulation result of the proposed method, the current unbalance rate of the main ESS has been reduced by about 26%. Through the proposed control scheme, it is possible to prevent an unexpected single phase overload of the main BESS in the microgrid.

A business-oriented approach for battery energy storage placement in power systems

Battery energy storage systems (BESSs) are gaining increasing importance in the low carbon transformation of power systems. Their deployment in the power grid, however, is currently challenged by the economic viability of BESS projects. To drive the growth of the BESS industry, private, commercial, and institutional investments in large-scale BESS projects are needed. For financiers and investors, choosing an appropriate BESS installation location is a crucial task that requires important considerations. However, so far, studies targeting the BESS placement problem have mainly focused on minimizing operational losses, solving power quality issues, and improving the voltage profile of the system. Implementing such approaches only considers the operational feasibility of BESS at the installation site while ignoring its business feasibility. Therefore, in this paper, we approach the BESS placement problem from a business viewpoint by conducting a stage-level investigation of BESS projects. First, we identify the factors impacting the business feasibility of placement decisions in projects’ construction, connection, operation, and disposal stages and propose cost and time effective measures for making them business friendly. We investigate several factors such as profitability of grid services, integrability of renewable resources, affordability of connection charges, and the usability of BESS capacity. Second, we investigate the business potential of placing BESSs in different grid-levels of the power system and examine BESS connection procedures at those levels. Third, we implement the proposed approach for installing a BESS in the Danish island of Bornholm, for which, we investigate multiple locations of the Bornholm power system.

Implementation of Distributed Autonomous Control Based Battery Energy Storage System for Frequency Regulation

It has been mandated that 5% of the generation capacity of conventional fossil fuel power plants shall be used exclusively for frequency regulation (FR) purposes in South Korea. However, the rotational speed of generators cannot be controlled quickly, and thus the variation in the power generation for FR takes some time. Even during this short period of time, frequency fluctuations may occur, and the frequency may be out of range of its reference value. In order to overcome the limitations of the existing FR method, 374 MW (103 MWh) battery energy storage systems (BESSs) for FR have been installed and are in operation at 13 sites in South Korea. When designing the capacity of BESS for FR, three key factors, i.e., the deployment time, duration of delivery, and end of delivery, are considered. When these times can be reduced, the required capacity for BESS installation can be decreased, achieving the same operational effects with minimal investment in the facilities. However, because a BESS for FR (FR BESS) needs to be installed under a large capacity, providing a single output, a centralized control method is employed. The centralized control method has the advantage of being able to view and check the entire system at once, although in the case of FR BESS, a novel system design that can optimize the above three factors through a faster and more accurate control is required. Therefore, this paper proposes the implementation of a distributed autonomous control-based BESS for frequency regulation. For the proposed FR BESS, the central control system is responsible for the determination of external factors, e.g., power generation/demand forecasting; and the system is designed such that the optimal control method of renewable energy sources and BESS according to real-time frequency variations during practical operation is determined and operated using a distributed autonomous control method. Furthermore, this study was verified through the simulation that the proposed distributed autonomous control method conducts FR faster than an FR BESS with conventional centralized control, leading to an increase in the FR success rate, and a decrease in the deployment time required (e.g., 200 ms).

Optimal Siting and Sizing of Battery Energy Storage: Case Study Seventh Feeder at Nakhon Phanom Substation in Thailand

The optimal siting and sizing of battery energy storage system (BESS) is proposed in this study to improve the performance of the seventh feeder at Nakhon Phanom substation, which is a distribution network with the connected photovoltaic (PV) in Thailand. The considered objective function aims to improve the distribution network performance by minimizing costs incurred in the distribution network within a day, comprising of voltage regulation cost, real power loss cost, and peak demand cost. Particle swarm optimization (PSO) is applied to solve the optimization problem. It is found that the optimal siting and sizing of the BESS installation could improve the performance of the distribution network in terms of cost minimization, voltage profile, real power loss, and peak demand. The results are investigated from three cases where case 1 is without PV and BESS installation, case 2 is with only PV installation, and case 3 is with PV and BESS installations. The comparison results show that case 3 provided the best costs, voltage deviation, real power loss, and peak demand compared to those of cases 1 and 2; system costs provided by cases 1, 2 and 3 are USD 4598, USD 5418, and USD 1467, respectively.

Technical and Financial Impacts on Distribution Systems of Integrating Batteries Controlled by Uncoordinated Strategies

This study assesses the technical and financial impacts on voltage levels, peak demand, and technical losses of distribution systems due to the integration of battery energy storage systems (BESSs) associated with photovoltaic distributed generation (PVDG). It assumes that the BESS features (location and storage capacity) are chosen by consumers individually, aiming to directly benefit themselves according to self-consumption and price arbitrage uncoordinated control strategies. Computational simulations of several PVDG/BESS penetration levels in residential feeders of a Brazilian utility were performed via OpenDSS, employing real data of the load (consumption and load profiles) and photovoltaic generation (irradiance and temperature). We address the PVDG/BESS locations and the selection of solar irradiance, temperature, and load profile based on the Monte Carlo method. As the impacts on voltage levels, peak demand, and technical losses are expressed in different units, they were stochastically converted into monetary amounts to identify the control strategy that enhances the technical benefits in the distribution system. The results show that BESS installation with location, size, and control strategy defined by consumers creates technical benefits for the distribution system. The risk analysis allows us to conclude that price arbitrage should be prioritized in deciding incentives for penetration levels of up to 60%. Above these levels, self-consumption should be prioritized as an incentive. However, it is worth mentioning that the two strategies could be encouraged regardless of the penetration levels, as both create technical benefits for the distribution networks. The proposed method can support policy proposals to encourage BESS integration in distribution systems.

Determination of optimal battery energy storage system capacity for commercial electricity consumers with photovoltaic systems by integrating battery aging and PV forecast uncertainty

A battery energy storage system (BESS) is a promising technology to augment the benefits provided by photovoltaic (PV) power generation. This study proposes a method to evaluate the optimal capacity of a BESS for commercial electricity consumers with PV systems. This method considers the aging effect of a BESS and the PV output uncertainty through linear programming and a real‐time control method. The benefit of BESS installation is assessed through cost–benefit analysis by using the net present value (NPV) in the determination of the optimal BESS capacity. Subsequently, the method is applied to the numerical simulation of a commercial load. In the numerical simulation, an optimal capacity is demonstrated at which the benefits of the BESS are maximum, especially the NPV. In addition, we highlight the impact of PV output uncertainty on the benefits of the BESS and verify the effectiveness of the proposed real‐time control method in mitigating this impact. The importance of considering the degradation of a BESS in the evaluation of the optimal capacity is also discussed. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

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.