The computation of the air conditioning loads life loss and its application to demand response

IF 1.6 Q4 ENERGY & FUELS IET Energy Systems Integration Pub Date : 2023-10-24 DOI:10.1049/esi2.12121
Zhiwei Li, Wenhao Hu, Zhihan Cong, Shuqiang Zhao
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Abstract

Air conditioning loads (ACLs) represent an increasing proportion of power system loads, offering significant potential for optimised scheduling and active participation in demand response (DR) programs. While many studies have focused on ON/OFF control schemes that satisfy system requirements, few have addressed quantifying the life loss of ACLs from the user perspective. To address this gap, a quantitative model of ACL life loss is established and an optimal scheduling model is developed for ACLs participating in DR that incorporates the cost of life loss. The relationship between life loss and refrigeration power is a complex non-linear high-order fractional function that cannot be solved by commercial solvers. Therefore, a bi-objective multi-weight optimisation algorithm is proposed with a complex non-linear fraction based on the Dinkelbach algorithm and its feasibility through mathematical examples is verified. Finally, a numerical example based on the IEEE 39-bus test system is provided to demonstrate the feasibility of the model and the effectiveness of the proposed solution method.

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空调负荷寿命损失的计算及其在需求响应中的应用
空调负荷(ACL)在电力系统负荷中所占比例越来越大,为优化调度和积极参与需求响应(DR)计划提供了巨大潜力。虽然许多研究都侧重于满足系统要求的开/关控制方案,但很少有研究从用户角度量化空调负荷的寿命损失。为了弥补这一不足,我们建立了 ACL 生命损失的定量模型,并为参与 DR 的 ACL 开发了一个包含生命损失成本的优化调度模型。生命损失与制冷功率之间的关系是一个复杂的非线性高阶分数函数,商业求解器无法解决。因此,在 Dinkelbach 算法的基础上,提出了一种具有复杂非线性分数的双目标多权重优化算法,并通过数学实例验证了该算法的可行性。最后,提供了一个基于 IEEE 39 总线测试系统的数值示例,以证明模型的可行性和所提求解方法的有效性。
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来源期刊
IET Energy Systems Integration
IET Energy Systems Integration Engineering-Engineering (miscellaneous)
CiteScore
5.90
自引率
8.30%
发文量
29
审稿时长
11 weeks
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