article · Scientific Reports
Integrating solar photovoltaic generation and electric vehicle charging stations into existing distribution grids requires balancing power stability against commercial viability. A techno-economic framework addresses this balance by simultaneously reducing active power losses, mitigating voltage deviations, and maximising investor returns under local tariff structures. Applied to a realistic eleven-kilovolt radial distribution network representing the El-Shohada district in Egypt, the approach uses a metaheuristic Growth Optimization algorithm. This method determines the optimal locations and capacities for both solar units and charging stations over a twenty-four-hour timeframe. The model accounts for uncertain factors including varying electrical demand, fluctuations in solar irradiance, and electric vehicle charging patterns. Computational testing over repeated runs confirmed that the algorithm effectively balances technical grid stability with investor returns.
Expanding electric vehicle use and solar energy can strain local electricity networks if managed poorly. By identifying the best locations and capacities for infrastructure, this planning framework helps network operators protect grid reliability while ensuring that renewable energy and charging investments remain economically attractive and aligned with local tariff policies.
This research provides an optimization planning tool designed for power distribution utilities, grid operators, and renewable energy investors looking to integrate solar and vehicle charging infrastructure. Tested on a simulated model of an Egyptian municipal distribution network using local tariff data, the tool represents early-stage applied research that would require software productisation and live field trials before direct commercial deployment.
AI-generated from the published abstract. Always read the original work before citing.
This paper presents a comprehensive techno-economic framework for the optimal integration of distributed energy resources (DERs)-specifically Photovoltaic (PV) solar generation-and Electric Vehicle Charging Stations (EVCS) into modern electrical distribution grids. The methodology is applied to a realistic 25-bus, 11 kV radial distribution network modeled after the El-Shohada district in Menofia Governorate, Egypt. To balance inherently conflicting technical and financial objectives, a multi-objective penalty function is formulated. It simultaneously minimizes active power losses, mitigates voltage deviations, and maximizes investor profitability based on contemporary Egyptian energy tariff structures. The recently developed metaheuristic Growth Optimization (GO) algorithm is utilized to determine the optimal bus locations and capacities of these units over a 24-hour horizon, factoring in stochastic load profiles, solar irradiance, and EV charging behavior. Statistical validation based on 30 independent optimization runs demonstrates the high computational efficiency of the GO algorithm, yielding an optimal equilibrium that enhances grid reliability while providing a solid economic foundation.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1038/s41598-026-65285-y
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
