Multi-objective optimization framework for generation and transmission capacity expansion planning of power systems considering resiliency, equity, and sustainability, A

Abstract

To ensure the continued decarbonization of the electric grid while meeting increased demand, new utility-scale renewable energy resources need to be implemented in existing networks. The common considerations for developing conventional generating plants are not applicable to most renewable energy projects. The most ideal locations of renewable resources are not dictated by demand-centralized areas but by weather and atmospheric conditions. Therefore, more transmission capacity needs to be developed to integrate these resources properly. The development of these projects is materially and energy intensive. The frequency and severity of natural disasters is increasing as the atmosphere continues to warm. Power systems need to become more resilient to withstand these events. Socially vulnerable populations are at greater risk during long-duration outages that may occur due to natural disasters. A review of the literature is presented on power system resilience, equity, and sustainability using life cycle assessment. This thesis outlines the development of a novel multi-objective optimization framework for generation and transmission capacity expansion planning in which resiliency, equity, and sustainability are considered as well as cost. The framework is formulated as a risk-based security-constrained problem solved using Chebyshev goal programming. The proposed framework is applied to a representation of Colorado’s electric grid infrastructure considering wildfire scenarios. The results of the case study are provided and analyzed. The framework implemented multiple solar generation resources in socially vulnerable regions around Colorado. More socially vulnerable nodes were served their full energy demanded. Conclusions and recommendations for future work are presented.