ABSTRACT

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.

摘要

分布式能源系统 (DES) 的规划和运行优化通常转换为近似混合整数线性规划 (MILP) 问题。为了提高 MILP 模型的精度，需要对许多非线性因素进行线性化处理，其中最关键的因素之一是非设计效率。在本研究中，通过文献综述和动态仿真模型研究了常见能量转换技术的非设计性能及其对优化可靠性的影响。研究发现，大多数技术在一定的负载范围内都能保持高且稳定的效率，而某些技术的非设计特性可以忽略不计。因此，在我们的 MILP 模型中，通过优化某些类型设备的数量，同时将其负载限制在一定范围内并忽略其他类型设备的非设计特性，可以简化非设计效率。由于完美的工作条件，这种方法允许设备始终以高效率工作。优化结果证明，与考虑所有技术的非设计效率的方法相比，最大偏差仅为2.29%，表明该方法具有足够的精度。由于非设计效率的简化，更多的非线性因素有望添加到模型中。优化结果证明，与考虑所有技术的非设计效率的方法相比，最大偏差仅为2.29%，表明该方法具有足够的精度。由于非设计效率的简化，更多的非线性因素有望添加到模型中。优化结果证明，与考虑所有技术的非设计效率的方法相比，最大偏差仅为2.29%，表明该方法具有足够的精度。由于非设计效率的简化，更多的非线性因素有望添加到模型中。