使用时间定价框架下的分布式能源资源共同优化

Krisha Maharjan, Jian Zhang, Heejin Cho, Yang Chen
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摘要

分布式能源系统(DES)因其在效率和环境方面的优势而被视为一种前景广阔的解决方案。然而,尽管分布式能源资源和技术发展迅速,但与传统发电相比,分布式能源发电的份额仍然很小。使用时间定价(TOU)是鼓励分布式能源系统普及的重要激励策略。本文提出了一种考虑到使用时间定价影响的多目标优化方法,以确定分布式能源系统的最佳配置和容量,该系统涉及不同的技术,包括太阳能光伏(PV)、太阳能集热器(STC)、热电联产系统(CHP)和集成储能(ES)。分布式能源系统旨在部分或全部满足商业建筑(大型酒店和中型写字楼)的电力和热力负荷。所提出的多目标优化方法可用于配置分布式能源技术的最佳组合以及系统容量,以降低系统在不同地点的成本和对环境的影响。结果表明,基于现有的分时定价结构,所提出的优化方法可以实现系统成本与环境影响之间的权衡。
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CO-OPTIMIZATION OF DISTRIBUTED ENERGY RESOURCES UNDER TIME-OF-USE PRICING FRAME
Distributed energy systems (DES) have been considered as a promising solution due to the benefits on efficiency and environment sides. However, despite the rapid development of distributed energy resources and technologies, the share of the distributed energy generation is still small in comparison to that of traditional generation. Time-of-use (TOU) pricing can be an important incentive strategy to encourage the penetration of distributed energy systems. In this paper, a multi-objective optimization considering the time-of-use pricing impacts is proposed to determine the optimal configuration and capacity of distributed energy system involving different technologies including solar photovoltaic (PV), solar thermal collector (STC), combined heating and power system (CHP), and integrated energy storage (ES). The distributed energy system is designed to satisfy the electric and thermal load of commercial buildings (large hotel and medium office) partially or entirely. The proposed multi-objective optimization is utilized to configurate the optimal combination of distributed energy technologies as well as the system capacity to reduce both the cost and environment impact of the system in different locations. Results show that the proposed optimization method can achieve a trade-off between system cost and environment impact based on the existing time-of-use pricing structure.
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