With the progressive exhaustion of fossil energy and growing concerns about climate change,it has been ob served that distributed energy resources such as photovoltaic(PV)systems and electric vehicles(EVs)are being in...With the progressive exhaustion of fossil energy and growing concerns about climate change,it has been ob served that distributed energy resources such as photovoltaic(PV)systems and electric vehicles(EVs)are being increasingly integrated into distribution systems.This underscores the in creasing imperative for a thorough analysis to evaluate reliabili ty from the perspectives of distribution systems and EV charg ing services,taking into account the stochastic nature of PV and EV load demands.This paper presents an approach for the reliability assessment of distribution systems that incorporate PV and EVs considering reliability models for both PV systems and EV battery systems.It also defines new indices to investi gate the adequacy and customer-side reliability for EV charging services.The developed methodology utilizes a Monte Carlo simulation-based approach and is showcased using the modified Roy Billinton Test System(RBTS)Bus 4 distribution system.The results illustrate that reliability indices for EV charging ser vices,such as percentage of charging energy not supplied(PCENS),average EV interruption frequency index(AEVIFI)and average EV interruption duration index(AEVIDI),are im proved under the proposed approach.展开更多
To accommodate wind power as safely as possible and deal with the uncertainties of the output power of winddriven generators,a min-max-min two-stage robust optimization model is presented,considering the unit commitme...To accommodate wind power as safely as possible and deal with the uncertainties of the output power of winddriven generators,a min-max-min two-stage robust optimization model is presented,considering the unit commitment,source-network load collaboration,and control of the load demand response.After the constraint functions are linearized,the original problem is decomposed into the main problem and subproblem as a matrix using the strong dual method.The minimum-maximum of the original problem was continuously maximized using the iterative method,and the optimal solution was finally obtained.The constraint conditions expressed by the matrix may reduce the calculation time,and the upper and lower boundaries of the original problem may rapidly converge.The results of the example show that the injected nodes of the wind farms in the power grid should be selected appropriately;otherwise,it is easy to cause excessive accommodation of wind power at some nodes,leading to a surge in reserve costs and the load demand response is continuously optimized to reduce the inverse peak regulation characteristics of wind power.Thus,the most economical optimization scheme for the worst scenario of the output power of the generators is obtained,which proves the economy and reliability of the two-stage robust optimization method.展开更多
In this paper,a novel multi-objective optimization model of integrated energy systems(IESs)is proposed based on the ladder-type carbon emission trading mechanism and refined load demand response strategies.First,the c...In this paper,a novel multi-objective optimization model of integrated energy systems(IESs)is proposed based on the ladder-type carbon emission trading mechanism and refined load demand response strategies.First,the carbon emission trading mechanism is introduced into the optimal scheduling of IESs,and a ladder-type carbon emission cost calculation model based on rewards and penalties is established to strictly control the carbon emissions of the system.Then,according to different response characteristics of electric load and heating load,a refined load demand response model is built based on the price elasticity matrix and substitutability of energy supply mode.On these basis,a multi-objective optimization model of IESs is established,which aims to minimize the total operating cost and the renewable energy source(RES)curtailment.Finally,based on typical case studies,the simulation results show that the proposed model can effectively improve the economic benefits of IESs and the utilization efficiency of RESs.展开更多
The energy storage system(ESS)as a demand-side management(DSM)resource can effectively smooth the load power fluctuation of a power system.However,designing a more reasonable ESS operational strategy will be a prerequ...The energy storage system(ESS)as a demand-side management(DSM)resource can effectively smooth the load power fluctuation of a power system.However,designing a more reasonable ESS operational strategy will be a prerequisite before incorporating the energy storage device into DSM.As different load levels have different demands for the real-time chargedischarge power of an ESS,this paper proposes a heuristic ESS operation scheduling strategy which can take into account the electrical load demand differences.In this paper,firstly,two demand degree concepts for charging power and discharging power are defined to describe the differentiated ESS demand under the condition of different electrical load levels.Secondly,an inverse proportion technique based ESS scheduling strategy,with the consideration of the load demand difference,is proposed in this paper.Thirdly,some evaluating indices are defined in this paper for describing the influence of the proposed strategy on the smoothing degree of the daily load curve.Finally,several case studies are designed to verify the validity and correctness of the proposed technique,and the results show that the proposed technique can effectively smooth the load curve and improve the ability of peak shaving and valley filling.展开更多
