Loss-Voltage Sensitivity Analysis Based Battery Energy Storage Systems Allocation and Distributed Generation Capacity Upgrade

Anuradha, K.; Jayatunga, Upuli; Perera, H. Y. Ranjit

doi:10.1016/j.est.2021.102357

Cited by 14 publications

(4 citation statements)

References 38 publications

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“…Various objectives, such as overall performance improvement [9], loss reduction [10], voltage profile improvement [11], and cost minimization [12][13][14], have been adopted to achieve optimal planning of DGs or ESSs in ADNs. However, the role of ADNs has evolved significantly compared to that of conventional (passive) networks.…”

Section: Literature Reviewmentioning

confidence: 99%

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Evolutionary Approach for DISCO Profit Maximization by Optimal Planning of Distributed Generators and Energy Storage Systems in Active Distribution Networks

Mahfoud,

Alkayem,

Fernandez-Rodriguez

et al. 2024

Mathematics

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Distribution companies (DISCOs) aim to maximize their annual profits by performing the optimal planning of distributed generators (DGs) or energy storage systems (ESSs) in the deregulated electricity markets. Some previous studies have focused on the simultaneous planning of DGs and ESSs for DISCO profit maximization but have rarely considered the reactive powers of DGs and ESSs. In addition, the optimization methods used for solving this problem are either traditional or outdated, which may not yield superior results. To address these issues, this paper simultaneously performs the optimal planning of DGs and ESSs in distribution networks for DISCO profit maximization. The utilized model not only takes into account the revenues of trading active and reactive powers but also addresses the active and reactive powers of DGs and ESSs. To solve the optimization problem, a new hybrid evolutionary algorithm (EA) called the oppositional social engineering differential evolution with Lévy flights (OSEDE/LFs) is proposed. The OSEDE/LFs is applied to optimize the planning model using the 30-Bus and IEEE 69-Bus networks as test systems. The results of the two case studies are compared with several other EAs. The results confirm the significance of the planning model in achieving higher profits and demonstrate the effectiveness of the proposed approach when compared with other EAs.

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Section: Literature Reviewmentioning

confidence: 99%

“…This has been achieved in previous works using different optimization methods. Conventional methods, such as the analytical method proposed in [11], have been used. Linear programming (LP) [20], mixed-integer LP (MILP) [21], and mixed-integer nonlinear programming (MINLP) [13,15] have been applied to build the proposed models.…”

Section: Literature Reviewmentioning

confidence: 99%

Evolutionary Approach for DISCO Profit Maximization by Optimal Planning of Distributed Generators and Energy Storage Systems in Active Distribution Networks

Mahfoud,

Alkayem,

Fernandez-Rodriguez

et al. 2024

Mathematics

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“…Saini and Gidwani [11] proposed a GA-based techno-economical methodology with BESS placement. Anuradha et al [12] proposed a voltage and loss sensitivity analysis based technique and Thokar et al [13] used a moth search algorithm for allocating BESS to enhance the DG capacity. Ahmadi et al [14] proposed a multi-verse optimization algorithm-based approach for optimum coordination of BESS with DGs.…”

Section: Introductionmentioning

confidence: 99%

Optimum Placement of Battery Energy Storage Systems and Solar PV Units in Distribution Networks Using Gravitational Search Algorithm

Goli¹,

Yelem²,

Jasthi³

et al. 2023

Atlantis Highlights in Intelligent Systems

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This paper proposes the optimum sizing and placement of photovoltaic (PV) units and battery energy storage systems using the Gravitational Search Algorithm (GSA) to minimize the burden on the substation. The solar PV units are allocated for daytime peak load reduction and the evening load is compensated with battery energy storage systems. Optimum placement and sizing of solar PV units and shunt capacitors is carried out to minimize the real and reactive powers drawn from the substation to a predefined value, minimize the active power losses, and improve the distribution system's voltage profile. The BESS capacity required for nighttime is also estimated by considering similar objectives. Simulation results have been presented using a 69 bustest system to demonstrate the significance of the proposed methodology.

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“…The studies by Anuradha, K.B.J. [19] and Baghbanzadeh, D. [20] point to the importance of loss reduction in the operation and distribution of electricity generated by distributed energy systems.…”

Section: Introductionmentioning

confidence: 99%

Raising the Resilience of Industrial Manufacturers through Implementing Natural Gas-Fired Distributed Energy Resource Systems with Demand Response

2023

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The use of relatively small-scale distributed electric power generation sources is one of the key focus areas in the development of global industry and regional power generation. By integrating distributed generation sources into their on-site energy infrastructure, industrial consumers gain new characteristics and possibilities as entities of the power system that do not only consume power, but in fact can flexibly generate and deliver electricity to local and even centralized grids. This type of entity is called a distributed energy resource system with demand response (Russian: ‘active energy complex’). The purpose of this study is to lay the methodological foundation for the use of distributed energy resource systems with demand response in industrial sites under existing gas and power market conditions and for ensuring the synchronization of parameters that is necessary for managing complex energy consumption. This article provides an empirical study of the principles of the natural gas pricing under the demand volatility of regional markets and the Russian Mercantile Exchange. The article outlines the key drivers, as identified by the authors, that impact gas consumption by a distributed energy resource system, including demand characteristics, limitations and capacity of the gas network and the mode of gas consumption by an industrial enterprise and its generator. Accounting for all of these factors is essential for effective management and proper operational adjustment of a distributed energy resource system with demand response. The result of the study is a proprietary model and a tool for the management of distributed energy resource systems in integration with the gas demand management, which analyze the internal and external parameters of the industrial entity’s operations and its distributed energy resource system, as well as factors existing in the integrated distributed energy system where the consumer is able to buy natural gas in various market segments. The proprietary tool of distributed energy resource system management is based on the centralized control system, which combines performance analytics, operational scheduling of production and the distributed energy resource system, price planning for the wholesale and retail power markets, regional gas markets and exchange, monitoring all elements of the system, and assessment of different active energy management scenarios under various external and internal conditions impacting production and energy demand. Our proprietary tool has been successfully tested in a typical industrial site and was reported to deliver a significant electricity and gas cost-saving effect, which amounted to an 18 percent reduction in the total energy costs of the company, or more than USD 2.6 million per year. The resulting saving effect can recoup the costs of investing in a distributed energy resource system, including construction and installation of the local grid and automation infrastructure, and can be obtained in any country of the world.

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Loss-Voltage Sensitivity Analysis Based Battery Energy Storage Systems Allocation and Distributed Generation Capacity Upgrade

Cited by 14 publications

References 38 publications

Evolutionary Approach for DISCO Profit Maximization by Optimal Planning of Distributed Generators and Energy Storage Systems in Active Distribution Networks

Evolutionary Approach for DISCO Profit Maximization by Optimal Planning of Distributed Generators and Energy Storage Systems in Active Distribution Networks

Optimum Placement of Battery Energy Storage Systems and Solar PV Units in Distribution Networks Using Gravitational Search Algorithm

Raising the Resilience of Industrial Manufacturers through Implementing Natural Gas-Fired Distributed Energy Resource Systems with Demand Response

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