5G-Enabled Forecasting and Scheduling for Smart Grid-Based Operational Control of Renewable Power Systems

Abstract

The growing share of renewables has introduced new operational problems into modern smart grids because the electricity from renewable energy sources is intermittent, the load demands are variable and the requirement for real-time control has arisen. In this paper, a framework for smart grid forecasting and scheduling for the operational control of renewable power systems, which can be implemented using 5G is presented. The proposed framework involves constructing a coordinated energy management framework that combines load demand, PV energy generation, wind energy generation, BESS, demand response, grid power exchange, and 5G communication parameters. A 500-kW photovoltaic system, 300 kW wind generation system, 1000 kWh battery energy storage system and 10 5G base stations were used in simulation for 24 hours. The results indicate that the overall operating cost savings in the proposed full framework were about $520 as compared with the conventional case, resulting in almost 28.8% cost savings. The renewable utilization ratio was around 100% in all the operating scenarios, demonstrating good utilization of available solar and wind power generation. With the proposed framework, the max grid import was lowered from approximately 355 kW in the conventional case to almost 310 kW. The SOC level of the battery was kept in the proper operating window (20%-90%), enabling peak-load management and balancing of renewable energy. Moreover, under normal operations, the proposed 5G-enabled control ensured a communication delay of between 2 and 7 ms, a range that falls within the 10 ms limit allowed for the communication delay. The impact of uncertainty in communication conditions on operational reliability is shown as communication delay rises to almost 13.5 ms under the stress-test case. In general, the findings show that the proposed framework for 5G-based forecasting and scheduling can effectively minimize operating cost, promote the utilization of renewable resources, enhance grid support, and ensure reliable communication-aware control in renewable-rich smart grids.