In this paper,a model free volt/var control(VVC)algorithm is developed by using deep reinforcement learning(DRL).We transform the VVC problem of distribution networks into the network framework of PPO algorithm,in ord...In this paper,a model free volt/var control(VVC)algorithm is developed by using deep reinforcement learning(DRL).We transform the VVC problem of distribution networks into the network framework of PPO algorithm,in order to avoid directly solving a large-scale nonlinear optimization problem.We select photovoltaic inverters as agents to adjust system voltage in a distribution network,taking the reactive power output of inverters as action variables.An appropriate reward function is designed to guide the interaction between photovoltaic inverters and the distribution network environment.OPENDSS is used to output system node voltage and network loss.This method realizes the goal of optimal VVC in distribution network.The IEEE 13-bus three phase unbalanced distribution system is used to verify the effectiveness of the proposed algorithm.Simulation results demonstrate that the proposed method has excellent performance in voltage and reactive power regulation of a distribution network.展开更多
The major challenge to increase the decentralized generation share in distribution grids is the maintenance of the voltage within the limits. The inductive power injection is widely used as a remedial measure. The mai...The major challenge to increase the decentralized generation share in distribution grids is the maintenance of the voltage within the limits. The inductive power injection is widely used as a remedial measure. The main aim of this paper is to study the effect of the reactive power injection (by what-ever means) on radial grid structures and their impact on the voltage of the higher voltage-level grids. Various studies have shown that, in addition to the major local effect on the voltage at the injection point, the injection of the reactive power on a feeder has a global effect, which cannot be neglected. The reactive power flow and the voltage on the higher voltage level grid are significantly affected. In addition, a random effect is introduced by the DGs which are connected through inverters (using wind or PVs). Although their operation is in accordance with the grid code, a volatile reactive power flow circulates on the grid. Finally, this study proposes the implementation of the “Volt/var secondary control” interaction chain in order to increase the distributed generation share at every distribution voltage level, be it medium or low voltage, and at the same time to guarantee a stable operation of the power grid. Features of Volt/var secondary control loops ensure a resilient behavior of the whole chain.展开更多
This paper proposes an online hierarchical volt/var control(VVC)for unbalanced distribution networks using diagonal-scaling alternating direction method of multipliers(DS-ADMM).Under the hierarchical VVC strategy,loca...This paper proposes an online hierarchical volt/var control(VVC)for unbalanced distribution networks using diagonal-scaling alternating direction method of multipliers(DS-ADMM).Under the hierarchical VVC strategy,local photovoltaic(PV)agents only exchange limited information with the center agent and adjust reactive power outputs in real time,with the goal of minimizing the voltage deviations and reactive power regulation costs in the time-varying environment.A diagonalized auxiliary matrix is constructed and developed from the Hessian matrix using preconditioning methods,which is then combined with alternating direction method of multipliers(ADMM)to design the DS-ADMM with improved convergence speed.The DS-ADMM is applied to the hierarchical VVC strategy,further improving the tracking capability and performance for time-varying environmental changes.Simulation studies on a modified IEEE 123-bus unbalanced distribution network are conducted to verify the effectiveness of the hierarchical VVC strategy using DS-ADMM and its robustness under non-ideal communication conditions,and its scalability is further validated on the modified IEEE 8500-node test feeder.展开更多
