Power system restoration has attracted more attention and made great progress recently. Research progress of the power system restoration from 2006 to 2016 is reviewed in this paper, including black-start, network rec...Power system restoration has attracted more attention and made great progress recently. Research progress of the power system restoration from 2006 to 2016 is reviewed in this paper, including black-start, network reconfiguration and load restoration. Some emerging methods and key techniques are also discussed in the context of the integration of variable renewable energy and development of the smart grid. There is a long way to go to achieve automatic self-healing in bulk power systems because of its extreme complexity. However, rapidly developing artificial intelligence technology will eventually enable the step-by-step dynamic decision-making based on the situation awareness of supervisory control and data acquisition systems(SCADA) and wide area measurement systems(WAMS) in the near future.展开更多
As the power control technology of wind farms develops,the output power of wind farms can be constant,which makes it possible for wind farms to participate in power system restoration.However,due to the uncertainty of...As the power control technology of wind farms develops,the output power of wind farms can be constant,which makes it possible for wind farms to participate in power system restoration.However,due to the uncertainty of wind energy,the actual output power can’t reach a constant dispatch power in all time intervals,resulting in uncertain power sags which may induce the frequency of the system being restored to go outside the security limits.Therefore,it is necessary to optimize the dispatch of wind farms participating in power system restoration.Considering that the probability distribution function(PDF)oftransient power sags is hard to obtain,a robust optimization model is proposed in this paper,which can maximize the output power of wind farms participating in power system restoration.Simulation results demonstrate that the security constraints of the restored system can be kept within security limits when wind farm dispatch is optimized by the proposed method.展开更多
This paper proposes a sectionalizing planning for parallel power system restoration after a complete system blackout.Parallel restoration is conducted in order to reduce the total restoration process time.Physical and...This paper proposes a sectionalizing planning for parallel power system restoration after a complete system blackout.Parallel restoration is conducted in order to reduce the total restoration process time.Physical and operation knowledge of the system,operating personnel experience,and computer simulation are combined in this planning to improve the system restoration and serve as a guidance for system operators/planners.Sectionalizing planning is obtained using discrete evolutionary programming optimization method assisted by heuristic initialization and graph theory approach.Set of transmission lines that should not be restored during parallel restoration process(cut set)is determined in order to sectionalize the system into subsystems or islands.Each island with almost similar restoration time is set as an objective function so as to speed up the resynchronization of the islands.Restoration operation and constraints(black start generator availability,load-generation balance and maintaining acceptable voltage magnitude within each island)is also takeninto account in the course of this planning.The method is validated using the IEEE 39-bus and 118-bus system.Promising results in terms of restoration time was compared to other methods reported in the literature.展开更多
This paper proposes a multi-time collaborative restoration model for integrated electricity-gas distribution sys-tems(IEGDSs)considering multiple resources after extreme weather events.Based on the linearized power fl...This paper proposes a multi-time collaborative restoration model for integrated electricity-gas distribution sys-tems(IEGDSs)considering multiple resources after extreme weather events.Based on the linearized power flow constraints of the unbalanced electrical distribution system(EDS)and gas distribution system(GDS),this problem can be formulated as a mixed-integer linear programming(MILP)model.To improve the efficiency and veracity of the solution,a rolling optimiza-tion based two-stage method is developed with the first stage solved by a linear approximation model,and the second stage solved by real-time updated rolling optimization.By solving the MILP problem using rolling optimization,the proposed model and solution method achieve efficient and reliable collaborative restoration of IEGDS considering multiple resources and unbal-anced operation characteristics of EDS.The effectiveness of the proposed model and method is validated by using an IEGDS made of a 37-bus unbalanced EDS and 11-node GDS.Index Terms-Electricity-gas system,mix-integer linear programming,power system restoration.展开更多
The power system restoration control has a higher uncertainty level than the preventive control of cascading failures. In order to ensure the feasibility of the decision support system of restoration control, a decisi...The power system restoration control has a higher uncertainty level than the preventive control of cascading failures. In order to ensure the feasibility of the decision support system of restoration control, a decision support framework for adaptive restoration control of transmission system is proposed, which can support the coordinated restoration of multiple partitions, coordinated restoration of units and loads, and coordination of multi-partition decision-making process and actual restoration process. The proposed framework is divided into two layers, global coordination layer and partition optimization layer. The upper layer partitions the transmission system according to the power outage scenario, constantly and dynamically adjusts the partitions during the restoration process, and optimizes the time-space decision-making of inter-partition connectivity. For each partition, the lower layer pre-selects restoration targets according to the estimated restoration income, optimizes the corresponding restoration paths, and evaluates the restoration plans according to the expected net income per unit of power consumption. During the restoration process, if the restoration operation such as energizing the outage branch fails, the current restoration plan will be adaptively switched to the sub-optimal one or re-optimized if necessary. The framework includes two operation modes, i.e., the on-line operation mode and training simulation mode, and provides an information interaction interface for collaborative restoration with related distribution systems. The effectiveness and adaptability of the proposed framework is demonstrated by simulations using the modified IEEE 118-bus system.展开更多
