In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent...In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent and sustainable supply of electricity.A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability.The choice of optimization technique for economic power dispatching from DGs depends on a number of factors,such as the size and complexity of the power system,the availability of computational resources,and the specific requirements of the application.Optimization techniques for economic power dispatching from distributed generations(DGs)can be classified into two main categories:(i)Classical optimization techniques,(ii)Heuristic optimization techniques.In classical optimization techniques,the linear programming(LP)model is one of the most popular optimization methods.Utilizing the LP model,power demand and network constraints are met while minimizing the overall cost of generating electricity from DGs.This approach is efficient in determining the best DGs dispatch and is capable of handling challenging optimization issues in the large-scale system including renewables.The quadratic programming(QP)model,a classical optimization technique,is a further popular optimization method,to consider non-linearity.The QP model can take into account the quadratic cost of energy production,with consideration constraints like network capacity,voltage,and frequency.The metaheuristic optimization techniques are also used for economic power dispatching from DGs,which include genetic algorithms(GA),particle swarm optimization(PSO),and ant colony optimization(ACO).Also,Some researchers are developing hybrid optimization techniques that combine elements of classical and heuristic optimization techniques with the incorporation of droop control,predictive control,and fuzzy-based methods.These methods can deal with large-scale systems with many objectives and non-linear,non-convex optimization issues.The most popular approaches are the LP and QP models,while more difficult problems are handled using metaheuristic optimization techniques.In summary,in order to increase efficiency,reduce costs,and ensure a consistent supply of electricity,optimization techniques are essential tools used in economic power dispatching from DGs.展开更多
This study proposes a wind farm active power dispatching(WFAPD) algorithm based on the grey incidence method, which does not rely on an accurate mathematical model of wind turbines. Based on the wind turbine start-sto...This study proposes a wind farm active power dispatching(WFAPD) algorithm based on the grey incidence method, which does not rely on an accurate mathematical model of wind turbines. Based on the wind turbine start-stop data at different wind speeds, the weighting coefficients, which are the participation degrees of a variable speed system and a variable pitch system in power regulation, are obtained using the grey incidence method. The incidence coefficient curve is fitted by the B-spline function at a full range of wind speeds, and the power regulation capacity of all wind turbines is obtained. Finally, the WFAPD algorithm, which is based on the regulating capacity of each wind turbine, is compared with the wind speed weighting power dispatching(WSWPD) algorithm in MATLAB. The simulation results show that the active power fluctuation of the wind farm is smaller, the rotating speed of wind turbines is smoother, and the fatigue load of highspeed turbines is effectively reduced.展开更多
This paper presents a pooled-neighbor swarm intelligence approach (PNSIA) to optimal reactive power dispatch and voltage control of power systems. The proposed approach uses more particles’ information to control the...This paper presents a pooled-neighbor swarm intelligence approach (PNSIA) to optimal reactive power dispatch and voltage control of power systems. The proposed approach uses more particles’ information to control the mutation operation. The proposed PNSIA algorithm is also extended to handle mixed variables, such as transformer taps and reactive power source in- stallation, using a simple scheme. PNSIA applied for optimal power system reactive power dispatch is evaluated on an IEEE 30-bus power system and a practical 118-bus power system in which the control of bus voltages, tap position of transformers and reactive power sources are involved to minimize the transmission loss of the power system. Simulation results showed that the proposed approach is superior to current methods for finding the optimal solution, in terms of both solution quality and algorithm robustness.展开更多
