A probabilistic spot market design for reducing real-time balancing costs

Balancing services are used for maintaining the continuous balance between generation and load in the system and keep the frequency stable on its nominal value. The demand for balancing services is increasing with the growing penetration of wind generation into the electricity industry. It is clearly seen that a major challenge of the coming environment for the electricity market is reducing the procurement cost of balancing services. This paper presents a probabilistic spot market model based on integration of day-ahead spot market and the real-time balancing market which aims to trade off preventive actions in the day-ahead spot market with corrective actions in the real-time balancing market. The proposed model is formulated as a bi-level optimization problem. To solve it, the inner optimization problem (reflecting the real-time balancing market) was substituted by its equivalent Karush-Kuhn-Tucker optimality conditions. Conventional spot market model is used as a benchmark in this study. The proposed and conventional spot market designs are applied to modified Nordic 32-bus example system. Comparison of results point out the benefits of the proposed approach over the traditional model.