A Stochastic Multi-Objective Planning Framework for Distributed Energy Resources as an Alternative to Transmission Expansion

Building new transmission lines has grown increasingly difficult in recent years due to ever-increasing environmental concerns and rising construction costs. An alternative would involve investing in distributed energy resources (DERs) which can reduce the need for new transmission lines by reducing the load. This study presents a new stochastic multi-objective planning model for DERs as a replacement for transmission network reinforcement. The proposed model aims to minimize the investment costs of DERs and the congestion costs of transmission networks while maximizing the absorption of private investments. The uncertainties in the future electric loads and generators' offer prices are captured by scenarios. The non-dominated sorting genetic algorithm II (NSGA-II) is utilized for solving the multi-objective optimization problem. Subsequently, the fuzzy decision-making method is applied to non-dominated solutions to obtain the final optimal expansion plan. Finally, the effectiveness and applicability of the proposed planning model are investigated using the IEEE 24-bus test system, offering insights from both the perspectives of system operators and private investors.