Driven by the desire of a low-carbon society,the penetration level of renewable generation in the power grid of China will still grow fast in the near future.As the synchronised generators whose output is controllable...Driven by the desire of a low-carbon society,the penetration level of renewable generation in the power grid of China will still grow fast in the near future.As the synchronised generators whose output is controllable are gradually replaced by volatile energy resources,energy storage is expected to play a vital role in regulation services and flexibility provision.Because the capital cost of energy storage is still relatively high,it is important to assess the value or demand of energy storage before making an investment decision.This paper presents two representative mathematical tools to achieve this target in a geometric fashion.The first one is the multi-parametric programming method.It depicts the reduced cost by deploying energy storage through post-optimal value function,which is easy to visualise or can be embedded in high-level optimisation problems such as storage sizing.The second one is a polyhedral projection method.It represents all feasible power-energy capacity pairs of a storage unit to achieve a certain target.The above methods remove the need of repeatedly solving a large number of problems with varying capacity parameters.Simple examples are given for illustration,and the presented methods can also directly handle problems with complex models and constraints.展开更多
Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational s...Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational scenarios,considering the large amount of historical operational snapshot data.Specifically,DTSAs analyse the intrinsic mechanisms of different scheduling operational scenario switching to mathematically represent typical operational scenarios.A Gramian angular summation field-based operational scenario image encoder was designed to convert operational scenario sequences into highdimensional spaces.This enables DTSAs to fully capture the spatiotemporal characteristics of new power systems using deep feature iterative aggregation models.The encoder also facilitates the generation of typical operational scenarios that conform to historical data distributions while ensuring the integrity of grid operational snapshots.Case studies demonstrate that the proposed method extracted new fine-grained power system dispatch schemes and outperformed the latest high-dimensional feature-screening methods.In addition,experiments with different new energy access ratios were conducted to verify the robustness of the proposed method.DTSAs enable dispatchers to master the operation experience of the power system in advance,and actively respond to the dynamic changes of the operation scenarios under the high access rate of new energy.展开更多
This paper summarizes the prevailing power system operation methods for managing the uncertainty brought by large-scale integration of renewables and active load demand.From the perspective of power system operations,...This paper summarizes the prevailing power system operation methods for managing the uncertainty brought by large-scale integration of renewables and active load demand.From the perspective of power system operations,uncertainty management is an important problem.In this paper,the mathematical models used for handling uncertainty are discussed,along with the pros and cons as well as future development efforts of four different operation methods.The study concludes that it is difficult to adopt a universal operation theory for mitigating the uncertainty in power system operations.Instead,it is necessary to choose the most feasible operation method that matches the specific operation requirement.展开更多
State estimation is a critical functionality of energy management system(EMS) to provide power system states in real-time operations. However, problems such as failure to converge, prone to failure during contingencie...State estimation is a critical functionality of energy management system(EMS) to provide power system states in real-time operations. However, problems such as failure to converge, prone to failure during contingencies,and biased estimates while system is under stressed condition occur so that state estimation results may not be reliable.The unreliable results further impact downstream network and market applications, such as contingency analysis,voltage stability analysis, transient stability analysis, system alarming, and unit commitment. Thus, operators may lose the awareness of system condition in EMS. This paper proposes a fully independent and one-of-a-kind system by integrating linear state estimator into situational awareness applications based on real-time synchrophasor data. With guaranteed and accurate state estimation solution and advanced real-time data analytic and monitoring functionalities, the system is capable of assisting operators to assess and diagnose current system conditions for proactive and necessary corrective actions. The architecture, building components, and implementation of the proposed system are explored in detail. Two case studies with simulated data from the subsystems of Electric Reliability Council of Texas(ERCOT) and Los Angeles Department of Water and Power(LADWP) are presented. The test results show the effectiveness and reliability of the system, and its value for realtime power system operations.展开更多
