2024/07/01 by Sourabh Dalvi, Dalvi, Sourabh, David Biagioni +7
Engineering · #Electric Power System Optimization #Energy Load and Power Forecasting #FOS: Electrical engineering #Optimal Power Flow Distribution #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2407.01715
openalex publication_date 2024/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
This paper proposes a methodology to solve generation expansion equilibrium problems by using a predictive model to represent the equilibrium in a simplified network constrained electricity market. The investment problem for each generation company (Genco) is a bi-level problem with the investment decision made in the upper level and market clearing condition in the lower level, which traditionally is represented as a Mathematical Program with Equilibrium Constraint (MPEC). The predictive model is trained for estimating the system-wide revenues for each technology type across energy, ancillary services and capacity markets given the amount of technology-specific installed capacity on the grid. The profit maximization investment problem for each Genco is solved using a global search algorithm, which uses the predictive model to evaluate the objective function. To solve for the strategic equilibrium, each Genco's problem is plugged into a diagonalization algorithm that is generally used in multi-leader, single-follower bi-level problems. The methodology presented here enables significant computational improvements while still capturing the desired market characteristics and dynamics of traditional equilibrium modeling approaches