With the development and application of energy Internet technology,the collaborative interaction of“source network,load and storage”has becomethe development trend of power grid dispatching.The large-scale access of...With the development and application of energy Internet technology,the collaborative interaction of“source network,load and storage”has becomethe development trend of power grid dispatching.The large-scale access of renewableenergy on the load side,the unified management of adjustable loads,and theparticipation of multiple parties in energy operations have put forward requirementsfor the safety,credibility,openness,and transparency of the load dispatchingenvironment.Under the environment of carbon emission reduction,the paperproposed an architecture of the scheduling data blockchain,based on the in-depthstudy of blockchain.Moreover,smart contracts are used to realize the applicationscenario of load dispatching instruction evidence on the blockchain.The contentand storage mode of scheduling instruction evidence on blockchain are studied.And different storage modes are adopted according to the actual needs.Andthe smart contract system realizes the evidence generation of power dispatchinginstruction.This is the basis for the normal circulation of power dispatchinginstruction evidence.The research significance of this paper is highlighted as follows.The data and information generated in the power dispatching process arestored as evidence.On the one hand,it can provide a basis for settlement betweenpower production and dispatching companies and power users.On the other hand,it can prepare for distributed transactions in the power grid under the environmentof carbon emission reduction.展开更多
In recent years, most of the leakage faults that may occur in the rectifying power supply control system of all urban rail network traffic in China are rectifying power supply equipment such as traction rectifying pow...In recent years, most of the leakage faults that may occur in the rectifying power supply control system of all urban rail network traffic in China are rectifying power supply equipment such as traction rectifying power supply transformer of urban traction substation. When multiple high-speed trains start at the same time for several times or start at the same time within a short interval;Short-term or peak line currents generated may overwhelm them directly;Cause them to catch fire and burn;Even cause the line current to stop normal operation for a period of time. The heavy will cause the whole train line long or short time current stop normal operation.展开更多
In the process of building smart grid, dispatching automation technology is an indispensable and important component. With the continuous expansion of the power grid scale and the increase of the proportion of new ene...In the process of building smart grid, dispatching automation technology is an indispensable and important component. With the continuous expansion of the power grid scale and the increase of the proportion of new energy sources connected to the grid, a large AC/DC hybrid power grid will be formed, and many new problems and challenges will emerge continuously. When dispatching personnel manage the power grid, they must pay full attention to the application of key technologies of smart grid dispatching automation, ensure people's demand for electricity, promote the development of smart grid, and lay a solid foundation of power and energy for the continuous progress of economy and society.展开更多
In the subway power dispatching monitoring system, the actual power dispatching workstation and the virtual power supply system are combined to realize the simulation of the subway power dispatching monitoring system....In the subway power dispatching monitoring system, the actual power dispatching workstation and the virtual power supply system are combined to realize the simulation of the subway power dispatching monitoring system. At the same time, the system is universal and can be popularized and applied to the operation and control of other subway line power supply systems. At present, the system has been used in the operation, control and monitoring of subway power supply system by subway power dispatchers which has been mature in various cities, which can effectively improve the work efficiency of subway power dispatchers and meet the actual application needs. It is of great practical significance to establish a complete and systematic subway power dispatching and monitoring system.展开更多
At this stage, the rapid social progress, the development of China's subway engineering construction has also been improved. Relevant research points out that the future metro power dispatching information managem...At this stage, the rapid social progress, the development of China's subway engineering construction has also been improved. Relevant research points out that the future metro power dispatching information management system should have high precision and powerful real-time monitoring function, which can accurately locate the fault location while carrying out early warning. In addition, through the above process, the related failure events can be specially handled to form the whole process monitoring of the whole system. In the process of establishing the knowledge base, it belongs to the reference process of historical experience information, so as to improve the efficiency of solving power failure and meet the development needs of the whole system.展开更多
