Optimal Operation of Strategic Microgrids in the Day-Ahead Market in
Presence of Rivals
In this paper, a new approach is proposed for the optimal operation of
the strategic microgrids in the day-ahead market in the presence of
rivals. The method describes a bi-level multi-objective operation of
price maker participants (microgrids) that are going to maximize their
profit in the presence of rivals and minimize their emissions. The
upper-level problem in a bi-level mathematical optimization problem with
equilibrium constraints (MPEC) seeks to maximize the profit of price
maker participants, and the lower level maximizes the social welfare.
Karush-Kuhn-Tucker (KKT) conditions and duality theory are utilized to
convert the bi-level model to a mixed-integer linear programming model.
The Epsilon constraint method is used to solve the
bi-level-multi-objective problem in order to maximize the profit of the
linearized model and reduce the emissions of price maker participants.
The method generates some Pareto optimal solutions, and the fuzzy
decision-making method is used to find the best solution among Pareto
optimal solutions. To show the effect of the network on the studies, the
power transmission distribution factor (PTDF) method has been used. The
proposed method is tested on a 6-bus system in various scenarios. The
results show the good performance of the proposed method.