Fault restoration techniques have always been crucial for distribution system operators(DSOs).In the last decade,it started to gain more and more importance due to the introduction of output-based regulations where DS...Fault restoration techniques have always been crucial for distribution system operators(DSOs).In the last decade,it started to gain more and more importance due to the introduction of output-based regulations where DSO performances are evaluated according to frequency and duration of energy supply interruptions.The paper presents a tabu-searchbased algorithm able to assist distribution network operational engineers in identifying solutions to restore the energy supply after permanent faults.According to the network property,two objective functions are considered to optimize either reliability or resiliency.The mathematical formulation includes the traditional feeders,number of switching operation limit,and radiality constraints.Thanks to the DSO of Milan,Unareti,the proposed algorithm has been tested on a real distribution network to investigate its effectiveness.展开更多
This paper proposes a voltage source converter (VSC) -based AC-DC hybrid distribution system (HDS) resilient model to mitigate power outages caused by wildfires. Before a wildfire happens, the public-safety power shut...This paper proposes a voltage source converter (VSC) -based AC-DC hybrid distribution system (HDS) resilient model to mitigate power outages caused by wildfires. Before a wildfire happens, the public-safety power shutoff (PSPS) strategy is applied to actively cut some vulnerable lines which may easily cause wildfires, and reinforce some lines that are connected to critical loads. To mitigate load shedding caused by active line disconnection in the PSPS strategy, network reconfiguration is applied before the wildfire occurrence. During the restoration period, repair crews (RCs) repair faulted lines, and network reconfiguration is also taken into consideration in the recovery strategy to pick up critical loads. Since there exists possible errors in the wildfire prediction, several different scenarios of wildfire occurrence have been taken into consideration, leading to the proposition of a stochastic multi-period resilient model for the VSC-based AC-DC HDS. To accelerate the computational performance, a progressive hedging algorithm has been applied to solve the stochastic model which can be written as a mixed-integer linear program. The proposed model is verified on a 106-bus AC-DC HDS under wildfire conditions, and the result shows the proposed model not only can improve the system resilience but also accelerate computational speed.展开更多
基金supported by National Basic Research Program of China(973 Program)(No.2012CB215101)
文摘Power system restoration has attracted more attention and made great progress recently. Research progress of the power system restoration from 2006 to 2016 is reviewed in this paper, including black-start, network reconfiguration and load restoration. Some emerging methods and key techniques are also discussed in the context of the integration of variable renewable energy and development of the smart grid. There is a long way to go to achieve automatic self-healing in bulk power systems because of its extreme complexity. However, rapidly developing artificial intelligence technology will eventually enable the step-by-step dynamic decision-making based on the situation awareness of supervisory control and data acquisition systems(SCADA) and wide area measurement systems(WAMS) in the near future.
基金supported by the National Natural Science Foundation of China(No.51507080)the Science and Technology Project of State Grid Corporation of China(5228001600DT)
文摘As the power control technology of wind farms develops,the output power of wind farms can be constant,which makes it possible for wind farms to participate in power system restoration.However,due to the uncertainty of wind energy,the actual output power can’t reach a constant dispatch power in all time intervals,resulting in uncertain power sags which may induce the frequency of the system being restored to go outside the security limits.Therefore,it is necessary to optimize the dispatch of wind farms participating in power system restoration.Considering that the probability distribution function(PDF)oftransient power sags is hard to obtain,a robust optimization model is proposed in this paper,which can maximize the output power of wind farms participating in power system restoration.Simulation results demonstrate that the security constraints of the restored system can be kept within security limits when wind farm dispatch is optimized by the proposed method.
文摘This paper proposes a sectionalizing planning for parallel power system restoration after a complete system blackout.Parallel restoration is conducted in order to reduce the total restoration process time.Physical and operation knowledge of the system,operating personnel experience,and computer simulation are combined in this planning to improve the system restoration and serve as a guidance for system operators/planners.Sectionalizing planning is obtained using discrete evolutionary programming optimization method assisted by heuristic initialization and graph theory approach.Set of transmission lines that should not be restored during parallel restoration process(cut set)is determined in order to sectionalize the system into subsystems or islands.Each island with almost similar restoration time is set as an objective function so as to speed up the resynchronization of the islands.Restoration operation and constraints(black start generator availability,load-generation balance and maintaining acceptable voltage magnitude within each island)is also takeninto account in the course of this planning.The method is validated using the IEEE 39-bus and 118-bus system.Promising results in terms of restoration time was compared to other methods reported in the literature.
