A multi-objective optimization framework for EV-integrated distribution grids using the hiking optimization algorithm DOI Creative Commons
Mahmoud Samiei Moghaddam,

Masoumeh Azadikhouy,

Nasrin Salehi Dehno

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 17, 2025

Electric vehicle (EV) integration into distribution grids introduces significant challenges in maintaining grid stability, minimizing operational costs, and ensuring overall system efficiency. In response to these challenges, a novel multi-objective optimization model is proposed that concurrently minimizes energy losses, procurement load shedding, voltage deviations over 24-hour period, while also accounting for the costs associated with EV battery management. The optimized using Hiking Optimization Algorithm (HOA), which leverages an adaptive search mechanism based on Tobler's Function. This enhances exploration of solution space effectively avoids local optima, resulting superior performance compared conventional methods. Simulation results 33-bus demonstrated that, integration, were reduced by 19.3%, losses decreased 59.7%, shedding was minimized 75.4%, improved 43.5% relative scenario without EVs. Additionally, eliminated photovoltaic (PV) curtailment, thereby optimal utilization renewable resources. When benchmarked against alternative techniques, HOA achieved 4.4% lower total cost than Komodo Mlipir (KMA) 24.5% Particle Swarm (PSO). These clearly demonstrate model's effectiveness enhancing optimizing improving approach offers scalable reliable modern management context increasing penetration integration.

Язык: Английский

Analysis of Techno–Economic and Social Impacts of Electric Vehicle Charging Ecosystem in the Distribution Network Integrated with Solar DG and DSTATCOM DOI Creative Commons

Ramesh Bonela,

Sriparna Roy Ghatak, Sarat Chandra Swain

и другие.

Energies, Год журнала: 2025, Номер 18(2), С. 363 - 363

Опубликована: Янв. 16, 2025

In this work, a comprehensive planning framework for an electric vehicle charging ecosystem (EVCE) is developed, incorporating solar distributed generation (DG) and distribution static compensator (DSTATCOM), to assess their long-term techno–economic environmental impacts. The optimal locations capacities of the EVCE, DG, DSTATCOM are determined using improved particle swarm optimization algorithm based on success rate technique. study aims maximize technical, financial, social benefits while ensuring that all security constraints met. To financial viability proposed model over 10-year horizon, detailed economic analysis comprising installation cost, operation, maintenance cost conducted. make more realistic, various practical parameters, such as inflation interest rate, incorporated during analysis. Additionally, highlight societal approach, quantifies carbon emissions corresponding emissions. tested both 33-bus network 108-bus Indian network. Various scenarios explored, with different configurations solar-based DSTATCOM, assist power system planners in selecting most suitable strategy.

Язык: Английский

Процитировано

0
Optimization Research on a Novel Community Integrated Energy System Based on Solar Energy Utilization and Energy Storage DOI Creative Commons
Xunwen Zhao, Hailin Mu, Nan Li

и другие.

Energies, Год журнала: 2025, Номер 18(5), С. 1151 - 1151

Опубликована: Фев. 26, 2025

Integrated energy systems (IESs) are essential for enabling the transition in communities and reducing CO2 emissions. This paper proposes a novel IES that combines photovoltaic (PV) solar thermal with coordinated electrical storage to meet demands of residential communities. The system also incorporates hydrogen production fuel cell vehicles. A dual-objective optimization model was developed, minimizing both economic costs system’s performance evaluated using data from case study Dalian, which showed successfully reduced annual total cost emissions compared conventional systems. key findings PV electrolysis provides environmental advantages. integration offers higher efficiency, while supplies enhance coordination. Additionally, carbon trading prices effectively reduce emissions, but excessively high do not always lead better emission outcomes. introduces comprehensive, multi-energy approach optimizing supply, contributing insights field sustainable

Язык: Английский

Процитировано

0
A multi-objective optimization framework for EV-integrated distribution grids using the hiking optimization algorithm DOI Creative Commons
Mahmoud Samiei Moghaddam,

Masoumeh Azadikhouy,

Nasrin Salehi Dehno

и другие.

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Апрель 17, 2025

Electric vehicle (EV) integration into distribution grids introduces significant challenges in maintaining grid stability, minimizing operational costs, and ensuring overall system efficiency. In response to these challenges, a novel multi-objective optimization model is proposed that concurrently minimizes energy losses, procurement load shedding, voltage deviations over 24-hour period, while also accounting for the costs associated with EV battery management. The optimized using Hiking Optimization Algorithm (HOA), which leverages an adaptive search mechanism based on Tobler's Function. This enhances exploration of solution space effectively avoids local optima, resulting superior performance compared conventional methods. Simulation results 33-bus demonstrated that, integration, were reduced by 19.3%, losses decreased 59.7%, shedding was minimized 75.4%, improved 43.5% relative scenario without EVs. Additionally, eliminated photovoltaic (PV) curtailment, thereby optimal utilization renewable resources. When benchmarked against alternative techniques, HOA achieved 4.4% lower total cost than Komodo Mlipir (KMA) 24.5% Particle Swarm (PSO). These clearly demonstrate model's effectiveness enhancing optimizing improving approach offers scalable reliable modern management context increasing penetration integration.

Язык: Английский

Процитировано

0