Utilities around the world have been considering Demand Side Management (DSM) in their strategic planning. The costs of constructing and operating a new capacity generation unit are increasing everyday as well as Tran...Utilities around the world have been considering Demand Side Management (DSM) in their strategic planning. The costs of constructing and operating a new capacity generation unit are increasing everyday as well as Transmission and distribution and land issues for new generation plants, which force the utilities to search for another alternatives without any additional constraints on customers comfort level or quality of delivered product. De can be defined as the selection, planning, and implementation of measures intended to have an influence on the demand or customer-side of the electric meter, either caused directly or stimulated indirectly by the utility. DSM programs are peak clipping, Valley filling, Load shifting, Load building, energy conservation and flexible load shape. The main Target of this paper is to show the relation between DSM and Load Forecasting. Moreover, it highlights on the effect of applying DSM on Forecasted demands and how this affects the planning strategies for utility companies. This target will be clearly illustrated through applying the developed algorithm in this paper on an existing residential compound in Cairo-Egypt.展开更多
In the framework of liberalized deregulated electricity market, dynamic competitive environment exists between wholesale and retail dealers for energy supplying and management. Smart Grids topology in form of energy m...In the framework of liberalized deregulated electricity market, dynamic competitive environment exists between wholesale and retail dealers for energy supplying and management. Smart Grids topology in form of energy management has forced power supplying agencies to become globally competitive. Demand Response (DR) Programs in context with smart energy network have influenced prosumers and consumers towards it. In this paper Fair Emergency Demand Response Program (FEDRP) is integrated for managing the loads intelligently by using the platform of Smart Grids for Residential Setup. The paper also provides detailed modelling and analysis of respective demands of residential consumers in relation with economic load model for FEDRP. Due to increased customer’s partaking in this program the load on the utility is reduced and managed intelligently during emergency hours by providing fair and attractive incentives to residential clients, thus shifting peak load to off peak hours. The numerical and graphical results are matched for intelligent load management scenario.展开更多
Lately,in modern smart power grids,energy demand for accurate forecast of electricity is gaining attention,with increased interest of research.This is due to the fact that a good energy demand forecast would lead to p...Lately,in modern smart power grids,energy demand for accurate forecast of electricity is gaining attention,with increased interest of research.This is due to the fact that a good energy demand forecast would lead to proper responses for electricity demand.In addition,proper energy demand forecast would ensure efficient planning of the electricity industry and is critical in the scheduling of the power grid capacity and management of the entire power network.As most power systems are been deregulated and with the rapid introduction and development of smart-metering technologies in Oman,new opportunities may arise considering the efficiency and reliability of the power system;like price-based demand response programs.These programs could either be a large scale for household,commercial or industrial users.However,excellent demand forecasting models are crucial for the deployment of these smart metering in the power grid based on good knowledge of the electricity market structure.Consequently,in this paper,an overview of the Oman regulatory regime,financial mechanism,price control,and distribution system security standard were presented.More so,the energy demand forecast in Oman was analysed,using the econometric model to forecasts its energy peak demand.The energy econometric analysis in this study describes the relationship between the growth of historical electricity consumption and macro-economic parameters(by region,and by tariff),considering a case study of Mazoon Electricity Distribution Company(MZEC),which is one of the major power distribution companies in Oman,for effective energy demand in the power grid.展开更多
In recent years, Rwanda’s rapid economic development has created the “Rwanda Africa Wonder”, but it has also led to a substantial increase in energy consumption with the ambitious goal of reaching universal access ...In recent years, Rwanda’s rapid economic development has created the “Rwanda Africa Wonder”, but it has also led to a substantial increase in energy consumption with the ambitious goal of reaching universal access by 2024. Meanwhile, on the basis of the rapid and dynamic connection of new households, there is uncertainty about generating, importing, and exporting energy whichever imposes a significant barrier. Long-Term Load Forecasting (LTLF) will be a key to the country’s utility plan to examine the dynamic electrical load demand growth patterns and facilitate long-term planning for better and more accurate power system master plan expansion. However, a Support Vector Machine (SVM) for long-term electric load forecasting is presented in this paper for accurate load mix planning. Considering that an individual forecasting model usually cannot work properly for LTLF, a hybrid Q-SVM will be introduced to improve forecasting accuracy. Finally, effectively assess model performance and efficiency, error metrics, and model benchmark parameters there assessed. The case study demonstrates that the new strategy is quite useful to improve LTLF accuracy. The historical electric load data of Rwanda Energy Group (REG), a national utility company from 1998 to 2020 was used to test the forecast model. The simulation results demonstrate the proposed algorithm enhanced better forecasting accuracy.展开更多
