Optimal scheduling of active and reactive power considering distributed renewable power generation in electricity market

Abstract The growing penetration of renewable energy sources (RES) in power markets poses several operational issues, such as price volatility, transmission congestion, and voltage instability. In response to these issues, this work suggests an optimal power flow (OPF) method that considers renewable energy generation (REG) and demand response strategies to reduce system cost and enhance voltage stability. The IEEE-30 bus system is utilized as the test case, and the optimization problem is addressed using the Whale Optimization Algorithm (WOA). The outcomes show that incorporating an electricity market lowers generation costs from 798.86 $/h to 707.35 $/h with an 11.5% decrease, and system losses from 8.63 MW to 8.16 MW. Further, the inclusion of REG in the market-based model lowers the operational cost to 706.96 $/h, and system losses to 7.21 MW, an overall improvement of 16.5%. The total voltage deviation (VD) which is an important stability index, decreases from 0.1060 pu to 0.0803 pu, enhancing voltage stability by 24.2%. In addition, a multi-objective optimization approach is implemented that balances minimizing the cost and the reduction of voltage deviation. Convergence behavior reveals that WOA can find a good solution at 300 iterations and is faster and more accurate than traditional algorithms. The research proves that optimal scheduling of active and reactive power and effective participation of the demand side can improve economic efficiency and voltage stability. These results set WOA as a strong and effective method for power system performance optimization in deregulated electricity markets, enabling large-scale renewable integration while maintaining system reliability and economic viability.