Optimal sizing and placement of energy storage system in power grids: A state-of-the-art one-stop handbook

Wind farm (WF) power output is not constant due to the intermittent nature of wind speed, wind direction, and wind turbine (WT) wake effect. The integration of WF into large power systems affects the transmission system's available transfer capability (ATC). In this paper, WF power output is calculated by a proposed formula that considers the wind direction and wake effect of WT. The battery energy storage system (BESS) has been installed in the system, and charging/discharging criteria have been created to enhance the ATC value of the system. The clusters/zones are created according to transmission congestion distribution factor (TCDF) values. The average TCDF (ATCDF) value is proposed to select the optimal position of WF and BESS. The proposed approach increases ATC significantly. The results are simulated in the IEEE-30 bus system.

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“…The shadow area for WT placed at d distance can be calculated from Figure 2. The mathematical formula is shown in Equation (11). 33 A…”

Section: P Vmentioning

confidence: 99%

AnATCDFapproach forATCenhancement using charging/discharging ofwind‐batterysystem considering wind direction and wake effect ofWTs

Narain

Srivastava

Singh

2021

Int Trans Electr Energ Syst

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“…Recently, a large number of scholars have performed studies in this field (Yang et al, 2020). The literature (Oudalov et al, 2007) tends to optimize the location and power capacity of BESSs by calculating the sensitivity of network loss, and then reduce the power loss of DN.…”

Section: Introductionmentioning

confidence: 99%

Optimal Locating and Sizing of BESSs in Distribution Network Based on Multi-Objective Memetic Salp Swarm Algorithm

et al. 2021

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Battery energy storage systems (BESSs) are a key technology to accommodate the uncertainties of RESs and load demand. However, BESSs at an improper location and size may result in no-reasonable investment costs and even unsafe system operation. To realize the economic and reliable operation of BESSs in the distribution network (DN), this paper establishes a multi-objective optimization model for the optimal locating and sizing of BESSs, which aims at minimizing the total investment cost of BESSs, the power loss cost of DN and the power fluctuation of the grid connection point. Firstly, a multi-objective memetic salp swarm algorithm (MMSSA) was designed to derive a set of uniformly distributed non-dominated Pareto solutions of the BESSs allocation scheme, and accumulate them in a retention called a repository. Next, the best compromised Pareto solution was objectively selected from the repository via the ideal-point decision method (IPDM), where the best trade-off among different objectives was achieved. Finally, the effectiveness of the proposed algorithm was verified based on the extended IEEE 33-bus test system. Simulation results demonstrate that the proposed method not only effectively improves the economy of BESSs investment but also significantly reduces power loss and power fluctuation.

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“…When different energy vectors are intertwined in future smart energy systems, optimal sizing of each component is especially important. In the research on the optimal sizing of renewable energy systems, many papers have considered WT, PV, ESS, and fuel cells (Yang et al, 2020;Yang et al, 2021). However, the previous published papers only considered the perspective of electrical power use, and do not consider both heat demand and electricity generation together as well as the impact of heating demand that increases the electrical energy use under the trend of electrified heating in the future.…”

Section: Introductionmentioning

confidence: 99%

Optimal Sizing of a Grid Independent Renewable Heating System for Building Decarbonisation

Chen

Friedrich

2021

Front. Energy Res.

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As the use of fossil fuels has led to global climate change due to global warming, most countries are aiming to reduce greenhouse gas emissions through the application of renewable energies. Due to the distributed and seasonal heating demand, the decarbonisation of heating is more challenging, especially for countries that are cold in winters. Electrically powered heat pumps are considered as an attractive solution for decarbonising heating sector. Since grid-powered heat pumps may significantly increase the power demand of the grid, this paper considers using local renewable energy to provide power for heat pumps, which is known as the grid independent renewable heating system including photovoltaic, wind turbine, battery storage system and thermal energy storage. This paper investigates a complete renewable heating system (RHS) framework and sizing the components to decarbonise building heating. The relationship between the reduction of gas consumption and the requirement of battery storage system (BSS) under the corresponding installation capacity of renewable components is analysed with their technical requirements. Then, according to different investment plans, this paper uses the particle swarm optimisation algorithm for optimal sizing of each component in the RHS to find a solution to minimise CO2 emissions. The results verify that the RHS with optimal sizing can minimise CO2 emissions and reduce the operational cost of natural gas. This work provides a feasible solution of how to invest the RHS to replace the existing heating system based on gas boilers and CHPs.

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Optimal sizing and placement of energy storage system in power grids: A state-of-the-art one-stop handbook

Cited by 65 publications

References 139 publications

AnATCDFapproach forATCenhancement using charging/discharging ofwind‐batterysystem considering wind direction and wake effect ofWTs

AnATCDFapproach forATCenhancement using charging/discharging ofwind‐batterysystem considering wind direction and wake effect ofWTs

Optimal Locating and Sizing of BESSs in Distribution Network Based on Multi-Objective Memetic Salp Swarm Algorithm

Optimal Sizing of a Grid Independent Renewable Heating System for Building Decarbonisation

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