Hierarchical multi-objective design of regional integrated energy system under heterogeneous low-carbon policies

Abstract

Fossil-to-renewable energy system transition is an inevitable future trend considering carbon dioxide emissions mitigation burdens. However, huge investment costs and insufficient policy support are still the two main barriers to further expand renewable energy penetration. To transcend these barriers, from the perspective of both policy makers and energy suppliers, this study simultaneously integrates low-carbon policy formulations and regional integrated energy system (IES) reshaping to achieve an affordable decarbonization pathways. Mixed Integer Quadratically-Constrained Programs (MIQCP) models are constructed, and hierarchical multi-objective optimization is applied to quantify local government's decision-making costs and energy suppliers' system transition costs. A new rural community in Dalian (China) is taken as a case study to capture the relationship among energy structure adjustment, energy system reshaping, and renewable subsidy and carbon tax adjustment under different CO2 emission reduction regulations. The result shows that under the same CO2 emission reduction rate, portfolio policies can benefit both the policy maker and the energy supplier by balancing the local government revenue and expenditure, and reducing the annual total costs of IES. In addition, via IESs optimization, a higher renewable energy penetration rate could be obtained and the energy supplier could achieve a competitive cost within 40% CO2 emission reduction targets.