In this paper,interval number optimization and model predictive control are proposed to handle the uncertain-but-bounded parameters in electric water heater load scheduling.First of all,interval numbers are used to de...In this paper,interval number optimization and model predictive control are proposed to handle the uncertain-but-bounded parameters in electric water heater load scheduling.First of all,interval numbers are used to describe uncertain parameters including hot water demand,ambient temperature,and real-time price of electricity.Moreover,the traditional thermal dynamic model of electric water heater is transformed into an interval number model,based on which,the day-ahead load scheduling problem with uncertain parameters is formulated,and solved by interval number optimization.Different tolerance degrees for constraint violation and temperature preferences are also discussed for giving consumers more choices.Furthermore,the model predictive control which incorporates both forecasts and newly updated information is utilized to make and execute electric water heater load schedules on a rolling basis throughout the day.Simulation results demonstrate that interval number optimization either in day-ahead optimization or model predictive control format is robust to the uncertain hot water demand,ambient temperature,and real-time price of electricity,enabling customers to flexibly adjust electric water heater control strategy.展开更多
Integration of large number of electric vehicles(EVs)with distribution networks is devastating for conventional power system devices such as transformers and power lines etc.This paper proposes a methodology for manag...Integration of large number of electric vehicles(EVs)with distribution networks is devastating for conventional power system devices such as transformers and power lines etc.This paper proposes a methodology for management of responsive household appliances management and EVs with water-filling algorithm.With the proposed scheme,the load profile of a transformer is retained below its rated capacity while minimally affecting the associated consumers.When the instantaneous demand at transformer increases beyond its capacity,the proposed methodology dynamically allocates demand curtailment limit(DCL)to each home served by transformer.The DCL allocation takes convenience factors,load profile and information of flexible appliances into account to assure the comfort of all the consumers.The proposed scheme is verified by modeling and simulating five houses and a distribution transformer.The smart appliances such as an HVAC,a water heater,a cloth dryer and an EV are also modeled for the study.Results show that the proposed scheme performs to reduce overloading effects of the transformer efficiently and assures comfort of the consumers at the same time.展开更多
This paper presents a demand dispatch strategy of aggregated electric water heaters(EWHs) for a load aggregation system at demand side, based on the theory of cyber-physical system. The objective is to solve the probl...This paper presents a demand dispatch strategy of aggregated electric water heaters(EWHs) for a load aggregation system at demand side, based on the theory of cyber-physical system. The objective is to solve the problem of water heater load control when the cyber-physical load aggregation system participates in demand dispatch of the power grid. First, an implementation framework of the demand dispatch strategy is designed between the cyber space and the physical space, including state awareness,real-time analysis, scientific decision-making and precise execution. Second, a multilevel incentive model, an EWH appliance model and a thermostat setpoint control rule are introduced. Next, based on the models and the rule, the state awareness logic, real-time analysis logic, scientific decision-making logic and precise execution logic of the strategy are designed to implement demand dispatch of aggregated EWHs. Finally, simulation results confirm the effectiveness, the advantage and excellent scalability of the proposed strategy.展开更多
基金This work was supported by the National Natural Science Foundation of China(Grant No.51477111)the National Key Research and Development Program of China(Grant No.2016 YFB-0901102).
文摘In this paper,interval number optimization and model predictive control are proposed to handle the uncertain-but-bounded parameters in electric water heater load scheduling.First of all,interval numbers are used to describe uncertain parameters including hot water demand,ambient temperature,and real-time price of electricity.Moreover,the traditional thermal dynamic model of electric water heater is transformed into an interval number model,based on which,the day-ahead load scheduling problem with uncertain parameters is formulated,and solved by interval number optimization.Different tolerance degrees for constraint violation and temperature preferences are also discussed for giving consumers more choices.Furthermore,the model predictive control which incorporates both forecasts and newly updated information is utilized to make and execute electric water heater load schedules on a rolling basis throughout the day.Simulation results demonstrate that interval number optimization either in day-ahead optimization or model predictive control format is robust to the uncertain hot water demand,ambient temperature,and real-time price of electricity,enabling customers to flexibly adjust electric water heater control strategy.
基金supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea government (MSIP) (No.2015R1A2A1A10052459)
文摘Integration of large number of electric vehicles(EVs)with distribution networks is devastating for conventional power system devices such as transformers and power lines etc.This paper proposes a methodology for management of responsive household appliances management and EVs with water-filling algorithm.With the proposed scheme,the load profile of a transformer is retained below its rated capacity while minimally affecting the associated consumers.When the instantaneous demand at transformer increases beyond its capacity,the proposed methodology dynamically allocates demand curtailment limit(DCL)to each home served by transformer.The DCL allocation takes convenience factors,load profile and information of flexible appliances into account to assure the comfort of all the consumers.The proposed scheme is verified by modeling and simulating five houses and a distribution transformer.The smart appliances such as an HVAC,a water heater,a cloth dryer and an EV are also modeled for the study.Results show that the proposed scheme performs to reduce overloading effects of the transformer efficiently and assures comfort of the consumers at the same time.
基金supported by National Natural Science Foundation of China(No.51777068)Fundamental Research Funds for the Central Universities(No.2016XS15)
文摘This paper presents a demand dispatch strategy of aggregated electric water heaters(EWHs) for a load aggregation system at demand side, based on the theory of cyber-physical system. The objective is to solve the problem of water heater load control when the cyber-physical load aggregation system participates in demand dispatch of the power grid. First, an implementation framework of the demand dispatch strategy is designed between the cyber space and the physical space, including state awareness,real-time analysis, scientific decision-making and precise execution. Second, a multilevel incentive model, an EWH appliance model and a thermostat setpoint control rule are introduced. Next, based on the models and the rule, the state awareness logic, real-time analysis logic, scientific decision-making logic and precise execution logic of the strategy are designed to implement demand dispatch of aggregated EWHs. Finally, simulation results confirm the effectiveness, the advantage and excellent scalability of the proposed strategy.