Besides common characteristics of wind power,there are some special characteristics in China power system,including large-scale,long distance transmission and lack of flexible regulating power sources.These special ch...Besides common characteristics of wind power,there are some special characteristics in China power system,including large-scale,long distance transmission and lack of flexible regulating power sources.These special characteristics make power dispatch more challenging in China.Many studies have been carried out and some improvements are presented including wind power monitoring and control as well as evaluation of wind power integration capabilities.As a demonstration project,the technologies are integrated into the energy management system and are implemented in the Northwest China power system.They provide effective measures for wind power dispatch in the grid.展开更多
Distributed photovoltaic power (PV) is the main development model of distributed generation. It is necessary to research on dispatching and operation management with large-scale distributed PV connected. This paper an...Distributed photovoltaic power (PV) is the main development model of distributed generation. It is necessary to research on dispatching and operation management with large-scale distributed PV connected. This paper analyzes development status, technical requirement and dispatching and operation management situation of distributed PV in Germany and China. Then introduce the preparation of distributed PV dispatching and operation management criterion. Through summarizing the experiences and lessons of large-scale distributed PV development in Germany, it gives advice to the development of distributed PV dispatching and operation management in China.展开更多
With the development of power systems, power grid within a control area becomes much more complicated due to increasing number of nodes and renewable energy interconnections. The role of power system control center is...With the development of power systems, power grid within a control area becomes much more complicated due to increasing number of nodes and renewable energy interconnections. The role of power system control center is more critical in maintaining system reliable and security operations. Latest developed information and communication technologies provide a platform to enhance the functions and performance of power system control center. Smart power dispatch concept will be the trend of future control center development. In this paper, we start from the human factors of control center design and propose operation indices to reduce the information presented to the system operator. The operation indices will be the important criteria in situation awareness of a power grid. Past, present, future and capability states of a power grid are also proposed to provide better visions to the operator of system conditions. The basic ideas of operation indices and operation states are discussed in the paper. In the end, the design factors for a power dispatch cockpit are discussed.展开更多
The ever-increasing integration of stochastic renewable energy sources into power systems operation is making the supply-demand balance more challenging.While joint chance-constrained methods are equipped to model the...The ever-increasing integration of stochastic renewable energy sources into power systems operation is making the supply-demand balance more challenging.While joint chance-constrained methods are equipped to model these complexities and uncertainties,solving these problems using traditional iterative solvers is often time-consuming,limiting their suitability for real-time applications.To overcome the shortcomings of today’s solvers,we propose a fast,scalable,and explainable machine learning-based optimization proxy.Our solution,called Learning to Optimize the Optimization of Joint Chance-Constrained Problems(LOOP−JCCP),is iteration-free and solves the underlying problem in a single-shot.Our model uses a polyhedral reformulation of the original problem to manage constraint violations and ensure solution feasibility across various scenarios through customizable probability settings.To this end,we build on our recent deterministic solution(LOOP−LC2.0)by incorporating a set aggregator module to handle uncertain sample sets of varying sizes and complexities.Our results verify the feasibility of our near-optimal solutions for joint chance-constrained power dispatch scenarios.Additionally,our feasibility guarantees increase the transparency and interpretability of our method,which is essential for operators to trust the outcomes.We showcase the effectiveness of our model in solving the stochastic energy management problem of Virtual Power Plants(VPPs).Our theoretical analysis,supported by empirical evidence,reveals strong flexibility in parameter tuning,adaptability to diverse datasets,and significantly improved computational speed.展开更多