For active distribution networks(ADNs)integrated with massive inverter-based energy resources,it is impractical to maintain the accurate model and deploy measurements at all nodes due to the large-scale of ADNs.Thus,c...For active distribution networks(ADNs)integrated with massive inverter-based energy resources,it is impractical to maintain the accurate model and deploy measurements at all nodes due to the large-scale of ADNs.Thus,current models of ADNs usually involve significant errors or even unknown occurances.Moreover,ADNs are usually partially observable since only a few measurements are available at pilot nodes or nodes with significant users.To provide a practical Volt/Var control(VVC)strategy for such networks,a data-driven VVC method is proposed in this paper.First,the system response policy,approximating the relationship between the control variables and states of monitoring nodes,is estimated by a recursive regression closed-form solution.Then,based on real-time measurements and the newly updated system response policy,a VVC strategy with convergence guarantee is realized.Since the recursive regression solution is embedded in the control stage,a data-driven closedloop VVC framework is established.The effectiveness of the proposed method is validated in an unbalanced distribution system considering nonlinear loads,where not only the rapid and self-adaptive voltage regulation is realized,but also systemwide optimization is achieved.展开更多
When urban distribution systems are gradually modernized,the overhead lines are replaced by underground cables,whose shunt admittances can not be ignored.Traditional power flow(PF)model withπequivalent circuit shows ...When urban distribution systems are gradually modernized,the overhead lines are replaced by underground cables,whose shunt admittances can not be ignored.Traditional power flow(PF)model withπequivalent circuit shows non-convexity and long computing time,and most recently proposed linear PF models assume zero shunt elements.All of them are not suitable for fast calculation and optimization problems of modern distribution systems with non-negligible line shunts.Therefore,this paper proposes a linearized branch flow model considering line shunt(LBFS).The strength of LBFS lies in maintaining the linear structure and the convex nature after appropriately modeling theπequivalent circuit for network equipment like transformers.Simulation results show that the calculation accuracy in nodal voltage and branch current magnitudes is improved by considering shunt admittances.We show the application scope of LBFS by controlling the network voltages through a two-stage stochastic Volt/VAr control(VVC)problem with the uncertain active power output from renewable energy sources(RESs).Since LBFS results in a linear VVC program,the global solution is guaranteed.Case study exhibits that VVC framework can optimally dispatch the discrete control devices,viz.substation transformers and shunt capacitors,and also optimize the decision rules for real-time reactive power control of RES.Moreover,the computing efficiency is significantly improved compared with that of traditional VVC methods.展开更多
Photovoltaic(PV)inverter-based volt/var control(VVC)is highly promising to tackle the emerging voltage regulation challenges brought by increasing PV penetration.However,PV inverter operational reliability has arisen ...Photovoltaic(PV)inverter-based volt/var control(VVC)is highly promising to tackle the emerging voltage regulation challenges brought by increasing PV penetration.However,PV inverter operational reliability has arisen as a critical concern for practical VVC implementation.This paper proposes a new PV inverter based VVC optimization model and a Pareto front analysis method for maintaining a satisfactory inverter lifetime.First,reliability of the vulnerable DC-link capacitor inside a PV inverter is analyzed,and long-term VVC impact on inverter operational reliability is identified.Second,a multi-objective PV inverter based VVC optimization model is proposed for minimizing both inverter apparent power output and network power loss with a weighting factor.Third,a Pareto front analysis method is developed to visualize the impact of the weighting factor on VVC performance and inverter reliability,thus determining the effective weighting factor to reduce network power loss with expected inverter lifetime.Effectiveness of the proposed VVC optimization model and Pareto front analysis method are verified in a case study.展开更多
In the present scenario,many solar photovoltaic(SPV)systems have been installed in the distribution network,most of them are operating at the unity power factor,which does not provide any reactive power support.In fut...In the present scenario,many solar photovoltaic(SPV)systems have been installed in the distribution network,most of them are operating at the unity power factor,which does not provide any reactive power support.In future distribution grids,there will be significant advances in operating strategies of SPV systems with the introduction of smart inverter functions.The new IEEE Std.1547-2018 incorporates dynamic Volt/VAr control(VVC)for smart inverters.These smart inverters can inject or absorb reactive power and maintain voltages at points of