Optimal dispatch strategy for building aggregators to fully utilize the energy flexibilities

Abstract

Well-managed demand-side flexibility can effectively alleviate the pressure on the reliability of the power system and the advanced development of smart grid technologies creates win-win opportunities for the power system operators and demand-side users. The
building sector, as one of the largest consumers of electricity, has great flexibility potential through smart load control and natural thermal mass storage. However, few studies have investigated the potential contribution of buildings in providing multiple flexibility services without sacrificing the occupants’ comforts. Another major hurdle to utilizing the building energy flexibility is that individual buildings usually cannot reach a sufficient size to bid the flexibility services in the electricity market. Therefore, this paper proposes an optimal dispatch strategy for building clusters using mixed-integer non-linear programming (MINLP) to aggregate and utilize full-scale energy flexibilities of variable controllable loads, the passive thermal mass storage and active electrical storage systems. The building cluster consisting of five commercial buildings is selected in the case study to test the proposed strategy and analyze
the practical relevance based on a real-life electricity market. Results show that the proposed dispatch strategy reduces the electricity costs of the building cluster by 11.6% from multiple revenue streams, including energy arbitrage, regulation service and operating reserve service. Active electrical storage systems can increase revenues by 2.3 times and the unlocked flexibility of building thermal and lighting loads can achieve 152 $ daily revenues. This study addresses the issue that the energy flexibility of individual buildings is too small to bid flexibility services, and the findings may stimulate the investment of the distributed storage system at the aggregated level, as the building aggregator is a promising business model in future flexibility markets.