The increasing integration of intermittent renewable energy sources into distribution networks has exerted significant pressure on the frequency regulation of power systems.Meanwhile,integrating small-capacity battery...The increasing integration of intermittent renewable energy sources into distribution networks has exerted significant pressure on the frequency regulation of power systems.Meanwhile,integrating small-capacity battery energy storage systems into distribution network is a growing trend in the construction of virtual power plants(VPPs),which offer great potential advantages in improving the system frequency regulation capabilities.However,the process of power dispatch for VPPs may be hindered by imperfections in the communication network,which affects their frequency control performance.Simultaneously,the economic benefits associated with their frequency control services are often overlooked.As such,we propose a codesign method of power dispatch with dynamic power regulation and communication transmission optimization for frequency control in VPPs.First,a joint design scheme of power dispatch and routing optimization under cloud-edge collaborations is proposed.This scheme encompasses a power dispatch method considering the influences of communication network and a routing optimization policy based on graph convolutional neural networks,both of which are designed to ensure the accurate and real-time frequency control service.Further,we propose a dynamic power regulation strategy under edge-edge collaborations.Specifically,according to the established correction control objective,an adaptive distributed auction algorithm(ADAA)based dynamic power regulation control method is designed to determine the optimal regulation power of VPPs,thereby improving the economic benefits of frequency control service.Finally,the simulation results validate the feasibility and superiority of the proposed co-design method for frequency control.展开更多
Peer-to-peer(P2P)energy trading in active distribution networks(ADNs)plays a pivotal role in promoting the efficient consumption of renewable energy sources.However,it is challenging to effectively coordinate the powe...Peer-to-peer(P2P)energy trading in active distribution networks(ADNs)plays a pivotal role in promoting the efficient consumption of renewable energy sources.However,it is challenging to effectively coordinate the power dispatch of ADNs and P2P energy trading while preserving the privacy of different physical interests.Hence,this paper proposes a soft actor-critic algorithm incorporating distributed trading control(SAC-DTC)to tackle the optimal power dispatch of ADNs and the P2P energy trading considering privacy preservation among prosumers.First,the soft actor-critic(SAC)algorithm is used to optimize the control strategy of device in ADNs to minimize the operation cost,and the primary environmental information of the ADN at this point is published to prosumers.Then,a distributed generalized fast dual ascent method is used to iterate the trading process of prosumers and maximize their revenues.Subsequently,the results of trading are encrypted based on the differential privacy technique and returned to the ADN.Finally,the social welfare value consisting of ADN operation cost and P2P market revenue is utilized as a reward value to update network parameters and control strategies of the deep reinforcement learning.Simulation results show that the proposed SAC-DTC algorithm reduces the ADN operation cost,boosts the P2P market revenue,maximizes the social welfare,and exhibits high computational accuracy,demonstrating its practical application to the operation of power systems and power markets.展开更多
Combined Heat and Power Economic Dispatch(CHPED)is an important problem in the energy field,and it is beneficial for improving the utilization efficiency of power and heat energies.This paper proposes a Modified Genet...Combined Heat and Power Economic Dispatch(CHPED)is an important problem in the energy field,and it is beneficial for improving the utilization efficiency of power and heat energies.This paper proposes a Modified Genetic Algorithm(MGA)to determine the power and heat outputs of three kinds of units for CHPED.First,MGA replaces the simulated binary crossover by a new one based on the uniform and guassian distributions,and its convergence can be enhanced.Second,MGA modi-fies the mutation operator by introducing a disturbance coefficient based on guassian distribution,which can decrease the risk of being trapped into local optima.Eight instances with or without prohibited operating zones are used to investigate the efficiencies of MGA and other four genetic algorithms for CHPED.In comparison with the other algorithms,MGA has reduced generation costs by at least 562.73$,1068.7$,522.68$and 1016.24$,respectively,for instances 3,4,7 and 8,and it has reduced generation costs by at most 848.22$,3642.85$,897.63$and 3812.65$,respectively,for instances 3,4,7 and 8.Therefore,MGA has desirable convergence and stability for CHPED in comparison with the other four genetic algorithms.展开更多
Photovoltaic(PV)power generation has highly penetrated in distribution networks,providing clean and sustainable energy.However,its uncertain and intermittent power outputs significantly impair network operation,leadin...Photovoltaic(PV)power generation has highly penetrated in distribution networks,providing clean and sustainable energy.However,its uncertain and intermittent power outputs significantly impair network operation,leading to unexpected power loss and voltage fluctuation.To address the uncertainties,this paper proposes a multi-timescale affinely adjustable robust reactive power dispatch(MTAAR-RPD)method to reduce the network power losses as well as alleviate voltage deviations and fluctuations.The MTAAR-RPD aims to coordinate on-load tap changers(OLTCs),capacitor banks(CBs),and PV inverters through a three-stage structure which covers multiple timescales of“hour-minute-second”.The first stage schedules CBs and OLTCs hourly while the second stage dispatches the base reactive power outputs of PV inverter every 15 min.The third stage affinely adjusts the inverter reactive power output based on an optimized Q-P droop controller in real time.The three stages are coordinately optimized by an affinely adjustable robust optimization method.A solution algorithm based on a cutting plane algorithm is developed to solve the optimization problem effectively.The proposed method is verified through theoretical analysis and numerical simulations.展开更多