Demand response(DR)is gaining more and more importance in the architecture of power systems in a context of flexible loads and high share of intermittent generation.Changes in electricity markets regulation in several...Demand response(DR)is gaining more and more importance in the architecture of power systems in a context of flexible loads and high share of intermittent generation.Changes in electricity markets regulation in several countries have recently enabled an effective integration of DR mechanisms in power systems.Through its flexible components(pumps,tanks),drinking water systems are suitable candidates for energy-efficient DR mechanisms.However,these systems are often managed independently of power system operation for both economic and operational reasons.Indeed,a sufficient level of economic viability and water demands risk management are necessary for water utilities to integrate their flexibilities to power system operation.In this paper,we proposed a mathematical model for optimizing pump schedules in water systems while trading DR blocs in a spot power market during peak times.Uncertainties about water demands were considered in the mathematical model allowing to propose power reductions covering the potential risk of real-time water demand forecasting inaccuracy.Numerical results were discussed on a real water system in France,demonstrating both economic and ecological benefits.展开更多
In this letter,a new formulation of Lebesgue integration is used to evaluate the probabilistic static security of power system operation with uncertain renewable energy generation.The risk of power flow solutions viol...In this letter,a new formulation of Lebesgue integration is used to evaluate the probabilistic static security of power system operation with uncertain renewable energy generation.The risk of power flow solutions violating any pre-defined operation security limits is obtained by integrating a semialgebraic set composed of polynomials.With the high-order moments of historical data of renewable energy generation,the integration is reformulated as a generalized moment problem which is then relaxed to a semi-definite program(SDP).Finally,the effectiveness of the proposed method is verified by numerical examples.展开更多
Renewable generation is rapidly increasing and transforming power systems toward“new-type power systems”.The integration of renewable energy resources necessitates a shift from conventional grid-following converters...Renewable generation is rapidly increasing and transforming power systems toward“new-type power systems”.The integration of renewable energy resources necessitates a shift from conventional grid-following converters(GFLs)to advanced grid-forming controls.Although grid-forming converters(GFMs)provide grid support and enhance system stability under weak grid conditions,their deployment requires more robust hardware,complex control algorithms and system operation constraints,resulting in planning and operational trade-offs between system stability and cost efficiency.This paper studies the underexplored question of how many GFMs are needed from a techno-economic perspective.The holistic analysis integrates long-term planning,short-term operational strategies and dynamic stability considerations,thereby supporting large-scale renewable integration while ensuring system security and economic benefits.展开更多
The data acquisition technologies used in power systems have been continuously improving,thus laying the solid foundation for data-driven operation analysis of power systems.However,existing methods for analyzing the ...The data acquisition technologies used in power systems have been continuously improving,thus laying the solid foundation for data-driven operation analysis of power systems.However,existing methods for analyzing the relationship between operational variables mainly depend on the mathematical model and element parameters of the power system.Therefore,a thorough data-based analysis method is required to investigate the spatiotemporal characteristics of power system operation,especially for new types of power systems.The causal inference method,which has been successfully applied in many fields,is a powerful tool for investigating the interaction of data variables.In this study,a causal inference method is proposed based on supervisory control and data acquisition(SCADA)data for investigating the spatiotemporal causal relationships in power systems.Initially,a multiple data-sequence regression model is proposed to analyze the relationship of operation data variables.Next,the linear non-Gaussian acyclic model(LiNGAM)is used to calculate the causal index of the operational variables,and its limitations are analyzed.Furthermore,a new causal index of“full variable amplitude LiNGAM(FVA-LiNGAM)”is proposed by incorporating prior causal direct knowledge and considering the effect of real variable amplitude.Using the FVA-LiNGAM causal index,the causal relationship of operation variables can be investigated with higher spatiotemporal accuracy than that of the original LiNGAM index.Taking a real SCADA data subset of a provincial power system as an example,the validity of the FVA-LiNGAM causal index is verified.The variation patterns in spatiotemporal causality are explored using actual SCADA data sequences.The result shows that there indeed exists some spatiotemporal causality variation patterns between the operating variables of the power system.展开更多
The integration of continuously varying and not easily predictable wind power generation is affecting the stability of the power system and leads to increasing demand for balancing services.In this study,a short-term ...The integration of continuously varying and not easily predictable wind power generation is affecting the stability of the power system and leads to increasing demand for balancing services.In this study,a short-term operation model of a district heating system is proposed to optimally schedule the production of both heat and power in a system with high wind power penetration.The application of the model in a case study system shows the increased flexibility offered by the coordination of power generation,consumption and heat storage units which are available in district heating systems.展开更多
