An integrated optimization of production planning and day ahead electricity market bidding for combined cycle natural gas power plants

Electricity is considered one of the most important inventions on earth. Although electricity generation sources have been diversified over time, natural gas is still one of the most important electricity generation sources in the world in this century. The situation in our country has evolved in a similar way and when we look at the electricity production resources, it is seen that natural gas has the largest share. Installation of natural gas power plants is cheap and fast. At the same time, its thermodynamic efficiency is higher when compared to other power plants. Electricity is not a type of energy that can be stored in large amounts by its nature. Therefore, it is important for the producers to make the right amount of production at the right time in natural gas power plants, as it is the case for all power plants. Within the scope of this study, a production planning model and a bidding model in the day ahead electricity market were developed for a producer with a combined natural gas power plant. These two models are solved in an integrated way, which is new in the literature, and they and present the producer with the results of the proposal decisions under the uncertainty of the market clearing price (MCP) in the day ahead electricity market. Due to the market structure, the day-ahead electricity market collects offer one day before real-time matches. In the study, a scenario-based model is proposed in order to take into account uncertainty in MCP. In the production model, it is aimed to minimize the production costs, the cost of switching the power plant to different production levels, and the maintenance, repair and labor costs. In the model, the operating conditions of the power plant from the previous day, secondary frequency control (SFC) obligations, generation capacities and the start-up situations where the power plant will start operating are taken into account. In the bid model, on the other hand, while maximizing the revenues is aimed, the number of bids, the status of the bids, MCPs and bid prices are taken into consideration. Scenarios were produced according to the expected values and errors, coming from a forecasting model in the scenario- based model presented to eliminate the MCP uncertainty in the model. In the numerical analysis part, scenario-based integrated solutions were obtained by running the model for a certain date, and the significant superiority of these solutions over the solutions found only with the expected values of MCP was shown.