文摘In the increasingly decentralized energy environment,economical power dispatching from distributed generations(DGs)is crucial to minimizing operating costs,optimizing resource utilization,and guaranteeing a consistent and sustainable supply of electricity.A comprehensive review of optimization techniques for economic power dispatching from distributed generations is imperative to identify the most effective strategies for minimizing operational costs while maintaining grid stability and sustainability.The choice of optimization technique for economic power dispatching from DGs depends on a number of factors,such as the size and complexity of the power system,the availability of computational resources,and the specific requirements of the application.Optimization techniques for economic power dispatching from distributed generations(DGs)can be classified into two main categories:(i)Classical optimization techniques,(ii)Heuristic optimization techniques.In classical optimization techniques,the linear programming(LP)model is one of the most popular optimization methods.Utilizing the LP model,power demand and network constraints are met while minimizing the overall cost of generating electricity from DGs.This approach is efficient in determining the best DGs dispatch and is capable of handling challenging optimization issues in the large-scale system including renewables.The quadratic programming(QP)model,a classical optimization technique,is a further popular optimization method,to consider non-linearity.The QP model can take into account the quadratic cost of energy production,with consideration constraints like network capacity,voltage,and frequency.The metaheuristic optimization techniques are also used for economic power dispatching from DGs,which include genetic algorithms(GA),particle swarm optimization(PSO),and ant colony optimization(ACO).Also,Some researchers are developing hybrid optimization techniques that combine elements of classical and heuristic optimization techniques with the incorporation of droop control,predictive control,and fuzzy-based methods.These methods can deal with large-scale systems with many objectives and non-linear,non-convex optimization issues.The most popular approaches are the LP and QP models,while more difficult problems are handled using metaheuristic optimization techniques.In summary,in order to increase efficiency,reduce costs,and ensure a consistent supply of electricity,optimization techniques are essential tools used in economic power dispatching from DGs.
基金supported by the Special Scientific Research Project of the Shaanxi Provincial Education Department (22JK0414)。
文摘This study proposes a wind farm active power dispatching(WFAPD) algorithm based on the grey incidence method, which does not rely on an accurate mathematical model of wind turbines. Based on the wind turbine start-stop data at different wind speeds, the weighting coefficients, which are the participation degrees of a variable speed system and a variable pitch system in power regulation, are obtained using the grey incidence method. The incidence coefficient curve is fitted by the B-spline function at a full range of wind speeds, and the power regulation capacity of all wind turbines is obtained. Finally, the WFAPD algorithm, which is based on the regulating capacity of each wind turbine, is compared with the wind speed weighting power dispatching(WSWPD) algorithm in MATLAB. The simulation results show that the active power fluctuation of the wind farm is smaller, the rotating speed of wind turbines is smoother, and the fatigue load of highspeed turbines is effectively reduced.
基金Project supported by the National Natural Science Foundation ofChina (No. 60421002) and the Outstanding Young Research Inves-tigator Fund (No. 60225006), China
文摘This paper presents a pooled-neighbor swarm intelligence approach (PNSIA) to optimal reactive power dispatch and voltage control of power systems. The proposed approach uses more particles’ information to control the mutation operation. The proposed PNSIA algorithm is also extended to handle mixed variables, such as transformer taps and reactive power source in- stallation, using a simple scheme. PNSIA applied for optimal power system reactive power dispatch is evaluated on an IEEE 30-bus power system and a practical 118-bus power system in which the control of bus voltages, tap position of transformers and reactive power sources are involved to minimize the transmission loss of the power system. Simulation results showed that the proposed approach is superior to current methods for finding the optimal solution, in terms of both solution quality and algorithm robustness.
