Optimizing dynamic economic dispatch through an enhanced Cheetah-inspired algorithm for integrated renewable energy and demand-side management

Abstract

This study presents the Enhanced Cheetah Optimizer Algorithm (ECOA) designed to tackle the intricate real-world challenges of dynamic economic dispatch (DED). These complexities encompass demand-side management (DSM), integration of non-conventional energy sources, and the utilization of pumped-storage hydroelectric units. Acknowledging the variability of solar and wind energy sources and the existence of a pumped-storage hydroelectric system, this study integrates a solar-wind-thermal energy system. The DSM program not only enhances power grid security but also lowers operational costs. The research addresses the DED problem with and without DSM implementation to analyze its impact. Demonstrating effectiveness on two test systems, the suggested method's efficacy is showcased. The recommended method's simulation results have been compared to those obtained using Cheetah Optimizer Algorithm (COA) and Grey Wolf Optimizer. The optimization results indicate that, for both the 10-unit and 20-unit systems, the proposed ECOA algorithm achieves savings of 0.24% and 0.43%, respectively, in operation costs when Dynamic Economic Dispatch is conducted with Demand-Side Management (DSM). This underscores the advantageous capability of DSM in minimizing costs and enhancing the economic efficiency of the power systems. Our ECOA has greater adaptability and reliability, making it a promising solution for addressing multi-objective energy management difficulties within microgrids, particularly when demand response mechanisms are incorporated. Furthermore, the suggested ECOA has the ability to elucidate the multi-objective dynamic optimal power flow problem in IEEE standard test systems, particularly when electric vehicles and renewable energy sources are integrated.

Multi-stage framework for optimal incorporating of inverter based distributed generator into distribution networks

“… 3 , 12 , 17 while minimum cost is utilized in refs. 13 , 15 , 16 . When all resources have the same generation cost function, then the minimum cost and minimum losses provide similar results.…”

“…DG size and allocation in distribution networks have been investigated in several studies to optimize one or more system variables, such as maximizing the hosting capacity and minimizing the total energy losses 3 , minimizing the real power losses and enhancing the VSI 9 , diminishing both the power losses and the voltage deviation 10 , maximizing DG hosting capacity 11 , minimizing active power losses, reactive power losses, voltage deviation, and maximizing the VSI 12 , minimizing costs and enhancing the economic efficiency of the power systems 13 , 14 , and minimize fuel cost, real power losses, emission cost, and voltage deviations 15 , 16 . Also, several types of DGs (wind, PV, and fuel cell) have been optimized for loss reduction and voltage profile enhancement in 9 , energy losses and emission reduction in 17 , and minimizing the injected power into the grid in 18 .…”

“… Year Refs. Optimization technique Objective Active power support of DG Reactive power support of DG Load variation Nonlinear load Harmonics of DG Description 2023 3 MOAGWO HC and APL ✓ – ✓ – – MOAGWO has been utilized to maximize the hosting capacity and minimize the total energy losses 2018 9 NN-ABC APL and VSI ✓ – – – – The ABC has been exploited to determine the optimal sizing of fuel cells to minimizes the real power losses and improves the voltage stability index 2021 10 GA APL and VD ✓ – – – – The position and size of DG unit issue has been solved by considering using genetic algorithm GA for reducing power losses and voltage deviation 2021 12 SPBO APL, TVD, and VSI ✓ – – – – SPBO has been suggested to solve the multi-objective DG allocation problem considering the power loss, the total voltage deviation, and the voltage stability index 2024 13 ECOA Cost ✓ ...…”

Multi-objective energy management in a renewable and EV-integrated microgrid using an iterative map-based self-adaptive crystal structure algorithm

“…For instance, fuel cells, which generate electricity from hydrogen and oxygen, primarily emit water vapor. However, during the reformation of natural gas or other fuels, they may produce some and emissions 113 , 114 . Despite their higher initial costs, fuel cells are generally more efficient and have lower emissions compared to microturbines.…”