We consider a power system whose electric demand pertaining to freshwater production is high(high freshwater electric demand),as in the Middle East,and investigate the tradeoff of storing freshwater in tanks versus st...We consider a power system whose electric demand pertaining to freshwater production is high(high freshwater electric demand),as in the Middle East,and investigate the tradeoff of storing freshwater in tanks versus storing electricity in batteries at the day-ahead operation stage.Both storing freshwater and storing electricity increase the actual electric demand at valley hours and decrease it at peak hours,which is generally beneficial in term of cost and reliability.But,to what extent?We analyze this question considering three power systems with different generation-mix configurations,i.e.,a thermal-dominated mix,a renewable-dominated one,and a fully renewable one.These generation-mix configurations are inspired by how power systems may evolve in different countries in the Middle East.Renewable production uncertainty is compactly modeled using chance constraints.We draw conclusions on how both storage facilities(freshwater and electricity)complement each other to render an optimal operation of the power system.展开更多
A future smart grid must fulfill the vision of the Energy Internet in which millions of people produce their own energy from renewables in their homes, offices, and factories and share it with each other. Electric veh...A future smart grid must fulfill the vision of the Energy Internet in which millions of people produce their own energy from renewables in their homes, offices, and factories and share it with each other. Electric vehicles and local energy storage will be widely deployed. Internet technology will be utilized to transform the power grid into an energysharing inter-grid. To prepare for the future, a smart grid with intelligent periphery, or smart GRIP, is proposed. The building blocks of GRIP architecture are called clusters and include an energy-management system （EMS）-controlled transmission grid in the core and distribution grids, micro-grids, and smart buildings and homes on the periphery; all of which are hierarchically structured. The layered architecture of GRIP allows a seamless transition from the present to the future and plug-and-play interoperability. The basic functions of a cluster consist of （1） dispatch, （2） smoothing, and （3） mitigation. A risk-limiting dispatch methodology is presented; a new device, called the electric spring, is developed for smoothing out fluctuations in periphery clusters; and means to mitigate failures are discussed.展开更多
With the growing integration of distributed energy resources(DERs),flexible loads,and other emerging technologies,there are increasing complexities and uncertainties for modern power and energy systems.This brings gre...With the growing integration of distributed energy resources(DERs),flexible loads,and other emerging technologies,there are increasing complexities and uncertainties for modern power and energy systems.This brings great challenges to the operation and control.Besides,with the deployment of advanced sensor and smart meters,a large number of data are generated,which brings opportunities for novel data-driven methods to deal with complicated operation and control issues.Among them,reinforcement learning(RL)is one of the most widely promoted methods for control and optimization problems.This paper provides a comprehensive literature review of RL in terms of basic ideas,various types of algorithms,and their applications in power and energy systems.The challenges and further works are also discussed.展开更多
To secure power system operations,practical dispatches in industries place a steady power transfer limit on critical inter-corridors,rather than high-dimensional and strong nonlinear stability constraints.However,comp...To secure power system operations,practical dispatches in industries place a steady power transfer limit on critical inter-corridors,rather than high-dimensional and strong nonlinear stability constraints.However,computational complexities lead to over-conservative pre-settings of transfer limit,which further induce undesirable and non-technical congestion of power transfer.To conquer this barrier,a scenario-classification hybrid-based banding method is proposed.A cluster technique is adopted to separate similarities from historical and generated operating condition dataset.With a practical rule,transfer limits are approximated for each operating cluster.Then,toward an interpretable online transfer limit decision,costsensitive learning is applied to identify cluster affiliation to assign a transfer limit for a given operation.In this stage,critical variables that affect the transfer limit are also picked out via mean impact value.This enables us to construct low-complexity and dispatcher-friendly rules for fast determination of transfer limit.The numerical case studies on the IEEE 39-bus system and a real-world regional power system in China illustrate the effectiveness and conservativeness of the proposed method.展开更多