This paper presents an advanced methodology for optimizing a UK network load demand with various uncertainties which are related to individual driving behaviours. Without the optimized regulation for traditional power...This paper presents an advanced methodology for optimizing a UK network load demand with various uncertainties which are related to individual driving behaviours. Without the optimized regulation for traditional power system demand, EVs （electric vehicles） would have an adverse impact on the stability of power systems. This becomes more significant for large-scale EVs plugging into the power grid. Traditional optimized methodologies are effective only for EV charging. The proposed techniques improve the system flexibility and stability through an advanced optimization model and flexible bidirectional charging/discharging control. Three scenarios with different charging and discharging power levels and various penetration levels of EVs are discussed in detail in this paper. Simulation results demonstrate that bidirectional EV power flow control has vast potentials to improve the load demand profile, with increased proportion of EVs, and charging/discharging power levels.展开更多
文摘With the progressive exhaustion of fossil energy and growing concerns about climate change,it has been ob served that distributed energy resources such as photovoltaic(PV)systems and electric vehicles(EVs)are being increasingly integrated into distribution systems.This underscores the in creasing imperative for a thorough analysis to evaluate reliabili ty from the perspectives of distribution systems and EV charg ing services,taking into account the stochastic nature of PV and EV load demands.This paper presents an approach for the reliability assessment of distribution systems that incorporate PV and EVs considering reliability models for both PV systems and EV battery systems.It also defines new indices to investi gate the adequacy and customer-side reliability for EV charging services.The developed methodology utilizes a Monte Carlo simulation-based approach and is showcased using the modified Roy Billinton Test System(RBTS)Bus 4 distribution system.The results illustrate that reliability indices for EV charging ser vices,such as percentage of charging energy not supplied(PCENS),average EV interruption frequency index(AEVIFI)and average EV interruption duration index(AEVIDI),are im proved under the proposed approach.
基金supported by the Special Research Project on Power Planning of the Guangdong Power Grid Co.,Ltd.
文摘To accommodate wind power as safely as possible and deal with the uncertainties of the output power of winddriven generators,a min-max-min two-stage robust optimization model is presented,considering the unit commitment,source-network load collaboration,and control of the load demand response.After the constraint functions are linearized,the original problem is decomposed into the main problem and subproblem as a matrix using the strong dual method.The minimum-maximum of the original problem was continuously maximized using the iterative method,and the optimal solution was finally obtained.The constraint conditions expressed by the matrix may reduce the calculation time,and the upper and lower boundaries of the original problem may rapidly converge.The results of the example show that the injected nodes of the wind farms in the power grid should be selected appropriately;otherwise,it is easy to cause excessive accommodation of wind power at some nodes,leading to a surge in reserve costs and the load demand response is continuously optimized to reduce the inverse peak regulation characteristics of wind power.Thus,the most economical optimization scheme for the worst scenario of the output power of the generators is obtained,which proves the economy and reliability of the two-stage robust optimization method.
基金supported by the Science and Technology Project of State Grid Corporation of China“Key Technologies and Application of Distributed Swarm Intelligent Collaborative Control and Optimization for Energy Internet”(No.52100220002B)。
文摘In this paper,a novel multi-objective optimization model of integrated energy systems(IESs)is proposed based on the ladder-type carbon emission trading mechanism and refined load demand response strategies.First,the carbon emission trading mechanism is introduced into the optimal scheduling of IESs,and a ladder-type carbon emission cost calculation model based on rewards and penalties is established to strictly control the carbon emissions of the system.Then,according to different response characteristics of electric load and heating load,a refined load demand response model is built based on the price elasticity matrix and substitutability of energy supply mode.On these basis,a multi-objective optimization model of IESs is established,which aims to minimize the total operating cost and the renewable energy source(RES)curtailment.Finally,based on typical case studies,the simulation results show that the proposed model can effectively improve the economic benefits of IESs and the utilization efficiency of RESs.
基金This work was supported by National Natural Science Foundation of China(51607051)Fundamental Research Funds for the Central Universities(PA2021KCPY0053,JZ2019HGTB0077)Visiting Scholarship of State Key Laboratory of Power Transmission Equipment&System Security and New Technology(Chongqing University)(2007DA 105127).
文摘The energy storage system(ESS)as a demand-side management(DSM)resource can effectively smooth the load power fluctuation of a power system.However,designing a more reasonable ESS operational strategy will be a prerequisite before incorporating the energy storage device into DSM.As different load levels have different demands for the real-time chargedischarge power of an ESS,this paper proposes a heuristic ESS operation scheduling strategy which can take into account the electrical load demand differences.In this paper,firstly,two demand degree concepts for charging power and discharging power are defined to describe the differentiated ESS demand under the condition of different electrical load levels.Secondly,an inverse proportion technique based ESS scheduling strategy,with the consideration of the load demand difference,is proposed in this paper.Thirdly,some evaluating indices are defined in this paper for describing the influence of the proposed strategy on the smoothing degree of the daily load curve.Finally,several case studies are designed to verify the validity and correctness of the proposed technique,and the results show that the proposed technique can effectively smooth the load curve and improve the ability of peak shaving and valley filling.
