外文翻译(基于多主体粒子群最优化能源反应发生装置的研究)(编辑修改稿)

外文翻译(基于多主体粒子群最优化能源反应发生装置的研究)(编辑修改稿)内容摘要：

ive power loss in work (.). Transfer conductance between bus and (.). Conductance of branch (.). Set of numbers of total buses excluding slack bus. Set of numbers of total buses. Set of numbers of possible reactive power source installation buses. Set of numbers of power demand buses. Set of numbers of work branches. Set of numbers of generator buses. Set of numbers of buses adjacent to bus , including bus . Set of numbers of buses. Set of numbers of buses. Set of numbers of buses on which injected reactive power outside limits. Set of numbers of transformer branches. Set of numbers of buses on which voltages outside limits. Demanded active power at bus (.). 7 Injected active power at bus (.). Active power loss in branch (.). Power flow in branch (.). Injected active power at slack bus (.). Reactive power source installation at bus (.). Demanded reactive power at bus (.). Injected reactive power at bus (.). Tap position of transformer . Voltage magnitude of bus (.). Voltage vectors of buses (.). Voltage vectors of buses (.). Manuscript received August 13, 2020。 revised December 27, 2020. This work is supported by the Outstanding Young Scholars Fund (no. 60225006) and Innovative Research Group Fund of Natural Science Foundation of China. Paper . The authors are with the College of Electrical Engineering, Zhejiang University, Hangzhou, Zhejiang 310027, China (。 ). Digital Object Identifier I. INTRODUCTION THE reactive power dispatch problem has a significant influence on secure and economic operation of power systems. Reactive power optimization is a subproblem of theoptimal powerflow (OPF) calculation, which determines all kinds of controllable variables, such as reactivepower outputs of generators and static reactive power pensators, tap ratios of transformers, outputs of shunt capacitors/reactors, etc., and minimizes transmission losses or other appropriate objective functions, while satisfying a given set of physical and operating constraints. Since transformer tap ratios and outputs of shunt capacitors/reactors have a discrete nature, while reactive power outputs of generators and static VAR pensators, busvoltage magnitudes, and angles are, on the other hand, continuous variables, the reactive power 8 optimization problem can be exactly formulated using a mixedinteger/nonlinear programming model, ., cast as a nonlinear optimization problem with a mixture of discrete and continuous variables. Up to now, a number of techniques ranging from classical techniques like gradientbased optimization algorithms to various mathematical programming techniques have been applied to solve this problem [1]–[4]. Recently, due to the basic efficiency of interiorpoint methods, which offer fast convergence and convenience in handling inequality constraints in parison with other methods, interiorpoint linear programming [5], quadratic programming [6], and nonlinear programming [7] methods have been widely used to solve the OPF problem of largescale power systems. However, these techniques have sev。