The distribution control center(DCC)has evolved from a sideshow in the traditional distribution service center to a major centerpiece of the utility moving into the decentralized world.Mostly,this is the place where m...The distribution control center(DCC)has evolved from a sideshow in the traditional distribution service center to a major centerpiece of the utility moving into the decentralized world.Mostly,this is the place where much of the action is happening due to new forms of energy that are coining into the distribution system.This creates the flexibility of operation and in-creased complexity due to the need for increased coordination between the transmission control center and DCC.However,the US and European utilities have adapted to this change in very different ways.Firstly,we describe the research works done in a DCC and their evolutions from the perspectives of major US utilities,and those enhanced by the European perspective focusing on the coordination of distribution system operator and transmission system operator(DSO-TSO).We pres-ent the insights into the systems used in these control centers and the role of vendors in their evolution.Throughout this paper,we present the perspectives of challenges,operational capabilities,and the involvement of various parties who will be re-sponsible to make the transition successful.Key differences are pointed out on how distribution operations are conducted between the US and Europe.展开更多
The energy conservation plays an important role for low carbon development.In order to evaluate the energy conservation in the full life-cycle,a scheme to estimate the energy consumption,or alternatively the energy pa...The energy conservation plays an important role for low carbon development.In order to evaluate the energy conservation in the full life-cycle,a scheme to estimate the energy consumption,or alternatively the energy pay,in constructing an overhead transmission line is proposed in this paper.The analysis of a typical projection is given for demonstration.With new additional overhead transmission lines,the energy consumption,known as the power loss in power network,is expected to be decline,which is defined in this paper as the energy payback.In order to estimate this kind of contribution,the scheme that consisted of load forecast,production simulation for generating systems,load flow simulation and power loss calculation has been proposed.Case studies,based on the IEEE 24-bus test system,are given to demonstrate the efficacy of the schemes.Moreover,several presumptive scenarios are deployed and analysed with the presented schemes for comparison.展开更多
This survey paper provides a critical overview of optimization formulations for planning and operation of islanded microgrids,including optimization objectives,constraints,and control variables.The optimization approa...This survey paper provides a critical overview of optimization formulations for planning and operation of islanded microgrids,including optimization objectives,constraints,and control variables.The optimization approaches reviewed address methods both for increasing the resiliency of advanced distribution systems and electrification of remote communities.This paper examines over 120 individual optimization studies and discovers that all optimizations studies of islanded microgrids are based on formulations selecting a combination of 16 possible objective functions,14 constraints,and 13 control variables.Each of the objectives,constraints,and variables are discussed exhaustively both from the perspective of their importance to islanded microgrids and chronological trends in their popularity.展开更多
More flexibility is desirable with the proliferation of variable renewable resources for balancing supply and demand in power systems.Thermostatically controlled loads(TCLs)attract tremendous attentions because of the...More flexibility is desirable with the proliferation of variable renewable resources for balancing supply and demand in power systems.Thermostatically controlled loads(TCLs)attract tremendous attentions because of their specific thermal inertia capability in demand response(DR)programs.To effectively manage numerous and distributed TCLs,intermediate coordinators,e.g.,aggregators,as a bridge between end users and dispatch operators are required to model and control TCLs for serving the grid.Specifically,intermediate coordinators get the access to fundamental models and response modes of TCLs,make control strategies,and distribute control signals to TCLs according the requirements of dispatch operators.On the other hand,intermediate coordinators also provide dispatch models that characterize the external characteristics of TCLs to dispatch operators for scheduling different resources.In this paper,the bottom-up key technologies of TCLs in DR programs based on the current research have been reviewed and compared,including fundamental models,response modes,control strategies,dispatch models and dispatch strategies of TCLs,as well as challenges and opportunities in future work.展开更多
This paper presents a new approach to solve mixed-variable unit commitment(UC) problems with non-smooth cost functions based on a generalized pattern search filter(GPS-filter) algorithm. A GPS-filter algorithm does no...This paper presents a new approach to solve mixed-variable unit commitment(UC) problems with non-smooth cost functions based on a generalized pattern search filter(GPS-filter) algorithm. A GPS-filter algorithm does not require any information about the gradient of the objective function while searching for an optimum solution. At the same time, it is available for solving mixed-variable optimization problems, which is very suitable for UC. A new suitable discrete neighborhood structure with UC characteristics is proposed to improve GPS-filter efficiently. A lot of multiple units' states are fixed before search; hence, the polling search of discrete variable is efficient for a few uncertain units. Numerical experiments are included to demonstrate the proposed approach's ability to handle the highly nonlinear, discontinuous, non-smooth cost functions and mixed variables of the UC problem.展开更多
基金supported by the National Key Research and Development Programme of China(2021YFB2400701).