common coupling(PCCs)based on local voltage measurements.With multiple inverter-interfaced SPV systems connected to the grid,it becomes a necessary task to develop local,distributed or hybrid VVC algorithms for maximization of energy savings.This paper aims to estimate substation energy savings through centralized and decentralized control of inverters of SPV system alongside various VVC devices.Control strategies of each SPV inverter have been accomplished in compliance with IEEE Std.1547-2018.Time-series simulations are carried out on the modified IEEE-123 node test system.By utilizing smart inverters in traditional SPV systems,considerable energy savings can be obtained.These savings can be further increased by incorporating optimal intelligent VVC characteristics(IVVCC).Results show that just by allowing smart inverters on a predefined IVVCC(as per IEEE Std.1547-2018),a reduction of 11.69%in reactive demand and 5.63%in active demand have been acquired when compared with a conventional SPV system.Reactive energy demand is additionally reduced to 48.42%by considering centralized control of VVC devices alongside optimal IVVCC.展开更多
高间歇性、高波动性分布式电源(distributed generation,DG)的持续大量接入给配电网的无功电压管理带来严峻挑战,对无功优化的时效性提出了更高要求。现有电压无功控制研究普遍基于单一电压等级和三相平衡网络模型假设,但实际中低压配...高间歇性、高波动性分布式电源(distributed generation,DG)的持续大量接入给配电网的无功电压管理带来严峻挑战,对无功优化的时效性提出了更高要求。现有电压无功控制研究普遍基于单一电压等级和三相平衡网络模型假设,但实际中低压配网两侧的DG、负荷通过配电变压器的耦合互动不断加剧。同时,由于换相缺失、线路不对称布置、负荷及DG不均匀接入等因素,配电网不平衡特性日益加剧,沿用单一电压等级和三相平衡网络可致电压无功控制决策结果不合理甚至不可行。为此,提出一种基于线性规划的中低压不平衡配电网电压无功实时优化方法。具体通过中压配网静止无功发生器(static var generator,SVG)和低压配网分布式光伏逆变器的协调控制,在满足电网运行约束和控制设备能力约束的情况下,实现中低压不平衡配电网节点电压偏差的最小化。同时,为满足高间歇性DG接入对电压无功控制实时性的要求,对上述非线性电压无功优化问题进行线性化逼近,并采用CPLEX求解器对相应线性规划问题进行有效求解。最后,基于某澳大利亚真实配网开展24h仿真,验证了所提基于线性规划的中低压不平衡配电网电压无功实时优化的有效性和优越性。展开更多
分布式可再生能源的大规模接入,加剧了有源配电网(Active Distribution Network,ADN)的三相不平衡,容易导致系统电压越限与线损增加。然而,由于当前配电网量测设备安装不全,部分节点负荷数据难以准确获取,因此传统基于全局观测的ADN电...分布式可再生能源的大规模接入,加剧了有源配电网(Active Distribution Network,ADN)的三相不平衡,容易导致系统电压越限与线损增加。然而,由于当前配电网量测设备安装不全,部分节点负荷数据难以准确获取,因此传统基于全局观测的ADN电压控制方法难以满足实际控制需求。为解决上述问题,提出一种含深度学习代理模型的电压无功控制(Volt/Var control,VVC)进化算法。设计以高速公路神经网络为代理模型,精确拟合局部量测负荷信息、调压控制策略与系统性能指标之间的映射关系。将训练后的代理模型嵌入非支配排序遗传算法的迭代寻优过程中,对电压偏移率、三相不平衡度及线路损耗指标进行直接计算,实现数据驱动的配电网VVC策略快速求取。在改进的IEEE 123节点三相配电网算例上进行测试,验证了所提算法的性能优势及求解效率。展开更多
基金supported by the Science and Technology Project of State Grid Zhejiang Electric Power Co.,Ltd.under Grant B311JY21000A。
摘要In this paper,a model free volt/var control(VVC)algorithm is developed by using deep reinforcement learning(DRL).We transform the VVC problem of distribution networks into the network framework of PPO algorithm,in order to avoid directly solving a large-scale nonlinear optimization problem.We select photovoltaic inverters as agents to adjust system voltage in a distribution network,taking the reactive power output of inverters as action variables.An appropriate reward function is designed to guide the interaction between photovoltaic inverters and the distribution network environment.OPENDSS is used to output system node voltage and network loss.This method realizes the goal of optimal VVC in distribution network.The IEEE 13-bus three phase unbalanced distribution system is used to verify the effectiveness of the proposed algorithm.Simulation results demonstrate that the proposed method has excellent performance in voltage and reactive power regulation of a distribution network.
摘要The major challenge to increase the decentralized generation share in distribution grids is the maintenance of the voltage within the limits. The inductive power injection is widely used as a remedial measure. The main aim of this paper is to study the effect of the reactive power injection (by what-ever means) on radial grid structures and their impact on the voltage of the higher voltage-level grids. Various studies have shown that, in addition to the major local effect on the voltage at the injection point, the injection of the reactive power on a feeder has a global effect, which cannot be neglected. The reactive power flow and the voltage on the higher voltage level grid are significantly affected. In addition, a random effect is introduced by the DGs which are connected through inverters (using wind or PVs). Although their operation is in accordance with the grid code, a volatile reactive power flow circulates on the grid. Finally, this study proposes the implementation of the “Volt/var secondary control” interaction chain in order to increase the distributed generation share at every distribution voltage level, be it medium or low voltage, and at the same time to guarantee a stable operation of the power grid. Features of Volt/var secondary control loops ensure a resilient behavior of the whole chain.
