Two-Stage Coordinate Optimal Scheduling of Seawater Pumped Storage in Active Distribution Networks

Abstract

The percentage of penetration in renewable energy generation (REG) in distribution networks has dramatically increased. Variable speed seawater pumped storage, which has a large power controllable range and flexible modes of operation, is an important tool to be applied in distribution networks to realize peak shaving and valley filling, and to mitigate the negative effects of REG. This paper presents a two-stage coordinated optimal scheduling model for the day-ahead and real-time operation of active distribution networks containing seawater pumped storage, REG, and flexible loads. In the model, seawater pumped storage and flexible loads are dispatched in the first day-ahead stage based on short-term forecast information of REG and load demands to minimize total operational costs. Then in the second real-time stage, the operation schedule of seawater pumped storage is adjusted to mitigate the negative effects of forecast errors of REG on the operation of active distribution networks. Network nodes power quality is improved and power loss is reduced. Applying the model, disadvantages of low accuracy short-term forecast are minimized whereas advantages of high accuracy ultra-short term forecast are fully taken. This model is tested using a modified Institute of Electrical and Electronics Engineers 33-bus system. Numerical results demonstrate the effectiveness of the proposed approach.

A Multi-Market-Driven Approach to Energy Scheduling of Smart Microgrids in Distribution Networks

“…There is a wide range of research covering the issue of energy scheduling for MGs in distribution networks. For economic energy dispatching, the vital parts mainly include the design of energy management system and the cost model, and various optimization methods and models have been already applied [12][13][14]. In previous studies, the multi-agent approach and various game theories have been widely applied to the decision-making of energy scheduling.…”