基金supported by Science and Technology Program of State Grid Corporation of China under Grant(No.5100-202155319A-0-0-00).
文摘With the development and application of energy Internet technology,the collaborative interaction of“source network,load and storage”has becomethe development trend of power grid dispatching.The large-scale access of renewableenergy on the load side,the unified management of adjustable loads,and theparticipation of multiple parties in energy operations have put forward requirementsfor the safety,credibility,openness,and transparency of the load dispatchingenvironment.Under the environment of carbon emission reduction,the paperproposed an architecture of the scheduling data blockchain,based on the in-depthstudy of blockchain.Moreover,smart contracts are used to realize the applicationscenario of load dispatching instruction evidence on the blockchain.The contentand storage mode of scheduling instruction evidence on blockchain are studied.And different storage modes are adopted according to the actual needs.Andthe smart contract system realizes the evidence generation of power dispatchinginstruction.This is the basis for the normal circulation of power dispatchinginstruction evidence.The research significance of this paper is highlighted as follows.The data and information generated in the power dispatching process arestored as evidence.On the one hand,it can provide a basis for settlement betweenpower production and dispatching companies and power users.On the other hand,it can prepare for distributed transactions in the power grid under the environmentof carbon emission reduction.
文摘In recent years, most of the leakage faults that may occur in the rectifying power supply control system of all urban rail network traffic in China are rectifying power supply equipment such as traction rectifying power supply transformer of urban traction substation. When multiple high-speed trains start at the same time for several times or start at the same time within a short interval;Short-term or peak line currents generated may overwhelm them directly;Cause them to catch fire and burn;Even cause the line current to stop normal operation for a period of time. The heavy will cause the whole train line long or short time current stop normal operation.
文摘In the process of building smart grid, dispatching automation technology is an indispensable and important component. With the continuous expansion of the power grid scale and the increase of the proportion of new energy sources connected to the grid, a large AC/DC hybrid power grid will be formed, and many new problems and challenges will emerge continuously. When dispatching personnel manage the power grid, they must pay full attention to the application of key technologies of smart grid dispatching automation, ensure people's demand for electricity, promote the development of smart grid, and lay a solid foundation of power and energy for the continuous progress of economy and society.
文摘In the subway power dispatching monitoring system, the actual power dispatching workstation and the virtual power supply system are combined to realize the simulation of the subway power dispatching monitoring system. At the same time, the system is universal and can be popularized and applied to the operation and control of other subway line power supply systems. At present, the system has been used in the operation, control and monitoring of subway power supply system by subway power dispatchers which has been mature in various cities, which can effectively improve the work efficiency of subway power dispatchers and meet the actual application needs. It is of great practical significance to establish a complete and systematic subway power dispatching and monitoring system.
文摘At this stage, the rapid social progress, the development of China's subway engineering construction has also been improved. Relevant research points out that the future metro power dispatching information management system should have high precision and powerful real-time monitoring function, which can accurately locate the fault location while carrying out early warning. In addition, through the above process, the related failure events can be specially handled to form the whole process monitoring of the whole system. In the process of establishing the knowledge base, it belongs to the reference process of historical experience information, so as to improve the efficiency of solving power failure and meet the development needs of the whole system.
基金supported by National Natural Science Foundation of China(No.51177019,61074100,60974036)Doctoral Fund of Ministry of Education of China(No.20090092110020)and the State Grid Corporation of China
文摘Besides common characteristics of wind power,there are some special characteristics in China power system,including large-scale,long distance transmission and lack of flexible regulating power sources.These special characteristics make power dispatch more challenging in China.Many studies have been carried out and some improvements are presented including wind power monitoring and control as well as evaluation of wind power integration capabilities.As a demonstration project,the technologies are integrated into the energy management system and are implemented in the Northwest China power system.They provide effective measures for wind power dispatch in the grid.
