Project deployment strategies for community renewable energy: A dynamic multi-period planning approach

Abstract

Supplying the energy needs of a community through renewable energy sources is a vital aspect in developing sustainable communities. Many variations and uncertainties affect the development of a renewable-powered net-zero energy system. Community developers face challenges in making the investment decisions when planning community-level renewable energy (RE) projects. This study aims to address the need for reliable methods to assess RE project deployment strategies. To achieve this, the key decision variables were identified and dynamic project performance was assessed for a Canadian RE case study. A framework was developed using system dynamics for rating renewable energy project deployment scenarios. A fuzzy logic-based optimization process was used to identify the optimal system capacities and energy mix. The optimal energy supply mix was identified as follows for the case study: grid electricity- 56%, solar PV – 28%, biomass – 11%, and waste-to-energy– 5%. The results of the system dynamics based rating indicated that stage-by-stage construction that also accounts for community growth in facility capacity sizing provides the best outcomes for the community, with 42.8% of the community’s energy demand supplied with renewables. The developed model can help community developers to identify the best energy choices and investment strategies when planning community energy systems.