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The optimization of planning and operation for distributed energy systems (DESs) is often converted into an approximated mixed-integer linear programming (MILP) problem. To improve the MILP model’s accuracy, it is necessary to linearize many non-linear factors, and one of the most critical factors is off-design efficiency. In this study, the off-design performance of common energy conversion technologies and their effect on optimization reliability are investigated through a literature review and dynamic simulation models. It is found that most technologies can maintain high and stable efficiency within a certain range of load, and the off-design characteristics of certain technologies can be ignored. Therefore, in our MILP model, the off-design efficiency is simplified by optimizing the number of certain types of devices while simultaneously limiting their load to a certain range and ignoring the off-design characteristics of other types of devices. This method allows the devices to always work with high efficiency, due to perfect working conditions. The optimization results prove that compared to the method considering the off-design efficiency of all technologies, the maximum deviation is only 2.29%, demonstrating enough accuracy of the proposed method. Owing to the simplification of off-design efficiency, more non-linear factors are promising to add in the model.

Effect and simplification of off-design efficiency on optimization of planning and operation for distributed energy systems