文摘Utilities around the world have been considering Demand Side Management (DSM) in their strategic planning. The costs of constructing and operating a new capacity generation unit are increasing everyday as well as Transmission and distribution and land issues for new generation plants, which force the utilities to search for another alternatives without any additional constraints on customers comfort level or quality of delivered product. De can be defined as the selection, planning, and implementation of measures intended to have an influence on the demand or customer-side of the electric meter, either caused directly or stimulated indirectly by the utility. DSM programs are peak clipping, Valley filling, Load shifting, Load building, energy conservation and flexible load shape. The main Target of this paper is to show the relation between DSM and Load Forecasting. Moreover, it highlights on the effect of applying DSM on Forecasted demands and how this affects the planning strategies for utility companies. This target will be clearly illustrated through applying the developed algorithm in this paper on an existing residential compound in Cairo-Egypt.
文摘In the framework of liberalized deregulated electricity market, dynamic competitive environment exists between wholesale and retail dealers for energy supplying and management. Smart Grids topology in form of energy management has forced power supplying agencies to become globally competitive. Demand Response (DR) Programs in context with smart energy network have influenced prosumers and consumers towards it. In this paper Fair Emergency Demand Response Program (FEDRP) is integrated for managing the loads intelligently by using the platform of Smart Grids for Residential Setup. The paper also provides detailed modelling and analysis of respective demands of residential consumers in relation with economic load model for FEDRP. Due to increased customer’s partaking in this program the load on the utility is reduced and managed intelligently during emergency hours by providing fair and attractive incentives to residential clients, thus shifting peak load to off peak hours. The numerical and graphical results are matched for intelligent load management scenario.
文摘Lately,in modern smart power grids,energy demand for accurate forecast of electricity is gaining attention,with increased interest of research.This is due to the fact that a good energy demand forecast would lead to proper responses for electricity demand.In addition,proper energy demand forecast would ensure efficient planning of the electricity industry and is critical in the scheduling of the power grid capacity and management of the entire power network.As most power systems are been deregulated and with the rapid introduction and development of smart-metering technologies in Oman,new opportunities may arise considering the efficiency and reliability of the power system;like price-based demand response programs.These programs could either be a large scale for household,commercial or industrial users.However,excellent demand forecasting models are crucial for the deployment of these smart metering in the power grid based on good knowledge of the electricity market structure.Consequently,in this paper,an overview of the Oman regulatory regime,financial mechanism,price control,and distribution system security standard were presented.More so,the energy demand forecast in Oman was analysed,using the econometric model to forecasts its energy peak demand.The energy econometric analysis in this study describes the relationship between the growth of historical electricity consumption and macro-economic parameters(by region,and by tariff),considering a case study of Mazoon Electricity Distribution Company(MZEC),which is one of the major power distribution companies in Oman,for effective energy demand in the power grid.
文摘In recent years, Rwanda’s rapid economic development has created the “Rwanda Africa Wonder”, but it has also led to a substantial increase in energy consumption with the ambitious goal of reaching universal access by 2024. Meanwhile, on the basis of the rapid and dynamic connection of new households, there is uncertainty about generating, importing, and exporting energy whichever imposes a significant barrier. Long-Term Load Forecasting (LTLF) will be a key to the country’s utility plan to examine the dynamic electrical load demand growth patterns and facilitate long-term planning for better and more accurate power system master plan expansion. However, a Support Vector Machine (SVM) for long-term electric load forecasting is presented in this paper for accurate load mix planning. Considering that an individual forecasting model usually cannot work properly for LTLF, a hybrid Q-SVM will be introduced to improve forecasting accuracy. Finally, effectively assess model performance and efficiency, error metrics, and model benchmark parameters there assessed. The case study demonstrates that the new strategy is quite useful to improve LTLF accuracy. The historical electric load data of Rwanda Energy Group (REG), a national utility company from 1998 to 2020 was used to test the forecast model. The simulation results demonstrate the proposed algorithm enhanced better forecasting accuracy.
文摘This paper presents an advanced methodology for optimizing a UK network load demand with various uncertainties which are related to individual driving behaviours. Without the optimized regulation for traditional power system demand, EVs （electric vehicles） would have an adverse impact on the stability of power systems. This becomes more significant for large-scale EVs plugging into the power grid. Traditional optimized methodologies are effective only for EV charging. The proposed techniques improve the system flexibility and stability through an advanced optimization model and flexible bidirectional charging/discharging control. Three scenarios with different charging and discharging power levels and various penetration levels of EVs are discussed in detail in this paper. Simulation results demonstrate that bidirectional EV power flow control has vast potentials to improve the load demand profile, with increased proportion of EVs, and charging/discharging power levels.
