Optimal strategy for bidding in deregulated-structure of electricity market: A competitive model

Profit maximization for electricity companies strongly depends on the tender strategies. To trade electricity at a high price and make the most of profits, electricity companies require suitable and optimal price offer models that take into account the operational constraints of electricity and price uncertainty in the market. Nowadays, the electricity industry is mostly inclined towards creating a competitive structure for increasing its productivity as well as technical and managerial efficiency. Here, the optimal distribution of the auction offers by the companies in the fully competitive electricity market is converted into an optimization problem and solved by the developed gray wolf optimizer (GWO) algorithm based on chaos theory. In a competitive electricity market, to increase the profit of the players in the market, the auction offers should be properly selected, because each player intends to increase its own profit. Of course, each of the players can change their level of offers without disrupting the customers' welfare. This problem is even more important for large manufacturing companies and large loads because a considerable share of the market is allocated to them. Results of this method are compared with those of other evolutionary methods and indicate the suitable efficiency of the proposed method.