Hybrid Ideal Point and Pareto Optimization for Village Virtual Power Plant: A Multi-Objective Model for Cost and Emissions Optimization

Abstract

Rural areas, with their vast land and abundant resources, are ripe for the development of distributed energy systems. A two-stage dispatch optimization model has been proposed for a virtual power plant (VPP) in this paper, with the aim of maximizing operational revenue, minimizing costs for villagers, and reducing carbon emissions. This model leverages a benefit allocation strategy based on Pareto optimization, ensuring a balanced approach to conflicting objectives such as financial gain, risk management, and environmental impact. The effectiveness of various allocation strategies is evaluated using the Ideal Point method, which assesses options based on their proximity to an ideal outcome across three critical dimensions: risk, benefit, and carbon emission reduction. This method provides an assessment of each strategy's impact, ensuring that the chosen strategy is holistic. Case study results have shown that the proposed two-stage model, when combined with the Ideal Point-Pareto optimization method, can effectively utilize dispersed resources in rural areas to enhance operational efficiency and reduce carbon emissions from energy consumption processes. Additionally, with a 47% reduction in computational volume compared to traditional scalar and particle swarm optimization algorithms.