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Project deployment strategies for community renewable energy: A dynamic multi-period planning approach
Renewable Energy ( IF 9.0 ) Pub Date : 2020-06-01 , DOI: 10.1016/j.renene.2020.01.045
Hirushie Karunathilake , Kasun Hewage , Tharindu Prabatha , Rajeev Ruparathna , Rehan Sadiq

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.

中文翻译:

社区可再生能源项目部署策略:动态多期规划方法

摘要 通过可再生能源满足社区的能源需求是发展可持续社区的一个重要方面。许多变化和不确定性会影响可再生能源净零能源系统的发展。在规划社区级可再生能源 (RE) 项目时,社区开发商在做出投资决策时面临挑战。本研究旨在解决对评估可再生能源项目部署策略的可靠方法的需求。为实现这一目标,确定了关键决策变量,并对加拿大可再生能源案例研究的动态项目绩效进行了评估。使用系统动力学开发了一个框架,用于对可再生能源项目部署场景进行评级。基于模糊逻辑的优化过程用于确定最佳系统容量和能源组合。案例研究的最佳能源供应组合确定如下:电网电力 - 56%,太阳能光伏 - 28%,生物质 - 11%,和废物转化为能源 - 5%。基于系统动力学的评级结果表明,在设施容量规模方面也考虑到社区增长的分阶段建设为社区提供了最好的结果,社区能源需求的 42.8% 由可再生能源提供。开发的模型可以帮助社区开发商在规划社区能源系统时确定最佳能源选择和投资策略。基于系统动力学的评级结果表明,在设施容量规模方面也考虑到社区增长的分阶段建设为社区提供了最好的结果,社区能源需求的 42.8% 由可再生能源提供。开发的模型可以帮助社区开发商在规划社区能源系统时确定最佳能源选择和投资策略。基于系统动力学的评级结果表明,在设施容量规模方面也考虑到社区增长的分阶段建设为社区提供了最好的结果,社区能源需求的 42.8% 由可再生能源提供。开发的模型可以帮助社区开发商在规划社区能源系统时确定最佳能源选择和投资策略。
更新日期:2020-06-01
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