文摘Distributed photovoltaic power (PV) is the main development model of distributed generation. It is necessary to research on dispatching and operation management with large-scale distributed PV connected. This paper analyzes development status, technical requirement and dispatching and operation management situation of distributed PV in Germany and China. Then introduce the preparation of distributed PV dispatching and operation management criterion. Through summarizing the experiences and lessons of large-scale distributed PV development in Germany, it gives advice to the development of distributed PV dispatching and operation management in China.
文摘With the development of power systems, power grid within a control area becomes much more complicated due to increasing number of nodes and renewable energy interconnections. The role of power system control center is more critical in maintaining system reliable and security operations. Latest developed information and communication technologies provide a platform to enhance the functions and performance of power system control center. Smart power dispatch concept will be the trend of future control center development. In this paper, we start from the human factors of control center design and propose operation indices to reduce the information presented to the system operator. The operation indices will be the important criteria in situation awareness of a power grid. Past, present, future and capability states of a power grid are also proposed to provide better visions to the operator of system conditions. The basic ideas of operation indices and operation states are discussed in the paper. In the end, the design factors for a power dispatch cockpit are discussed.
基金supported by National Science Foundation(NSF),Grant No.#2313768:“Collaborative Research:Learning-Assisted Estimation and Management of Flexible Energy Resources in Active Distribution Networks”,U.S.
文摘The ever-increasing integration of stochastic renewable energy sources into power systems operation is making the supply-demand balance more challenging.While joint chance-constrained methods are equipped to model these complexities and uncertainties,solving these problems using traditional iterative solvers is often time-consuming,limiting their suitability for real-time applications.To overcome the shortcomings of today’s solvers,we propose a fast,scalable,and explainable machine learning-based optimization proxy.Our solution,called Learning to Optimize the Optimization of Joint Chance-Constrained Problems(LOOP−JCCP),is iteration-free and solves the underlying problem in a single-shot.Our model uses a polyhedral reformulation of the original problem to manage constraint violations and ensure solution feasibility across various scenarios through customizable probability settings.To this end,we build on our recent deterministic solution(LOOP−LC2.0)by incorporating a set aggregator module to handle uncertain sample sets of varying sizes and complexities.Our results verify the feasibility of our near-optimal solutions for joint chance-constrained power dispatch scenarios.Additionally,our feasibility guarantees increase the transparency and interpretability of our method,which is essential for operators to trust the outcomes.We showcase the effectiveness of our model in solving the stochastic energy management problem of Virtual Power Plants(VPPs).Our theoretical analysis,supported by empirical evidence,reveals strong flexibility in parameter tuning,adaptability to diverse datasets,and significantly improved computational speed.
基金supported in part by the Major Program of the National Natural Science Foundation of China(No.62293504)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX24_1212)。
文摘The increasing integration of intermittent renewable energy sources into distribution networks has exerted significant pressure on the frequency regulation of power systems.Meanwhile,integrating small-capacity battery energy storage systems into distribution network is a growing trend in the construction of virtual power plants(VPPs),which offer great potential advantages in improving the system frequency regulation capabilities.However,the process of power dispatch for VPPs may be hindered by imperfections in the communication network,which affects their frequency control performance.Simultaneously,the economic benefits associated with their frequency control services are often overlooked.As such,we propose a codesign method of power dispatch with dynamic power regulation and communication transmission optimization for frequency control in VPPs.First,a joint design scheme of power dispatch and routing optimization under cloud-edge collaborations is proposed.This scheme encompasses a power dispatch method considering the influences of communication network and a routing optimization policy based on graph convolutional neural networks,both of which are designed to ensure the accurate and real-time frequency control service.Further,we propose a dynamic power regulation strategy under edge-edge collaborations.Specifically,according to the established correction control objective,an adaptive distributed auction algorithm(ADAA)based dynamic power regulation control method is designed to determine the optimal regulation power of VPPs,thereby improving the economic benefits of frequency control service.Finally,the simulation results validate the feasibility and superiority of the proposed co-design method for frequency control.