基金supported by the Fundamental Research Funds for the Central Universities(No.2024MS001)the Fellowship of the China Postdoctoral Science Foundation(No.2024M750892)the Postdoctoral Fellowship Program of CPSF(No.GZC20230785).
摘要This paper proposes an online hierarchical volt/var control(VVC)for unbalanced distribution networks using diagonal-scaling alternating direction method of multipliers(DS-ADMM).Under the hierarchical VVC strategy,local photovoltaic(PV)agents only exchange limited information with the center agent and adjust reactive power outputs in real time,with the goal of minimizing the voltage deviations and reactive power regulation costs in the time-varying environment.A diagonalized auxiliary matrix is constructed and developed from the Hessian matrix using preconditioning methods,which is then combined with alternating direction method of multipliers(ADMM)to design the DS-ADMM with improved convergence speed.The DS-ADMM is applied to the hierarchical VVC strategy,further improving the tracking capability and performance for time-varying environmental changes.Simulation studies on a modified IEEE 123-bus unbalanced distribution network are conducted to verify the effectiveness of the hierarchical VVC strategy using DS-ADMM and its robustness under non-ideal communication conditions,and its scalability is further validated on the modified IEEE 8500-node test feeder.
基金supported by the Research Project of China Southern Power Grid Corporation:The demonstration and application of the virtual power plant intelligent operation and management platform with source-grid coordination,No.GDKJXM20185069 (032000KK 52180069)。
摘要For active distribution networks(ADNs)integrated with massive inverter-based energy resources,it is impractical to maintain the accurate model and deploy measurements at all nodes due to the large-scale of ADNs.Thus,current models of ADNs usually involve significant errors or even unknown occurances.Moreover,ADNs are usually partially observable since only a few measurements are available at pilot nodes or nodes with significant users.To provide a practical Volt/Var control(VVC)strategy for such networks,a data-driven VVC method is proposed in this paper.First,the system response policy,approximating the relationship between the control variables and states of monitoring nodes,is estimated by a recursive regression closed-form solution.Then,based on real-time measurements and the newly updated system response policy,a VVC strategy with convergence guarantee is realized.Since the recursive regression solution is embedded in the control stage,a data-driven closedloop VVC framework is established.The effectiveness of the proposed method is validated in an unbalanced distribution system considering nonlinear loads,where not only the rapid and self-adaptive voltage regulation is realized,but also systemwide optimization is achieved.
基金supported in part by the National Natural Science Foundation of China(No.51977115)。
摘要When urban distribution systems are gradually modernized,the overhead lines are replaced by underground cables,whose shunt admittances can not be ignored.Traditional power flow(PF)model withπequivalent circuit shows non-convexity and long computing time,and most recently proposed linear PF models assume zero shunt elements.All of them are not suitable for fast calculation and optimization problems of modern distribution systems with non-negligible line shunts.Therefore,this paper proposes a linearized branch flow model considering line shunt(LBFS).The strength of LBFS lies in maintaining the linear structure and the convex nature after appropriately modeling theπequivalent circuit for network equipment like transformers.Simulation results show that the calculation accuracy in nodal voltage and branch current magnitudes is improved by considering shunt admittances.We show the application scope of LBFS by controlling the network voltages through a two-stage stochastic Volt/VAr control(VVC)problem with the uncertain active power output from renewable energy sources(RESs).Since LBFS results in a linear VVC program,the global solution is guaranteed.Case study exhibits that VVC framework can optimally dispatch the discrete control devices,viz.substation transformers and shunt capacitors,and also optimize the decision rules for real-time reactive power control of RES.Moreover,the computing efficiency is significantly improved compared with that of traditional VVC methods.
