Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy couplin...Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy coupling equipment,and renewable energy.An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost,carbon emission and enhance the power supply reliability.Firstly,the lowcarbon mathematical model of combined thermal and power unit,carbon capture system and power to gas unit(CCP)is established.Subsequently,we establish a low carbon multi-objective optimization model considering system operation cost,carbon emissions cost,integrated demand response,wind and photovoltaic curtailment,and load shedding costs.Furthermore,considering the intermittency of wind power generation and the flexibility of load demand,the low carbon economic dispatch problem is modeled as a Markov decision process.The twin delayed deep deterministic policy gradient(TD3)algorithm is used to solve the complex scheduling problem.The effectiveness of the proposed method is verified in the simulation case studies.Compared with TD3,SAC,A3C,DDPG and DQN algorithms,the operating cost is reduced by 8.6%,4.3%,6.1%and 8.0%.展开更多
The health status of distribution equipment and networks is not considered directly in existing distribution network planning methods.In order to effectively consider the health status and deal with the risk associate...The health status of distribution equipment and networks is not considered directly in existing distribution network planning methods.In order to effectively consider the health status and deal with the risk associated with load and renewable generation uncertainties,this paper presents a new optimal expansion planning approach for distribution network(EPADN)incorporating equipment’s health index(HI)and non-network solutions(NNSs).HI and relevant risk are used to help develop the optimal equipment replacement strategy and temporary NNSs are considered as promising options for handling the uncertainties of load growth,reliability requirements of power supply and output of distributed energy resources(DERs)at a lower cost than network alternatives.An EPADN model using network solutions(NSs)and NNSs is proposed.The planning objectives of the proposed model are safety,reliability,economy,and‘greenness’that are also the meaning of distribution network HI.A method integrating an improved niche genetic algorithm(INGA)and a spanning tree algorithm(STA)is fitted to solve the model presented here for real sized networks with a manageable computational cost.Simulation results of an actual 22-node distribution network in China,illustrate the effectiveness of the proposed approach.展开更多
The paper considers the quantity and causes of outages in electric grids of low and medium voltages using the example of an electric grid of a regional power supply company.The main types of damage to the equipment of...The paper considers the quantity and causes of outages in electric grids of low and medium voltages using the example of an electric grid of a regional power supply company.The main types of damage to the equipment of power lines and transformer substations were identified.Data on other areas of rural and urban electric grids are also analyzed.The main directions for reducing the quantity of outages in electric grids are proposed based on this analysis.Among them,there are the use of isolated wires in power transmission lines,the improvement of design of switching devices,switches and terminals of transformers,the application of technical condition diagnostics,the disaggregating of power lines and the increase of protection sensitivity of power lines.Most of the causes of equipment damage can be prevented by increasing the maintenance level of this equipment.展开更多
基金supported in part by the Scientific Research Fund of Liaoning Provincial Education Department under Grant LQGD2019005in part by the Doctoral Start-up Foundation of Liaoning Province under Grant 2020-BS-141.
文摘Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy coupling equipment,and renewable energy.An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost,carbon emission and enhance the power supply reliability.Firstly,the lowcarbon mathematical model of combined thermal and power unit,carbon capture system and power to gas unit(CCP)is established.Subsequently,we establish a low carbon multi-objective optimization model considering system operation cost,carbon emissions cost,integrated demand response,wind and photovoltaic curtailment,and load shedding costs.Furthermore,considering the intermittency of wind power generation and the flexibility of load demand,the low carbon economic dispatch problem is modeled as a Markov decision process.The twin delayed deep deterministic policy gradient(TD3)algorithm is used to solve the complex scheduling problem.The effectiveness of the proposed method is verified in the simulation case studies.Compared with TD3,SAC,A3C,DDPG and DQN algorithms,the operating cost is reduced by 8.6%,4.3%,6.1%and 8.0%.
基金This work was supported in part by the Science and Technology Project of SGCC under Grant No.PD71-18-023.
文摘The health status of distribution equipment and networks is not considered directly in existing distribution network planning methods.In order to effectively consider the health status and deal with the risk associated with load and renewable generation uncertainties,this paper presents a new optimal expansion planning approach for distribution network(EPADN)incorporating equipment’s health index(HI)and non-network solutions(NNSs).HI and relevant risk are used to help develop the optimal equipment replacement strategy and temporary NNSs are considered as promising options for handling the uncertainties of load growth,reliability requirements of power supply and output of distributed energy resources(DERs)at a lower cost than network alternatives.An EPADN model using network solutions(NSs)and NNSs is proposed.The planning objectives of the proposed model are safety,reliability,economy,and‘greenness’that are also the meaning of distribution network HI.A method integrating an improved niche genetic algorithm(INGA)and a spanning tree algorithm(STA)is fitted to solve the model presented here for real sized networks with a manageable computational cost.Simulation results of an actual 22-node distribution network in China,illustrate the effectiveness of the proposed approach.
文摘The paper considers the quantity and causes of outages in electric grids of low and medium voltages using the example of an electric grid of a regional power supply company.The main types of damage to the equipment of power lines and transformer substations were identified.Data on other areas of rural and urban electric grids are also analyzed.The main directions for reducing the quantity of outages in electric grids are proposed based on this analysis.Among them,there are the use of isolated wires in power transmission lines,the improvement of design of switching devices,switches and terminals of transformers,the application of technical condition diagnostics,the disaggregating of power lines and the increase of protection sensitivity of power lines.Most of the causes of equipment damage can be prevented by increasing the maintenance level of this equipment.