基金supported by the National Natural Science Foundation of China under Grant(51907122)National Key R&D Program of China under Giant(2018YFB0905000)Science and Technology Project of State Grid Corporation of China(SGTJDK00DWJS1800232).
文摘This paper proposes a multi-time collaborative restoration model for integrated electricity-gas distribution sys-tems(IEGDSs)considering multiple resources after extreme weather events.Based on the linearized power flow constraints of the unbalanced electrical distribution system(EDS)and gas distribution system(GDS),this problem can be formulated as a mixed-integer linear programming(MILP)model.To improve the efficiency and veracity of the solution,a rolling optimiza-tion based two-stage method is developed with the first stage solved by a linear approximation model,and the second stage solved by real-time updated rolling optimization.By solving the MILP problem using rolling optimization,the proposed model and solution method achieve efficient and reliable collaborative restoration of IEGDS considering multiple resources and unbal-anced operation characteristics of EDS.The effectiveness of the proposed model and method is validated by using an IEGDS made of a 37-bus unbalanced EDS and 11-node GDS.Index Terms-Electricity-gas system,mix-integer linear programming,power system restoration.
基金This work was supported in part by the China State Grid Corporation project of the Key Technologies of Power Grid Proactive Support for Energy Transition (No. 5100-202040325A-0-0-00).
文摘The power system restoration control has a higher uncertainty level than the preventive control of cascading failures. In order to ensure the feasibility of the decision support system of restoration control, a decision support framework for adaptive restoration control of transmission system is proposed, which can support the coordinated restoration of multiple partitions, coordinated restoration of units and loads, and coordination of multi-partition decision-making process and actual restoration process. The proposed framework is divided into two layers, global coordination layer and partition optimization layer. The upper layer partitions the transmission system according to the power outage scenario, constantly and dynamically adjusts the partitions during the restoration process, and optimizes the time-space decision-making of inter-partition connectivity. For each partition, the lower layer pre-selects restoration targets according to the estimated restoration income, optimizes the corresponding restoration paths, and evaluates the restoration plans according to the expected net income per unit of power consumption. During the restoration process, if the restoration operation such as energizing the outage branch fails, the current restoration plan will be adaptively switched to the sub-optimal one or re-optimized if necessary. The framework includes two operation modes, i.e., the on-line operation mode and training simulation mode, and provides an information interaction interface for collaborative restoration with related distribution systems. The effectiveness and adaptability of the proposed framework is demonstrated by simulations using the modified IEEE 118-bus system.
文摘Fault restoration techniques have always been crucial for distribution system operators(DSOs).In the last decade,it started to gain more and more importance due to the introduction of output-based regulations where DSO performances are evaluated according to frequency and duration of energy supply interruptions.The paper presents a tabu-searchbased algorithm able to assist distribution network operational engineers in identifying solutions to restore the energy supply after permanent faults.According to the network property,two objective functions are considered to optimize either reliability or resiliency.The mathematical formulation includes the traditional feeders,number of switching operation limit,and radiality constraints.Thanks to the DSO of Milan,Unareti,the proposed algorithm has been tested on a real distribution network to investigate its effectiveness.
基金supported in part by National Key Research and Development Program of China(2022YFA1004600)in part by the National Natural Science Foundation of China(51977166,52277123)in part by the Natural Science Foundation of Shaanxi Province(2022JC-19)。
文摘This paper proposes a voltage source converter (VSC) -based AC-DC hybrid distribution system (HDS) resilient model to mitigate power outages caused by wildfires. Before a wildfire happens, the public-safety power shutoff (PSPS) strategy is applied to actively cut some vulnerable lines which may easily cause wildfires, and reinforce some lines that are connected to critical loads. To mitigate load shedding caused by active line disconnection in the PSPS strategy, network reconfiguration is applied before the wildfire occurrence. During the restoration period, repair crews (RCs) repair faulted lines, and network reconfiguration is also taken into consideration in the recovery strategy to pick up critical loads. Since there exists possible errors in the wildfire prediction, several different scenarios of wildfire occurrence have been taken into consideration, leading to the proposition of a stochastic multi-period resilient model for the VSC-based AC-DC HDS. To accelerate the computational performance, a progressive hedging algorithm has been applied to solve the stochastic model which can be written as a mixed-integer linear program. The proposed model is verified on a 106-bus AC-DC HDS under wildfire conditions, and the result shows the proposed model not only can improve the system resilience but also accelerate computational speed.
