An Uncertain Optimal Energy Flow Model for CCHP Campus Microgrid Using Parameterized Probability Boxes  

作　　者：Shunjiang Lin Xuan Sheng Yuquan Xie Yanghua Liu Mingbo Liu 

机构地区：[1]IEEE [2]School of Electric Power Engineering,South China University of Technology,Guangzhou 510640,China [3]Digital Grid Research Institute,China Southern Power Grid,Guangzhou 510700,China [4]School of Electromechanical Engineering,Guangdong Polytechnic Normal University,Guangzhou,China

出　　处：《Journal of Modern Power Systems and Clean Energy》2023年第5期1618-1633,共16页现代电力系统与清洁能源学报（英文）

基　　金：supported by the National Natural Science Foundation of China (No. 51977080);the Natural Science Foundation of Guangdong Province (No. 2022A1515010332)。

摘　　要：Due to the uncertain fluctuations of renewable energy and load power, the state variables such as bus voltages and pipeline mass flows in the combined cooling, heating, and power campus microgrid(CCHP-CMG) may exceed the secure operation limits. In this paper, an optimal energy flow(OEF) model for a CCHP-CMG using parameterized probability boxes(p-boxes) is proposed to describe the higher-order uncertainty of renewables and loads. In the model, chance constraints are used to describe the secure operation limits of the state variable p-boxes, and variance constraints are introduced to reduce their random fluctuation ranges. To solve this model, the chance and variance constraints are transformed into the constraints of interval cumulants(ICs) of state variables based on the p-efficient point theory and interval Cornish-Fisher expansion. With the relationship between the ICs of state variables and node power, and using the affine interval arithmetic method, the original optimization model is finally transformed into a deterministic nonlinear programming model. It can be solved by the CONOPT solver in GAMS software to obtain the optimal operation point of a CCHP-CMG that satisfies the secure operation requirements considering the higher-order uncertainty of renewables and loads. Case study on a CCHP-CMG demonstrates the correctness and effectiveness of the proposed OEF model.

关 键 词：Combined cooling heating and power campus microgrid(CCHP-CMG) chance-constrained programming higher-order uncertainty optimal energy flow parameterized probability box 

分 类 号：TM73[电气工程—电力系统及自动化]