基金supported by the National Natural Science Foundation of China(No.52177085).
文摘Peer-to-peer(P2P)energy trading in active distribution networks(ADNs)plays a pivotal role in promoting the efficient consumption of renewable energy sources.However,it is challenging to effectively coordinate the power dispatch of ADNs and P2P energy trading while preserving the privacy of different physical interests.Hence,this paper proposes a soft actor-critic algorithm incorporating distributed trading control(SAC-DTC)to tackle the optimal power dispatch of ADNs and the P2P energy trading considering privacy preservation among prosumers.First,the soft actor-critic(SAC)algorithm is used to optimize the control strategy of device in ADNs to minimize the operation cost,and the primary environmental information of the ADN at this point is published to prosumers.Then,a distributed generalized fast dual ascent method is used to iterate the trading process of prosumers and maximize their revenues.Subsequently,the results of trading are encrypted based on the differential privacy technique and returned to the ADN.Finally,the social welfare value consisting of ADN operation cost and P2P market revenue is utilized as a reward value to update network parameters and control strategies of the deep reinforcement learning.Simulation results show that the proposed SAC-DTC algorithm reduces the ADN operation cost,boosts the P2P market revenue,maximizes the social welfare,and exhibits high computational accuracy,demonstrating its practical application to the operation of power systems and power markets.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant 61873272,62073327in part by the Natural Science Foundation of Jiangsu Province under Grant BK20200086,BK20200631.
文摘Combined Heat and Power Economic Dispatch(CHPED)is an important problem in the energy field,and it is beneficial for improving the utilization efficiency of power and heat energies.This paper proposes a Modified Genetic Algorithm(MGA)to determine the power and heat outputs of three kinds of units for CHPED.First,MGA replaces the simulated binary crossover by a new one based on the uniform and guassian distributions,and its convergence can be enhanced.Second,MGA modi-fies the mutation operator by introducing a disturbance coefficient based on guassian distribution,which can decrease the risk of being trapped into local optima.Eight instances with or without prohibited operating zones are used to investigate the efficiencies of MGA and other four genetic algorithms for CHPED.In comparison with the other algorithms,MGA has reduced generation costs by at least 562.73$,1068.7$,522.68$and 1016.24$,respectively,for instances 3,4,7 and 8,and it has reduced generation costs by at most 848.22$,3642.85$,897.63$and 3812.65$,respectively,for instances 3,4,7 and 8.Therefore,MGA has desirable convergence and stability for CHPED in comparison with the other four genetic algorithms.
基金supported in part by the Scientific Research Foundation of Nanjing University of Science and Technology(No.AE89991/255)in part by Jiangsu Provincial Key Laboratory of Smart Grid Technology and Equipment Project,Southeast University+1 种基金in part by the National Natural Science Foundation of China(No.51677025)in part by the Science and Technology Project of State Grid Corporation(No.SGMD0000YXJS1900502)。
文摘Photovoltaic(PV)power generation has highly penetrated in distribution networks,providing clean and sustainable energy.However,its uncertain and intermittent power outputs significantly impair network operation,leading to unexpected power loss and voltage fluctuation.To address the uncertainties,this paper proposes a multi-timescale affinely adjustable robust reactive power dispatch(MTAAR-RPD)method to reduce the network power losses as well as alleviate voltage deviations and fluctuations.The MTAAR-RPD aims to coordinate on-load tap changers(OLTCs),capacitor banks(CBs),and PV inverters through a three-stage structure which covers multiple timescales of“hour-minute-second”.The first stage schedules CBs and OLTCs hourly while the second stage dispatches the base reactive power outputs of PV inverter every 15 min.The third stage affinely adjusts the inverter reactive power output based on an optimized Q-P droop controller in real time.The three stages are coordinately optimized by an affinely adjustable robust optimization method.A solution algorithm based on a cutting plane algorithm is developed to solve the optimization problem effectively.The proposed method is verified through theoretical analysis and numerical simulations.
