Hybrid architecture for intelligent bidding in hourly-based electricity market

摘要

The paper presents a hybrid structure, that develops the foremost bidding strategies for an electrical power generating company (GenCo) for an hourly-based electricity market (EM). For a GenCo, to develop the most desirable bidding technique, an outcome of a two-level optimisation process is used. The two-levels of optimisation are as follows: at the primary level, the goal of GenCo is to strategically bid for maximum benefit, and the independent system operator (ISO) analyses the market clearing price (MCP) at the secondary level to help measure the quantity of energy dispatched for each GenCo to optimise global welfare. In this paper, we trained a neural network (NN) by using whale optimisation algorithm (WOA) to achieve a high hourly profit for GenCo. The efficacy of the proposed hybrid structure is decided via numerous case research on the benchmark IEEE 14-bus test system in an hourly-based market with a dynamically converting demand profile. For the GenCo, block bidding supply function is taken and optimal bidding technique is explored with changing demand. Strategic bidding is a method discovered inside an oligopoly EM that has many insinuations on the layout and policy-making of the mechanism.