文摘Driven by the desire of a low-carbon society,the penetration level of renewable generation in the power grid of China will still grow fast in the near future.As the synchronised generators whose output is controllable are gradually replaced by volatile energy resources,energy storage is expected to play a vital role in regulation services and flexibility provision.Because the capital cost of energy storage is still relatively high,it is important to assess the value or demand of energy storage before making an investment decision.This paper presents two representative mathematical tools to achieve this target in a geometric fashion.The first one is the multi-parametric programming method.It depicts the reduced cost by deploying energy storage through post-optimal value function,which is easy to visualise or can be embedded in high-level optimisation problems such as storage sizing.The second one is a polyhedral projection method.It represents all feasible power-energy capacity pairs of a storage unit to achieve a certain target.The above methods remove the need of repeatedly solving a large number of problems with varying capacity parameters.Simple examples are given for illustration,and the presented methods can also directly handle problems with complex models and constraints.
基金The Key R&D Project of Jilin Province,Grant/Award Number:20230201067GX。
文摘Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational scenarios,considering the large amount of historical operational snapshot data.Specifically,DTSAs analyse the intrinsic mechanisms of different scheduling operational scenario switching to mathematically represent typical operational scenarios.A Gramian angular summation field-based operational scenario image encoder was designed to convert operational scenario sequences into highdimensional spaces.This enables DTSAs to fully capture the spatiotemporal characteristics of new power systems using deep feature iterative aggregation models.The encoder also facilitates the generation of typical operational scenarios that conform to historical data distributions while ensuring the integrity of grid operational snapshots.Case studies demonstrate that the proposed method extracted new fine-grained power system dispatch schemes and outperformed the latest high-dimensional feature-screening methods.In addition,experiments with different new energy access ratios were conducted to verify the robustness of the proposed method.DTSAs enable dispatchers to master the operation experience of the power system in advance,and actively respond to the dynamic changes of the operation scenarios under the high access rate of new energy.
基金supported by National Key Research Program(973 Program,2012CB215102)National Natural Science Foundation of China(51277155)Research Grant Council of Hong Kong SAR(GRF 7124/11E and ECS739713).
文摘This paper summarizes the prevailing power system operation methods for managing the uncertainty brought by large-scale integration of renewables and active load demand.From the perspective of power system operations,uncertainty management is an important problem.In this paper,the mathematical models used for handling uncertainty are discussed,along with the pros and cons as well as future development efforts of four different operation methods.The study concludes that it is difficult to adopt a universal operation theory for mitigating the uncertainty in power system operations.Instead,it is necessary to choose the most feasible operation method that matches the specific operation requirement.
文摘State estimation is a critical functionality of energy management system(EMS) to provide power system states in real-time operations. However, problems such as failure to converge, prone to failure during contingencies,and biased estimates while system is under stressed condition occur so that state estimation results may not be reliable.The unreliable results further impact downstream network and market applications, such as contingency analysis,voltage stability analysis, transient stability analysis, system alarming, and unit commitment. Thus, operators may lose the awareness of system condition in EMS. This paper proposes a fully independent and one-of-a-kind system by integrating linear state estimator into situational awareness applications based on real-time synchrophasor data. With guaranteed and accurate state estimation solution and advanced real-time data analytic and monitoring functionalities, the system is capable of assisting operators to assess and diagnose current system conditions for proactive and necessary corrective actions. The architecture, building components, and implementation of the proposed system are explored in detail. Two case studies with simulated data from the subsystems of Electric Reliability Council of Texas(ERCOT) and Los Angeles Department of Water and Power(LADWP) are presented. The test results show the effectiveness and reliability of the system, and its value for realtime power system operations.
