This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal ...This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal allocation and sizing of multiple PV-DG units to minimize power losses using a probabilistic PV model and time-series power flow analysis. Addressing the uncertainties in PV output due to weather variability and diurnal cycles is critical. A probabilistic assessment offers a more robust analysis of DG integration’s impact on the grid, potentially leading to more reliable system planning. The presented approach employs a genetic algorithm (GA) and a determined PV output profile and probabilistic PV generation profile based on experimental measurements for one year of solar radiation in Cairo, Egypt. The proposed algorithms are validated using a co-simulation framework that integrates MATLAB and OpenDSS, enabling analysis on a 33-bus test system. This framework can act as a guideline for creating other co-simulation algorithms to enhance computing platforms for contemporary modern distribution systems within smart grids concept. The paper presents comparisons with previous research studies and various interesting findings such as the considered hours for developing the probabilistic model presents different results.展开更多
The artificial bee colony(ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow(OPF) problem by simultaneously optimizing three conflicting obj...The artificial bee colony(ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow(OPF) problem by simultaneously optimizing three conflicting objectives of OPF, instead of transforming multi-objective functions into a single objective function. The main idea of HMOABC is to extend original ABC algorithm to multi-objective and cooperative mode by combining the Pareto dominance and divide-and-conquer approach. HMOABC is then used in the 30-bus IEEE test system for solving the OPF problem considering the cost, loss, and emission impacts. The simulation results show that the HMOABC is superior to other algorithms in terms of optimization accuracy and computation robustness.展开更多
Firefly algorithm is the new intelligent algorithm used for all complex engineering optimization problems. Power system has many complex optimization problems one of which is the optimal power flow (OPF). Basically, i...Firefly algorithm is the new intelligent algorithm used for all complex engineering optimization problems. Power system has many complex optimization problems one of which is the optimal power flow (OPF). Basically, it is minimizing optimization problem and subjected to many complex objective functions and constraints. Hence, firefly algorithm is used to solve OPF in this paper. The aim of the firefly is to optimize the control variables, namely generated real power, voltage magnitude and tap setting of transformers. Flexible AC Transmission system (FACTS) devices may used in the power system to improve the quality of the power supply and to reduce the cost of the generation. FACTS devices are classified into series, shunt, shunt-series and series-series connected devices. Unified power flow controller (UPFC) is shunt-series type device that posses all capabilities to control real, reactive powers, voltage and reactance of the connected line in the power system. Hence, UPFC is included in the considered IEEE 30 bus for the OPF solution.展开更多
Recently,power electronic transformers(PETs)have received widespread attention owing to their flexible networking,diverse operating modes,and abundant control objects.In this study,we established a steady-state model ...Recently,power electronic transformers(PETs)have received widespread attention owing to their flexible networking,diverse operating modes,and abundant control objects.In this study,we established a steady-state model of PETs and applied it to the power flow calculation of AC-DC hybrid systems with PETs,considering the topology,power balance,loss,and control characteristics of multi-port PETs.To address new problems caused by the introduction of the PET port and control equations to the power flow calculation,this study proposes an iterative method of AC-DC mixed power flow decoupling based on step optimization,which can achieve AC-DC decoupling and effectively improve convergence.The results show that the proposed algorithm improves the iterative method and overcomes the overcorrection and initial value sensitivity problems of conventional iterative algorithms.展开更多
