A Bilevel Optimization Model for Energy Communities Considering Cost and Fairness

M. J. Alves, C. Henggeler Antunes, A. Soares, I. Soares

We propose a bilevel optimization model for an energy community where a central manager (leader) sets electricity prices, operates storage and procures energy in the market to maximize profit. The community (follower) first minimizes the maximum individual cost (fairness) and then total cost, ensuring no consumer pays more than in the first stage. Consumers schedule the operation of appliances, PV generation, storage and electric vehicles. We developed a hybrid approach with a genetic algorithm to explore the leader’s decisions with an exact solver to handle the lower-level lexicographic optimization. For every candidate solution, 3 LL MILP problems are solved using Gurobi. We also implemented a deterministic exact algorithm that requires solving a mixed-integer nonlinear program at each iteration, in addition to the lower-level problems. Computational results show that the hybrid approach achieves high-quality solutions, compared with upper bounds obtained with the exact algorithm.

Palabras clave: Bilevel Optimization; Energy

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