A novel CSHO algorithm-based Profit Maximization of GENCOs considering PEVs and RES under Deregulated Environment

Abstract

In deregulated power markets, the Profit-Based Unit Commitment (PBUC) problem has emerged as a critical optimization problem for power Generation Companies (GENCOs) aiming to maximize profit while ensuring system reliability. The increasing penetration of Plug-in Electric Vehicles (PEVs) and Renewable Energy Sources (RESs) introduces additional uncertainty and complexity due to their stochastic and time-varying characteristics. This paper presents a novel approach to solving the PBUC problem in a deregulated environment by integrating the dynamic impacts of PEV charging/discharging behaviors and RES intermittency. A metaheuristic algorithm, the Chaotic Sea Horse Optimizer (CSHO), is employed to determine optimal generation schedules that maximize profit while accounting for market prices, operational constraints, spinning reserve requirements, and environmental considerations. The proposed CSHO framework effectively handles the nonlinear, non-convex nature of the PBUC problem and adapts to the uncertainties associated with RES output and PEV load profiles. Simulation studies on standard test systems such as the IEEE-39 bus system (10 generators and 24 hours) with an equivalent PEV and Wind farm. The proposed approach is tested with different test cases to analyze its performance. The outcomes such as UC schedule, Real power output of thermal, wind and PEV units, fuel cost, startup cost, revenue and profit of the proposed test system are numerically and graphically reported. The obtained simulated results are compared with other mathematical and intelligent computational approaches for proving the efficiency and performance of the proposed CSHO technique.