Day-ahead bidding strategies of a distribution market operator in a coupled local and central market

Abstract

Smart energy systems lead to integrating more distributed energy resources and this creates the need for introducing a local electricity market within the distribution system. The distribution market operator is the distribution level equivalent of the market operator, which is responsible for managing the local electricity market and scheduling power transfers to achieve the optimal operation of distributed energy resources in the distribution system. The objective of this paper is twofold. The first objective is to look deeper into the distribution market operator and its role and interactions with other stakeholders in the so-called coupled local and central (national) market model. The second objective is to investigate quantitatively the distribution market operator's bidding strategies in the central day-ahead market and the effect of different bidding strategies on the performance of the local market. For this, distribution market operators dealing with uncertainties within the central day-ahead market prices is studied through two main approaches; the scenario-based approach to minimize the expected cost and the min-max regret as a robust risk-averse approach. The results from these two approaches are compared with the deterministic and perfect knowledge approaches as limits of the worst and best performances of the distribution market operator, respectively. Results show that the approach that the distribution market operator will choose is a trade-off between being risk-averse, having a higher amount of energy generated from distributed energy resources, and finally a lower system's cost.