| Abstrakt: |
This paper presents a problem of simultaneous maximization of GenCo's (Generation Company) revenue and minimization of ISO's (Independent System Operator) purchase cost in interconnected power markets having different designs, namely capacity‐plus‐energy market and energy‐only market. Both these problems have solved by multi‐objective optimizers such as multi‐objective particle swarm optimization (MOPSO) and non‐dominated sorting genetic algorithm‐II (NSGA‐II) using market data available in the literature. MOPSO and NSGA‐II are meta‐heuristic optimization algorithms, which are used for several engineering applications to optimize multiple objectives simultaneously. The paper illustrates a comparative analysis of results with optimum allocation and pricing under different market conditions such as cost of recall, probability of recall and load forecasting (L. F.) error etc. Furthermore, main objective to emphasize on GenCo's total revenue maximization as well as ISO's purchase cost minimization instead of capacity cost only. Multi‐objective optimization techniques have used to optimize both objectives simultaneously. Existing literature does not discuss the simultaneous solution of these problems by multi‐objective optimization techniques, which makes this work novel. It has been observed that the capacity price, the maximum value of GenCo's revenue and the minimum value of ISO's purchase increases at a different rate, with increasing the probability of recall, cost of recall and L. F. error. GenCo's revenue and ISO's purchase cost have profoundly affected by the L. F. error, moderately affected by the probability of recall and very lowly affected by the cost of recall. [ABSTRACT FROM AUTHOR] |
