Multi-objective economic environmental energy management microgrid using hybrid energy storage implementing and developed Manta Ray Foraging Optimization Algorithm

Dong, Yanle; Liu, Feichao; Liu, Xiang; Lou, Yunjiang; Ma, Yuanshe; Eghbalian, Nasrin

doi:10.1016/j.epsr.2022.108181

Cited by 22 publications

(7 citation statements)

References 36 publications

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“…To ensure the dependability and stability of a distribution network (DN) with many microgrids, various frameworks for operation management [73,74], market management [75,76], and security and risk management [77][78][79] (as shown in Figure 5) and algorithms for efficient energy [80][81][82][83][84] were also developed. Energy management is shown in Figure 6.…”

Section: Optimization and Management Of Microgrid Systemsmentioning

confidence: 99%

Exploring the Potential of Microgrids in the Effective Utilisation of Renewable Energy: A Comprehensive Analysis of Evolving Themes and Future Priorities Using Main Path Analysis

Pillai

Valsala

Raj

et al. 2023

Designs

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Microgrids are energy systems that can operate independently or in conjunction with the main electricity grid. Their purpose is to link different energy sources, enhance customer participation in energy markets, and improve energy system efficiency and flexibility. However, regulatory, technical, and financial obstacles hinder their deployment. To comprehend the current state of the field, this study utilized citation network analysis (CNA) methodology to examine over 1500 scholarly publications on microgrid research and development (R&D). The study employed modularity-based clustering analysis, which identified seven distinct research clusters, each related to a specific area of study. Cluster 1, focused on control strategies for microgrids, had the highest proportion of publications (23%) and the maximum citation link count (151), while Cluster 4, which examined microgrid stability, had the lowest proportion of papers (10%). On average, each publication within each cluster had four citation links. The citation network of microgrid research was partitioned using cluster analysis, which aided in identifying the main evolutionary paths of each subfield. This allowed for the precise tracing of their evolution, ultimately pinpointing emerging fronts and challenges. The identification of key pathways led to the discovery of significant studies and emerging patterns, highlighting research priorities in the field of microgrids. The study also revealed several research gaps and concerns, such as the need for further investigation into technical and economic feasibility, legislation, and standardization of microgrid technology. Overall, this study provides a comprehensive understanding of the evolution of microgrid research and identifies potential directions for future research.

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Section: Optimization and Management Of Microgrid Systemsmentioning

confidence: 99%

Exploring the Potential of Microgrids in the Effective Utilisation of Renewable Energy: A Comprehensive Analysis of Evolving Themes and Future Priorities Using Main Path Analysis

Pillai

Valsala

Raj

et al. 2023

Designs

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“…To ensure the optimal use of these resources and improve the homogeneity of the UAVs network, we introduced an equal load distribution to balance the exploitation of these resources. It is formulated mathematically in Equation (13).…”

Section: ) Load Distributionmentioning

confidence: 99%

“…Among existing meta-heuristics, the Manta Ray Foraging optimization algorithm is a recent Swarm Intelligence optimization algorithm developed by Zhao et al [2] in 2020. Due to its simplicity and easy implementation, it was widely applied for solving optimization problems such as electrical engineering [3], [4], image processing [5], [6], mathematics [7], geology [8], feature selection [9], system identification [10], energy [11]- [13], networking [14], PID control [15], and many others. Similar to other meta-heuristics, the MRFO algorithm suffers from premature and slow convergence and attempts to fall to local optima.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Improved Manta Ray Foraging Optimization With Tabu Search Algorithm for Solving the UAV Placement Problem in Smart Cities