文摘Demand response(DR)is gaining more and more importance in the architecture of power systems in a context of flexible loads and high share of intermittent generation.Changes in electricity markets regulation in several countries have recently enabled an effective integration of DR mechanisms in power systems.Through its flexible components(pumps,tanks),drinking water systems are suitable candidates for energy-efficient DR mechanisms.However,these systems are often managed independently of power system operation for both economic and operational reasons.Indeed,a sufficient level of economic viability and water demands risk management are necessary for water utilities to integrate their flexibilities to power system operation.In this paper,we proposed a mathematical model for optimizing pump schedules in water systems while trading DR blocs in a spot power market during peak times.Uncertainties about water demands were considered in the mathematical model allowing to propose power reductions covering the potential risk of real-time water demand forecasting inaccuracy.Numerical results were discussed on a real water system in France,demonstrating both economic and ecological benefits.
基金This work was supported by the National Natural Science Foundation of China(No.52007163)in part by China Postdoctoral Science Foundation(No.2020M671718).
文摘In this letter,a new formulation of Lebesgue integration is used to evaluate the probabilistic static security of power system operation with uncertain renewable energy generation.The risk of power flow solutions violating any pre-defined operation security limits is obtained by integrating a semialgebraic set composed of polynomials.With the high-order moments of historical data of renewable energy generation,the integration is reformulated as a generalized moment problem which is then relaxed to a semi-definite program(SDP).Finally,the effectiveness of the proposed method is verified by numerical examples.
基金supported in part by the Carbon Neutrality and Energy System Transformation project and in part by EPSRC under Grant EP/Y025946/1.
文摘Renewable generation is rapidly increasing and transforming power systems toward“new-type power systems”.The integration of renewable energy resources necessitates a shift from conventional grid-following converters(GFLs)to advanced grid-forming controls.Although grid-forming converters(GFMs)provide grid support and enhance system stability under weak grid conditions,their deployment requires more robust hardware,complex control algorithms and system operation constraints,resulting in planning and operational trade-offs between system stability and cost efficiency.This paper studies the underexplored question of how many GFMs are needed from a techno-economic perspective.The holistic analysis integrates long-term planning,short-term operational strategies and dynamic stability considerations,thereby supporting large-scale renewable integration while ensuring system security and economic benefits.
基金supported by the National Natural Science Foundation of China(51877034).
文摘The data acquisition technologies used in power systems have been continuously improving,thus laying the solid foundation for data-driven operation analysis of power systems.However,existing methods for analyzing the relationship between operational variables mainly depend on the mathematical model and element parameters of the power system.Therefore,a thorough data-based analysis method is required to investigate the spatiotemporal characteristics of power system operation,especially for new types of power systems.The causal inference method,which has been successfully applied in many fields,is a powerful tool for investigating the interaction of data variables.In this study,a causal inference method is proposed based on supervisory control and data acquisition(SCADA)data for investigating the spatiotemporal causal relationships in power systems.Initially,a multiple data-sequence regression model is proposed to analyze the relationship of operation data variables.Next,the linear non-Gaussian acyclic model(LiNGAM)is used to calculate the causal index of the operational variables,and its limitations are analyzed.Furthermore,a new causal index of“full variable amplitude LiNGAM(FVA-LiNGAM)”is proposed by incorporating prior causal direct knowledge and considering the effect of real variable amplitude.Using the FVA-LiNGAM causal index,the causal relationship of operation variables can be investigated with higher spatiotemporal accuracy than that of the original LiNGAM index.Taking a real SCADA data subset of a provincial power system as an example,the validity of the FVA-LiNGAM causal index is verified.The variation patterns in spatiotemporal causality are explored using actual SCADA data sequences.The result shows that there indeed exists some spatiotemporal causality variation patterns between the operating variables of the power system.
基金sponsored by Swe GRIDS,the Swedish Centre for Smart Grids and Energy Storage,www.swegrids.se.
文摘The integration of continuously varying and not easily predictable wind power generation is affecting the stability of the power system and leads to increasing demand for balancing services.In this study,a short-term operation model of a district heating system is proposed to optimally schedule the production of both heat and power in a system with high wind power penetration.The application of the model in a case study system shows the increased flexibility offered by the coordination of power generation,consumption and heat storage units which are available in district heating systems.
