Скачать или смотреть TECHNO-ECONOMIC OPTIMIZATION-EV CHARGING LOADS-WIND TURBINE-15-BUS RDS-JAYA ALGORITHM

DESIGN DETAILS
The rapid proliferation of electric vehicles (EVs) has introduced significant operational challenges in distribution networks (DNs), such as increased peak demand, voltage instability, and potential grid congestion. To address these issues, this study presents an optimal operational strategy for electric vehicle charging stations (EVCSs) integrated with renewable energy resources (RERs), specifically wind energy systems, within distribution networks.

A two-stage multi-objective optimization framework is developed to ensure secure, reliable, and economically efficient DN operation under high penetration levels of EVCSs and RERs.

In Stage 1, the power demand profiles of EVCSs equipped with Level 1 (AC), Level 2 (AC), and Level 3 (DC) charging units are determined to maintain voltage stability and network security while effectively meeting EV charging requirements.

In Stage 2, wind turbine (WT) systems are optimally integrated into the network to maximize economic benefits and minimize power purchases from the main grid without compromising reliability.
The proposed framework utilizes the Jaya algorithm to minimize operational costs and coordinate EV charging loads with renewable energy generation. The optimization considers multiple objectives, including power loss reduction, voltage deviation minimization, peak demand management, and cost optimization. Stochastic variations in wind speed and EV charging demand are modeled using probabilistic forecasting techniques to accurately represent real-world uncertainties.

The framework is validated on the 15-bus radial distribution system under varying penetration levels of EVs and renewable energy sources, demonstrating notable improvements in techno-economic performance, grid reliability, and voltage profile stability.

OBJECTIVE FUNCTIONS
This MATLAB design formulates a two-stage optimization problem.

Stage 1 focuses on determining the optimal operation of EVCSs through a multi-objective function that includes the power loss index, voltage deviation index, voltage stability index, and grid power purchase cost index

Stage 2 determines the optimal operation of solar PV and wind turbine (WT) systems based on the network configuration obtained from Stage 1.

This stage extends the initial formulation by introducing two additional objectives representing the economic benefits for WT owners through the sale of renewable energy to the distribution network at predefined contract rates.
Each component of the multi-objective function is mathematically defined as follows:
Power loss index(PLSI)=(Power loss with change in network)/(Power loss with basecase)
Voltage deviation index(VDI)=(VD with change in network)/(VD with basecase)
Voltage stability index(VSI)=(VS with change in network)/(VS with basecase)
Power purchased from grid index(PPGI)=(Power purchase from the grid with change in network)/(Power purchase from the grid with basecase)

REFERENCES
Reference Paper-1: Optimal operation of electric vehicle charging stations with solar and wind energy systems in distribution network using JAYA algorithm
Author’s Name: Kushal Manohar Jagtap, Farhad Ilahi Bakhsh, Ramya Kuppusamy, Yuvaraja Teekaraman
Source: Elsevier
Year:2025

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