为应对高比例新能源并网带来的不确定性与暂态稳定挑战,实现电力系统安全性与经济性的协同优化,提出一种含新能源接入的多目标暂态稳定约束最优潮流(transient stability constrained optimal power flow,TSCOPF)算法。采用基于凸包改...为应对高比例新能源并网带来的不确定性与暂态稳定挑战,实现电力系统安全性与经济性的协同优化,提出一种含新能源接入的多目标暂态稳定约束最优潮流(transient stability constrained optimal power flow,TSCOPF)算法。采用基于凸包改进的多边形不确定集区间模型刻画风光出力不确定性,并引入模糊集理论对模型的目标函数与暂态稳定约束进行模糊化处理;采用基于马尔可夫网络改进的强度Pareto进化算法(improved strength Pareto evolution algorithm based on Markov network,ISPEA-MN)进行求解。在改进的IEEE 39节点系统中进行仿真测试,结果表明:与传统方法相比,所提算法获得的Pareto解集分布更均匀、更逼近真实前沿,计算效率更优;所建模糊化模型在确保系统暂态稳定的前提下,将总发电成本降低了13.3元/h,有效提升了系统的经济性与运行安全性。主要创新点在于构建了融合不确定性处理与模糊化约束的TSCOPF模型,并提出了求解该模型的ISPEABMN高效算法。展开更多
There are many motors in operation or on standby in nuclear power plants,and the startup of group motors will have a great impact on the voltage of the emergency bus.At present,there is no special or inexpensive softw...There are many motors in operation or on standby in nuclear power plants,and the startup of group motors will have a great impact on the voltage of the emergency bus.At present,there is no special or inexpensive software to solve this problem,and the experience of engineers is not accurate enough.Therefore,this paper developed a method and system for the startup calculation of group motors in nuclear power plants and proposed an automatic generation method of circuit topology in nuclear power plants.Each component in the topology was given its unique number,and the component class could be constructed according to its type and upper and lower connections.The subordination and topology relationship of switches,buses,and motors could be quickly generated by the program according to the component class,and the simplified direct power flow algorithm was used to calculate the power flow for the startup of group motors according to the above relationship.Then,whether the bus voltage is in the safe range and whether the voltage exceeds the limit during the startup of the group motor could be judged.The practical example was used to verify the effectiveness of the method.Compared with other professional software,the method has high efficiency and low cost.展开更多
最优潮流(optimal power flow,OPF)是配电网优化调度决策的核心,因此亟须针对其设计出大规模网架下的快速计算方法。提出了一种面向可行性恢复的深度学习OPF求解方法。首先,构建基于状态-控制变量分解的OPF求解架构,基于深度神经网络搭...最优潮流(optimal power flow,OPF)是配电网优化调度决策的核心,因此亟须针对其设计出大规模网架下的快速计算方法。提出了一种面向可行性恢复的深度学习OPF求解方法。首先,构建基于状态-控制变量分解的OPF求解架构,基于深度神经网络搭建OPF状态变量求解模型;其次,针对基于深度神经网络的OPF结果不满足控制变量约束的问题,筛选存在不等式约束违规的样本并构建修正样本集,考虑实际物理约束和供需平衡关系,提出基于控制变量整体的联合修正约束条件,建立修正区间;最后,基于多边缘分布的Sinkhorn算法调整控制变量解,将约束违反变量迭代投影至修正区间内,使其满足实际物理约束条件。基于改进的IEEE 123节点配电网算例对所提方法进行验证。实验结果表明,所提方法能有效实现控制变量的可行性恢复,同时均衡各控制变量的平均绝对误差,提高解的精度。展开更多
摘要This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on identifying the optimal allocation and sizing of multiple PV-DG units to minimize power losses using a probabilistic PV model and time-series power flow analysis. Addressing the uncertainties in PV output due to weather variability and diurnal cycles is critical. A probabilistic assessment offers a more robust analysis of DG integration’s impact on the grid, potentially leading to more reliable system planning. The presented approach employs a genetic algorithm (GA) and a determined PV output profile and probabilistic PV generation profile based on experimental measurements for one year of solar radiation in Cairo, Egypt. The proposed algorithms are validated using a co-simulation framework that integrates MATLAB and OpenDSS, enabling analysis on a 33-bus test system. This framework can act as a guideline for creating other co-simulation algorithms to enhance computing platforms for contemporary modern distribution systems within smart grids concept. The paper presents comparisons with previous research studies and various interesting findings such as the considered hours for developing the probabilistic model presents different results.
基金Projects(61105067,61174164)supported by the National Natural Science Foundation of China
摘要The artificial bee colony(ABC) algorithm is improved to construct a hybrid multi-objective ABC algorithm, called HMOABC, for resolving optimal power flow(OPF) problem by simultaneously optimizing three conflicting objectives of OPF, instead of transforming multi-objective functions into a single objective function. The main idea of HMOABC is to extend original ABC algorithm to multi-objective and cooperative mode by combining the Pareto dominance and divide-and-conquer approach. HMOABC is then used in the 30-bus IEEE test system for solving the OPF problem considering the cost, loss, and emission impacts. The simulation results show that the HMOABC is superior to other algorithms in terms of optimization accuracy and computation robustness.