文摘We consider a power system whose electric demand pertaining to freshwater production is high(high freshwater electric demand),as in the Middle East,and investigate the tradeoff of storing freshwater in tanks versus storing electricity in batteries at the day-ahead operation stage.Both storing freshwater and storing electricity increase the actual electric demand at valley hours and decrease it at peak hours,which is generally beneficial in term of cost and reliability.But,to what extent?We analyze this question considering three power systems with different generation-mix configurations,i.e.,a thermal-dominated mix,a renewable-dominated one,and a fully renewable one.These generation-mix configurations are inspired by how power systems may evolve in different countries in the Middle East.Renewable production uncertainty is compactly modeled using chance constraints.We draw conclusions on how both storage facilities(freshwater and electricity)complement each other to render an optimal operation of the power system.
基金sponsored by National Key Basic Research Program of China (973 Program) (2012CB215102) for WuUS National Science Foundation Award (1135872) for VaraiyaHong Kong RGC Theme-based Research Project (T23-701/14-N) for Hui
文摘A future smart grid must fulfill the vision of the Energy Internet in which millions of people produce their own energy from renewables in their homes, offices, and factories and share it with each other. Electric vehicles and local energy storage will be widely deployed. Internet technology will be utilized to transform the power grid into an energysharing inter-grid. To prepare for the future, a smart grid with intelligent periphery, or smart GRIP, is proposed. The building blocks of GRIP architecture are called clusters and include an energy-management system （EMS）-controlled transmission grid in the core and distribution grids, micro-grids, and smart buildings and homes on the periphery; all of which are hierarchically structured. The layered architecture of GRIP allows a seamless transition from the present to the future and plug-and-play interoperability. The basic functions of a cluster consist of （1） dispatch, （2） smoothing, and （3） mitigation. A risk-limiting dispatch methodology is presented; a new device, called the electric spring, is developed for smoothing out fluctuations in periphery clusters; and means to mitigate failures are discussed.
基金supported by the Sichuan Science and Technology Program(Sichuan Distinguished Young Scholars)(No.2020JDJQ0037).
文摘With the growing integration of distributed energy resources(DERs),flexible loads,and other emerging technologies,there are increasing complexities and uncertainties for modern power and energy systems.This brings great challenges to the operation and control.Besides,with the deployment of advanced sensor and smart meters,a large number of data are generated,which brings opportunities for novel data-driven methods to deal with complicated operation and control issues.Among them,reinforcement learning(RL)is one of the most widely promoted methods for control and optimization problems.This paper provides a comprehensive literature review of RL in terms of basic ideas,various types of algorithms,and their applications in power and energy systems.The challenges and further works are also discussed.
基金supported in part by State Grid Corporation of China Project“Research on high penetrated renewable energy oriented intelligent identification for curtailment impacts and aid decision-making for promoting consumption in regional power grids”(No.5108-202135035A-0-0-00).
文摘To secure power system operations,practical dispatches in industries place a steady power transfer limit on critical inter-corridors,rather than high-dimensional and strong nonlinear stability constraints.However,computational complexities lead to over-conservative pre-settings of transfer limit,which further induce undesirable and non-technical congestion of power transfer.To conquer this barrier,a scenario-classification hybrid-based banding method is proposed.A cluster technique is adopted to separate similarities from historical and generated operating condition dataset.With a practical rule,transfer limits are approximated for each operating cluster.Then,toward an interpretable online transfer limit decision,costsensitive learning is applied to identify cluster affiliation to assign a transfer limit for a given operation.In this stage,critical variables that affect the transfer limit are also picked out via mean impact value.This enables us to construct low-complexity and dispatcher-friendly rules for fast determination of transfer limit.The numerical case studies on the IEEE 39-bus system and a real-world regional power system in China illustrate the effectiveness and conservativeness of the proposed method.
基金MONKS,Sarajevo,FBiH,Bosnia and Herzegovina(No.27-02-11-41250-34/21).
