As a key component of an integrated energy system (IES), energy storage can effectively alleviate the problem of the times between energy production and consumption. Exploiting the benefits of energy storage can improve the competitiveness of multi-energy systems. This paper proposes a method for day-ahead operation optimization of a building-level integrated energy system (BIES) considering additional potential benefits of energy storage. Based on the characteristics of peak-shaving and valley-filling of energy storage, and further consideration of the changes in the system’s load and real-time electricity price, a model of additional potential benefits of energy storage is developed. Aiming at the lowest total operating cost, a bi-level optimal operational model for day-ahead operation of BIES is developed. A case analysis of different dispatch strategies verifies that the addition of the proposed battery scheduling strategy improves economic operation. The results demonstrate that the model can exploit energy storage’s potential, further optimize the power output of BIES and reduce the economic cost.

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The multi-region integrated energy system (MRIES) is one promising option for exploiting the complementarity potentials between power system, thermal system and loads, as well as improving flexibility and economic competitiveness. However, the optimal planning has remained challenging since it involves multiple forms of energies with the nature of coupling. A mixed integer linear programming (MILP) model is proposed for joint optimization of MRIES planning and operation, which considers the flexible load's demand response (DR). It is realized by combining the multi-region heating network IES coupling model with the flexible cooling-heating-electric load DR model. The results show that the proposed model can assist planners to comprehensively analyze and evaluate the impacts of multiple factors on planning, and to determine the optimal planning configuration and operation strategy.INDEX TERMS Multi-region integrated energy system, regional thermal network, flexible demand response, planning and operation, mixed integer linear programming.

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