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Summary: Renewable energy such as wind power plays an important role in power generation. Large amount of renewable energy can allow these producers to change the market price and be as a price maker in the market. Thus, we propose an optimal bidding strategy in the day‐ahead market for the hybrid power plant that participates as a price maker in the day‐ahead market and as a price taker in the balancing market. Hybrid power plant is composed of wind power producer, battery storage and demand response. The uncertainty of day‐ahead market price is modeled through Robust Optimization. In case studies, bidding strategy of hybrid power plant as a price maker and price taker configuration is presented. Then, joint operation of hybrid power plant is compared to disjoint operation and the effect of participating in market as coordinated unit on total profit is investigated. Moreover, the changes in profit according to risk level are determined and finally, offering curves are obtained by dividing the confidence bounds of day‐ahead market price to some subintervals. The simulation is done based on Nord Pool Market and the results validate hybrid power plant can behave as a price maker in the day‐ahead market and the profit of all units increases in joint operation. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a new efficient algorithm inspired by Franklin's and Coulomb's laws theory that is referred to as CFA algorithm, for finding the global solutions of optimal economic load dispatch problems in power systems. CFA is based on the impact of electrically charged particles on each other due to electrical attraction and repulsion forces. The effectiveness of the CFA in different terms is tested on basic benchmark problems. Then, the quality of the CFA to achieve accurate results in different aspects is examined and proven on economic load dispatch problems including 4 different size cases, 6, 10, 15, and 110‐unit test systems. Finally, the results are compared with other inspired algorithms as well as results reported in the literature. The simulation results provide evidence for the well‐organized and efficient performance of the CFA algorithm in solving great diversity of nonlinear optimization problems. [ABSTRACT FROM AUTHOR]