文摘The distribution control center(DCC)has evolved from a sideshow in the traditional distribution service center to a major centerpiece of the utility moving into the decentralized world.Mostly,this is the place where much of the action is happening due to new forms of energy that are coining into the distribution system.This creates the flexibility of operation and in-creased complexity due to the need for increased coordination between the transmission control center and DCC.However,the US and European utilities have adapted to this change in very different ways.Firstly,we describe the research works done in a DCC and their evolutions from the perspectives of major US utilities,and those enhanced by the European perspective focusing on the coordination of distribution system operator and transmission system operator(DSO-TSO).We pres-ent the insights into the systems used in these control centers and the role of vendors in their evolution.Throughout this paper,we present the perspectives of challenges,operational capabilities,and the involvement of various parties who will be re-sponsible to make the transition successful.Key differences are pointed out on how distribution operations are conducted between the US and Europe.
基金This work was supported by the National Science Fund for Distinguished Young Scholars(No.51325702)the China Postdoctoral Science Foundation(No.2014M560968).
文摘The energy conservation plays an important role for low carbon development.In order to evaluate the energy conservation in the full life-cycle,a scheme to estimate the energy consumption,or alternatively the energy pay,in constructing an overhead transmission line is proposed in this paper.The analysis of a typical projection is given for demonstration.With new additional overhead transmission lines,the energy consumption,known as the power loss in power network,is expected to be decline,which is defined in this paper as the energy payback.In order to estimate this kind of contribution,the scheme that consisted of load forecast,production simulation for generating systems,load flow simulation and power loss calculation has been proposed.Case studies,based on the IEEE 24-bus test system,are given to demonstrate the efficacy of the schemes.Moreover,several presumptive scenarios are deployed and analysed with the presented schemes for comparison.
文摘This survey paper provides a critical overview of optimization formulations for planning and operation of islanded microgrids,including optimization objectives,constraints,and control variables.The optimization approaches reviewed address methods both for increasing the resiliency of advanced distribution systems and electrification of remote communities.This paper examines over 120 individual optimization studies and discovers that all optimizations studies of islanded microgrids are based on formulations selecting a combination of 16 possible objective functions,14 constraints,and 13 control variables.Each of the objectives,constraints,and variables are discussed exhaustively both from the perspective of their importance to islanded microgrids and chronological trends in their popularity.
基金supported in part by the National Natural Science Foundation of China(Grant No.52007030)the US National Science Foundation(Grant No.ECCS-1552073)awards of the US Department of Energy(DE-EE0007998 and DE-EE0009028).
文摘More flexibility is desirable with the proliferation of variable renewable resources for balancing supply and demand in power systems.Thermostatically controlled loads(TCLs)attract tremendous attentions because of their specific thermal inertia capability in demand response(DR)programs.To effectively manage numerous and distributed TCLs,intermediate coordinators,e.g.,aggregators,as a bridge between end users and dispatch operators are required to model and control TCLs for serving the grid.Specifically,intermediate coordinators get the access to fundamental models and response modes of TCLs,make control strategies,and distribute control signals to TCLs according the requirements of dispatch operators.On the other hand,intermediate coordinators also provide dispatch models that characterize the external characteristics of TCLs to dispatch operators for scheduling different resources.In this paper,the bottom-up key technologies of TCLs in DR programs based on the current research have been reviewed and compared,including fundamental models,response modes,control strategies,dispatch models and dispatch strategies of TCLs,as well as challenges and opportunities in future work.
基金Project Supported by National Natural Science Foundation of China(51277034,51377027)
文摘This paper presents a new approach to solve mixed-variable unit commitment(UC) problems with non-smooth cost functions based on a generalized pattern search filter(GPS-filter) algorithm. A GPS-filter algorithm does not require any information about the gradient of the objective function while searching for an optimum solution. At the same time, it is available for solving mixed-variable optimization problems, which is very suitable for UC. A new suitable discrete neighborhood structure with UC characteristics is proposed to improve GPS-filter efficiently. A lot of multiple units' states are fixed before search; hence, the polling search of discrete variable is efficient for a few uncertain units. Numerical experiments are included to demonstrate the proposed approach's ability to handle the highly nonlinear, discontinuous, non-smooth cost functions and mixed variables of the UC problem.