摘要Firefly algorithm is the new intelligent algorithm used for all complex engineering optimization problems. Power system has many complex optimization problems one of which is the optimal power flow (OPF). Basically, it is minimizing optimization problem and subjected to many complex objective functions and constraints. Hence, firefly algorithm is used to solve OPF in this paper. The aim of the firefly is to optimize the control variables, namely generated real power, voltage magnitude and tap setting of transformers. Flexible AC Transmission system (FACTS) devices may used in the power system to improve the quality of the power supply and to reduce the cost of the generation. FACTS devices are classified into series, shunt, shunt-series and series-series connected devices. Unified power flow controller (UPFC) is shunt-series type device that posses all capabilities to control real, reactive powers, voltage and reactance of the connected line in the power system. Hence, UPFC is included in the considered IEEE 30 bus for the OPF solution.
基金supported by the National Key Research and Development Program of China(2017YFB0903300).
摘要Recently,power electronic transformers(PETs)have received widespread attention owing to their flexible networking,diverse operating modes,and abundant control objects.In this study,we established a steady-state model of PETs and applied it to the power flow calculation of AC-DC hybrid systems with PETs,considering the topology,power balance,loss,and control characteristics of multi-port PETs.To address new problems caused by the introduction of the PET port and control equations to the power flow calculation,this study proposes an iterative method of AC-DC mixed power flow decoupling based on step optimization,which can achieve AC-DC decoupling and effectively improve convergence.The results show that the proposed algorithm improves the iterative method and overcomes the overcorrection and initial value sensitivity problems of conventional iterative algorithms.
摘要为应对高比例新能源并网带来的不确定性与暂态稳定挑战,实现电力系统安全性与经济性的协同优化,提出一种含新能源接入的多目标暂态稳定约束最优潮流(transient stability constrained optimal power flow,TSCOPF)算法。采用基于凸包改进的多边形不确定集区间模型刻画风光出力不确定性,并引入模糊集理论对模型的目标函数与暂态稳定约束进行模糊化处理;采用基于马尔可夫网络改进的强度Pareto进化算法(improved strength Pareto evolution algorithm based on Markov network,ISPEA-MN)进行求解。在改进的IEEE 39节点系统中进行仿真测试,结果表明:与传统方法相比,所提算法获得的Pareto解集分布更均匀、更逼近真实前沿,计算效率更优;所建模糊化模型在确保系统暂态稳定的前提下,将总发电成本降低了13.3元/h,有效提升了系统的经济性与运行安全性。主要创新点在于构建了融合不确定性处理与模糊化约束的TSCOPF模型,并提出了求解该模型的ISPEABMN高效算法。
基金Key Project of National Natural Science Foundation of China(52237008)Beijing Municipal Education Commission Research Program Funding Project(KM202111232022)。
摘要There are many motors in operation or on standby in nuclear power plants,and the startup of group motors will have a great impact on the voltage of the emergency bus.At present,there is no special or inexpensive software to solve this problem,and the experience of engineers is not accurate enough.Therefore,this paper developed a method and system for the startup calculation of group motors in nuclear power plants and proposed an automatic generation method of circuit topology in nuclear power plants.Each component in the topology was given its unique number,and the component class could be constructed according to its type and upper and lower connections.The subordination and topology relationship of switches,buses,and motors could be quickly generated by the program according to the component class,and the simplified direct power flow algorithm was used to calculate the power flow for the startup of group motors according to the above relationship.Then,whether the bus voltage is in the safe range and whether the voltage exceeds the limit during the startup of the group motor could be judged.The practical example was used to verify the effectiveness of the method.Compared with other professional software,the method has high efficiency and low cost.
摘要最优潮流(optimal power flow,OPF)是配电网优化调度决策的核心,因此亟须针对其设计出大规模网架下的快速计算方法。提出了一种面向可行性恢复的深度学习OPF求解方法。首先,构建基于状态-控制变量分解的OPF求解架构,基于深度神经网络搭建OPF状态变量求解模型;其次,针对基于深度神经网络的OPF结果不满足控制变量约束的问题,筛选存在不等式约束违规的样本并构建修正样本集,考虑实际物理约束和供需平衡关系,提出基于控制变量整体的联合修正约束条件,建立修正区间;最后,基于多边缘分布的Sinkhorn算法调整控制变量解,将约束违反变量迭代投影至修正区间内,使其满足实际物理约束条件。基于改进的IEEE 123节点配电网算例对所提方法进行验证。实验结果表明,所提方法能有效实现控制变量的可行性恢复,同时均衡各控制变量的平均绝对误差,提高解的精度。