Based on this evaluation results, a bi-layer optimal energy storage planning model for the CES operator is established, where the upper-layer model determines the installed capacity of lithium (Li-ion) battery station and the lower-layer model determines the optimal schedules of the CES system.
Also, the existing widely-used method in energy storage planning, that embeds the system frequency response model into the optimization model to deal with inertia shortage demand, is unfeasible to be directly used in the CES business model due to the data confidentiality problem.
The effectiveness of the energy storage planning method is highly related to the economic profits of the CES system. The above consideration motivates us to study the optimal energy storage planning problem of the CES system considering system inertia support and facing the electricity-heat coordination trend.
From the perspective of the CES operator, the purpose of installing extra energy storage facility is to increase CES system's profit. The objective function of the upper layer model (24) is to maximize the annual profit of the CES system after installing the Li-ion battery station.
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Based on this evaluation results, a bi-layer optimal energy storage planning model for the CES operator is established, where the upper-layer model determines the installed capacity of
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