Optimal Scheduling for Energy Storage Systems in Distribution Networks

Escoto, Miquel; Montagud, Mario; González, Noemi; Belinchón, Alejandro; Trujillo, Adriana Valentina; Romero, Julián; Díaz-Cabrera, Julio César; García, Marta Pellicer; López, Amparo

doi:10.3390/en13153921

Cited by 7 publications

(2 citation statements)

References 23 publications

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“…The proposed strategy can mitigate the voltage unbalance issue, improve the voltage profile, and correct power factors while supporting sustainable distribution system operation. Many more research works proved how efficient BESS is on the optimum dispatching due to the high penetration of renewable energy sources (RES) that are distributed and not centralized [31][32][33][34].…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of Distributed Energy Storage on Distribution and Transmission Networks’ Power Quality

et al. 2022

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This study investigates the effect of distributed Energy Storage Systems (ESSs) on the power quality of distribution and transmission networks. More specifically, this project aims to assess the impact of distributed ESS integration on power quality improvement in certain network topologies compared to typical centralized ESS architecture. Furthermore, an assessment is made to see if the network topology in which an ESS position supports its ability to restore node voltage magnitude within acceptable ranges. The power quality of a benchmark interconnected distribution and transmission network was determined using NEPLAN software. Following that, twelve variants of the benchmark were modeled, each with a different ESS integration architecture and (or) topology. Their power quality performance was compared to that of a benchmark network in addition to several cross analyses to determine the relative impact on power quality within the context of their respective ESS integration methodologies. The findings of this study buttress the understanding that the distributed ESS integration architecture within the distribution network topology, where the majority of consumer loads are connected, provides the strongest case for voltage magnitude power quality compensation, as required by the UK Electrical System Grid Code’s 5% rated node voltage compliance processes regulation.

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Section: Literature Reviewmentioning

confidence: 99%

The Impact of Distributed Energy Storage on Distribution and Transmission Networks’ Power Quality

et al. 2022

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“…Next and current position of cheetah (i = 1, 2,…,n) X i n Position of particle i at iteration n Traditional utility has faced several challenges in recent decades. One of the most challenging issues represents in the vulnerability of traditional grid to single points of failure, such as equipment malfunctions, natural disasters and cyberattacks 1 , which can lead to widespread power outages. In addition, integrating large-scale Renewable Energy Sources (RESs) into the traditional grid poses technical challenges because of variable generation, intermittency and the need for substantial grid upgrades 2 .…”

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confidence: 99%

Hybrid cheetah particle swarm optimization based optimal hierarchical control of multiple microgrids

Mohamed,

Mahmoud,

Saied

et al. 2024

Sci Rep

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The emergence of microgrids arises from the growing integration of Renewable Energy Resources (RES) and Energy Storage Systems (ESSs) into Distribution Networks (DNs). Effective integration, coordination, and control of Multiple Microgrids (MMGs) whereas navigating the complexities of energy transition within this context poses a significant challenge. The dynamic operation of MMGs is a challenge faced by the traditional distributed hierarchical control techniques. The application of Artificial Intelligence (AI) techniques is a promising way to improve the control and dynamic operation of MMGs in future smart DNs. In this paper, an innovative hybrid optimization technique that originates from Cheetah Optimization (CHO) and Particle Swarm Optimization (PSO) techniques is proposed, known as HYCHOPSO. Extensive benchmark testing validates HYCHOPSO’s superiority over CHO and PSO in terms of convergence performance. The objective for this hybridization stems from the complementary strengths of CHO and PSO. CHO demonstrates rapid convergence in local search spaces, while PSO excels in global exploration. By combining these techniques, the aim is to leverage their respective advantages and enhance the algorithm's overall performance in addressing complex optimization problems. The contribution of this paper offering a unique approach to addressing optimization challenges in microgrid systems. Through a comprehensive comparative study, HYCHOPSO is evaluated against various metaheuristic optimization approaches, demonstrating superior performance, particularly in optimizing the design parameters of Proportional-Integral (PI) controllers for hierarchical control systems within microgrids. This contribution expands the repertoire of available optimization methodologies and offers practical solutions to critical challenges in microgrid optimization, enhancing the efficiency, reliability, and sustainability of microgrid operations. HYCHOPSO achieves its optimal score within fewer than 50 iterations, unlike CHO, GWO, PSO, Hybrid-GWO-PSO, and SSIA-PSO, which stabilize after around 200 iterations. Across various benchmark functions, HYCHOPSO consistently demonstrates the lowest mean values, attains scores closer to the optimal values of the benchmark functions, underscoring its robust convergence capabilities.the proposed HYCHOPSO algorithm, paired with a PI controller for distributed hierarchical control, minimizes errors and enhances system reliability during dynamic MMG operations. Using HYCHOPSO framework, an accurate power sharing, voltage/frequency stability, seamless grid-to-island transition, and smooth resynchronization are achieved. This enhances the real application's reliability, flexibility, scalability and robustness.

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