基金This work was supported in part by NTU Grant No.021542-00001in part by Australian Government Research Training Program Scholarship。
摘要Photovoltaic(PV)inverter-based volt/var control(VVC)is highly promising to tackle the emerging voltage regulation challenges brought by increasing PV penetration.However,PV inverter operational reliability has arisen as a critical concern for practical VVC implementation.This paper proposes a new PV inverter based VVC optimization model and a Pareto front analysis method for maintaining a satisfactory inverter lifetime.First,reliability of the vulnerable DC-link capacitor inside a PV inverter is analyzed,and long-term VVC impact on inverter operational reliability is identified.Second,a multi-objective PV inverter based VVC optimization model is proposed for minimizing both inverter apparent power output and network power loss with a weighting factor.Third,a Pareto front analysis method is developed to visualize the impact of the weighting factor on VVC performance and inverter reliability,thus determining the effective weighting factor to reduce network power loss with expected inverter lifetime.Effectiveness of the proposed VVC optimization model and Pareto front analysis method are verified in a case study.
摘要In the present scenario,many solar photovoltaic(SPV)systems have been installed in the distribution network,most of them are operating at the unity power factor,which does not provide any reactive power support.In future distribution grids,there will be significant advances in operating strategies of SPV systems with the introduction of smart inverter functions.The new IEEE Std.1547-2018 incorporates dynamic Volt/VAr control(VVC)for smart inverters.These smart inverters can inject or absorb reactive power and maintain voltages at points of common coupling(PCCs)based on local voltage measurements.With multiple inverter-interfaced SPV systems connected to the grid,it becomes a necessary task to develop local,distributed or hybrid VVC algorithms for maximization of energy savings.This paper aims to estimate substation energy savings through centralized and decentralized control of inverters of SPV system alongside various VVC devices.Control strategies of each SPV inverter have been accomplished in compliance with IEEE Std.1547-2018.Time-series simulations are carried out on the modified IEEE-123 node test system.By utilizing smart inverters in traditional SPV systems,considerable energy savings can be obtained.These savings can be further increased by incorporating optimal intelligent VVC characteristics(IVVCC).Results show that just by allowing smart inverters on a predefined IVVCC(as per IEEE Std.1547-2018),a reduction of 11.69%in reactive demand and 5.63%in active demand have been acquired when compared with a conventional SPV system.Reactive energy demand is additionally reduced to 48.42%by considering centralized control of VVC devices alongside optimal IVVCC.
摘要高间歇性、高波动性分布式电源(distributed generation,DG)的持续大量接入给配电网的无功电压管理带来严峻挑战,对无功优化的时效性提出了更高要求。现有电压无功控制研究普遍基于单一电压等级和三相平衡网络模型假设,但实际中低压配网两侧的DG、负荷通过配电变压器的耦合互动不断加剧。同时,由于换相缺失、线路不对称布置、负荷及DG不均匀接入等因素,配电网不平衡特性日益加剧,沿用单一电压等级和三相平衡网络可致电压无功控制决策结果不合理甚至不可行。为此,提出一种基于线性规划的中低压不平衡配电网电压无功实时优化方法。具体通过中压配网静止无功发生器(static var generator,SVG)和低压配网分布式光伏逆变器的协调控制,在满足电网运行约束和控制设备能力约束的情况下,实现中低压不平衡配电网节点电压偏差的最小化。同时,为满足高间歇性DG接入对电压无功控制实时性的要求,对上述非线性电压无功优化问题进行线性化逼近,并采用CPLEX求解器对相应线性规划问题进行有效求解。最后,基于某澳大利亚真实配网开展24h仿真,验证了所提基于线性规划的中低压不平衡配电网电压无功实时优化的有效性和优越性。
摘要分布式可再生能源的大规模接入,加剧了有源配电网(Active Distribution Network,ADN)的三相不平衡,容易导致系统电压越限与线损增加。然而,由于当前配电网量测设备安装不全,部分节点负荷数据难以准确获取,因此传统基于全局观测的ADN电压控制方法难以满足实际控制需求。为解决上述问题,提出一种含深度学习代理模型的电压无功控制(Volt/Var control,VVC)进化算法。设计以高速公路神经网络为代理模型,精确拟合局部量测负荷信息、调压控制策略与系统性能指标之间的映射关系。将训练后的代理模型嵌入非支配排序遗传算法的迭代寻优过程中,对电压偏移率、三相不平衡度及线路损耗指标进行直接计算,实现数据驱动的配电网VVC策略快速求取。在改进的IEEE 123节点三相配电网算例上进行测试,验证了所提算法的性能优势及求解效率。