Singh Arvind R, Dey Bishwajit, Misra Srikant, Kumar Rangu Seshu, Bajaj Mohit, Blazek Vojtech
Department of Electrical Engineering, School of Physics and Electronic Engineering, Hanjiang Normal University, Shiyan, China.
Department of Electrical Engineering, Manipal University, Jaipur, Rajasthan, India.
iScience. 2025 Feb 27;28(3):112121. doi: 10.1016/j.isci.2025.112121. eCollection 2025 Mar 21.
Demand-side management (DSM) enhances distribution network efficiency by shifting or reducing loads, alleviating network stress. The Load Shifting Policy (LSP) reallocates flexible loads to low-price periods without altering total demand, while the Load Curtailing Policy (LCP) incentivizes consumers to reduce peak demand. This study introduces a hybrid DSM approach that combines LSP and LCP with a smart charging strategy for plug-in hybrid electric vehicles (PHEVs). Using the hybrid load shifting and curtailment policy (HLSCP), the microgrid (MG) load profile was optimized, reducing generation costs from 707¥ for the base load to 682¥ with HLSCP and 676¥ when incorporating smart PHEV charging. Emissions decreased correspondingly, from 1267kg to 1246kg. These results demonstrate the hybrid DSM's capacity to tackle economic and environmental challenges in power systems. The Differential Evolution (DE) optimization method further validated the robustness and efficiency of this cost-effective, sustainable microgrid management approach.
需求侧管理（DSM）通过转移或减少负荷来提高配电网效率，减轻网络压力。负荷转移策略（LSP）在不改变总需求的情况下将灵活负荷重新分配到低价时段，而负荷削减策略（LCP）激励消费者降低高峰需求。本研究引入了一种混合DSM方法，该方法将LSP和LCP与插电式混合动力汽车（PHEV）的智能充电策略相结合。使用混合负荷转移和削减策略（HLSCP），微电网（MG）的负荷曲线得到优化，发电成本从基本负荷的707元降至采用HLSCP时的682元，纳入智能PHEV充电时降至676元。排放量相应减少，从1267千克降至1246千克。这些结果证明了混合DSM应对电力系统经济和环境挑战的能力。差分进化（DE）优化方法进一步验证了这种具有成本效益的可持续微电网管理方法的稳健性和效率。
