Multi‐objective robust transmission expansion planning using information‐gap decision theory and augmented ɛ‐constraint method

摘要: This study presents a novel tractable mixed-integer linear programming model for multiyear transmission expansion planning (TEP) problem coping with the uncertain capital costs and electricity demands using information-gap decision theory (IGDT). As compete to occupy permissible uncertainty budget, proposed IGDT-based TEP (IGDT-TEP) framework employs augmented e-constraint method solve multi-objective optimisation maximising robust regions against variables (i.e. demands) centred on their forecasted values. enables system's planner control immunisation level of optimal plan regarding enforced uncertainties certain budget. Also, Latin hypercube sampling-based post-optimisation procedure is introduced evaluate robustness an obtained from IGDT-TEP framework. Simulation results demonstrate effectiveness handle nature demands.