et al. 2023

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The concept of smart cities is to enhance the life quality of residents and provide efficient services by integrating advanced information and communication technologies, autonomous robots, Internet of Things (IoT) devices, etc. Unmanned Aerial Vehicles (UAVs) are a class of autonomous flying mobile robots that bring a lot of benefits to smart cities due to their mobility, accessibility, autonomy, and many other advantages. Their integration allows for accomplishing hard and complex tasks that humans or other entities are not able to complete. In most applications, multiple connected UAVs are required to build a network under which missions are completed and tasks are shared. This network can be established by finding the optimal UAV placement that meets some requirements such as user coverage, UAV connectivity, energy, and load distribution. In this paper, we present a hybrid algorithm, called IMRFO-TS, based on the hybridization of Improved Manta Ray Foraging Optimization (IMRFO) with the Tabu Search (TS) algorithm for solving the UAV placement problem in a smart city. First, the tangential control strategy is incorporated into the original MRFO algorithm to enhance its convergence speed and explore the search space effectively. Second, The TS algorithm is hybridized with the IMRFO algorithm to increase the exploitation capability of IMRFO and improve the best solution (placement quality) obtained after each iteration. The performance of the proposed IMRFO-TS algorithm is validated using 52 benchmarks considering the fitness value, coverage, connectivity, energy consumption, and load distribution parameters. Compared to eight well-known optimization meta-heuristics such as the original MRFO, TS algorithm, Bat Algorithm (BA), Firefly Algorithm (FA), Grey Wolf Optimization (GWO), Sine Cosine Algorithm (SCA), Whale Optimization Algorithm (WOA), and Reptile Search Algorithm (RSA), the results of the experiments revealed the significant superiority of the proposed IMRFO-TS algorithm by obtaining promising solutions (optimal positions of UAVs) in the majority of the cases.

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“…P G = P L − P Bat − P FC (24) Regarding the power reference established by the energy management strategy, microgrid is used for sharing the battery energy. Still, several studies that advocated an economical EMS did not include the battery state of charge in the EMS.…”

Section: Fitness Functionmentioning

confidence: 99%

“…Dong et al. [24] controlled the microgrid system's cost‐effective environmental energy using the multiobjective optimization method, which utilizes a mix energy storage unit and the invention of the Manta Ray food optimization algorithm. A novel stochastic optimization algorithm is suggested for effective energy management (EM) of a microgrid.…”

Section: Introductionmentioning

confidence: 99%

A new optimal energy management strategy of microgrids using chaotic map‐based chameleon swarm algorithm

Ren,

Hou,

Jia

et al. 2023

IET Renewable Power Gen

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This study provides an optimal and efficient energy management strategy (EMS) for the cost-effective performance of a combined solar and green energy microgrid in both independent and grid-connected modes. A microgrid is formed by the system that includes a fuel cell (FC), a battery storage (BS), and a photovoltaic system (PV). Evidently, the unguaranteed features of the renewable energy and load electricity generate instability problems as well as economic ones, like operational expenses. To tackle these issues, a novel procedure is proposed that has been improved by a modified metaheuristic algorithm, called chaotic map-based chameleon Swarm Algorithm (CCSA). In this method, the simulation is based on a one-day planning perspective. The method aims to supply the power requirements of the load at the lowest possible cost under a constant DC bus voltage, protect the battery from overcharging and depletion, and improve the efficiency of the total system. To illustrate the suggested method's effectiveness, the simulation results of CCSA are compared with some studied methods in the literature, including GAMS, bald eagle search optimization algorithm (BEOA), original chameleon swarm algorithm (CSA), and grey wolf optimization algorithm (GWOA).

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Multi-objective economic environmental energy management microgrid using hybrid energy storage implementing and developed Manta Ray Foraging Optimization Algorithm

Cited by 22 publications

References 36 publications

Exploring the Potential of Microgrids in the Effective Utilisation of Renewable Energy: A Comprehensive Analysis of Evolving Themes and Future Priorities Using Main Path Analysis

Exploring the Potential of Microgrids in the Effective Utilisation of Renewable Energy: A Comprehensive Analysis of Evolving Themes and Future Priorities Using Main Path Analysis

A Hybrid Improved Manta Ray Foraging Optimization With Tabu Search Algorithm for Solving the UAV Placement Problem in Smart Cities

A new optimal energy management strategy of microgrids using chaotic map‐based chameleon swarm algorithm

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