Chance-Constrained Optimization for VPPs With Base Stations Considering Diverse Communication Rate Requirements
Chao Guo, Chengjin Ye, Yi Ding, Jing Li, Jia-Dong Dai, Xuanyi Zhou
Abstract
5G Base Stations (BSs) consume a large amount of electricity, requiring predominantly green power, which brings huge pressure on their electricity costs. To reduce energy costs and carbon emissions, aggregating 5G BSs (Macro BS and Micro BS), and distributed renewable energy into virtual power plants (VPPs) to participate in market transactions has become a trend. However, the operation of VPPs faces challenges: the uncertainty of renewable energy output and the unclear regulation mechanism of BSs. Consequently, this paper focuses on developing an optimal scheduling strategy for VPPs, considering the schedulability of BSs and the uncertainty of internal renewable energy. Firstly, the flexibility of BSs with 4G and 5G modules is investigated, particularly in terms of transceivers and backup energy storage. The communication rates of BSs are modeled to evaluate the impact of active transceiver numbers on user experience. A dynamic time-domain model of backup energy storage capacity considering communication load is proposed. The impact of user mobility and overlapping coverage areas of BSs on communication rates is considered to be more in line with real-world scenarios. Subsequently, an optimization model is developed for VPPs to maximize the profit of engaging BSs in the day-ahead market transaction, considering diverse communication rate requirements. The optimization model determines the schedule of transceivers, backup energy storage, and other resources. Then, to control the operational risks associated with the uncertainty of internal distributed renewable energy outputs, the chance constraint is introduced. Furthermore, the Taylor expansion-based algorithm is applied to coordinately solve the VPP dispatching problem. Numerical simulations are carried out to validate the effectiveness of the proposed models, which achieve a 5.4% increase in the proportion of internal renewable energy consumption and a 18.72% increase in economic benefits.