| Driven by the"Third industrial revolution",modern energy system has developed into Energy Internet(EI).The core of El is power system,which is mutually integrated with natural gas,thermal and transportation systems.The interaction among various energy networks makes system scheduling more challenging.Meanwhile,with the advancement of electricity market policies,demand response(DR)can involve in system operation more actively and flexibly,which provides new regulatory options for the economic,safe and stable dispatch of El.Based on these backgrounds,this research starts from the subject of DR participating in Energy Internet scheduling,and studies the dynamic modeling of integrated energy system(IES),decoupled-coordinated optimization of integrated power-gas system and stochastic optimization of multi-energy system based on energy hubs.The main contents achievements of this research are summarized as follows:(1)Based on electricity demand response and facing Energy Internet environment,multiple types of integrated demand response are modelled.The proposed demand response strategy can be divided into three forms:price-based DR,incentive-based DR and alternative DR.Each DR program can broaden the feasible region of integrated energy system and provide buffer for system operation.Systematic analysis of current DR projects including their characteristic and future challenges are provided,which further prove the necessity of this research.(2)A day-ahead scheduling method for IES considering dynamic gas flow and demand response is proposed.Based on the price signal and energy balance,this model introduces price-based and alternative DR to describe the time-shifting among same kind of energy and the substitution among different kinds of energy,which flatten load curve and hence improve system efficiency effectively.Meanwhile,time-space differential dynamic gas flow is considered in the model to analyze multi-energy flows in detail,improving calculation accuracy.Second-order cone relaxation is applied to the non-convex natural gas flow,and sequential optimization method(SOM)is applied to solve the relaxed day-ahead scheduling model to ensure its feasibility.(3)A decoupled-coordinated dispatch method for integrated power-gas system with demand response is proposed.To overcome the disadvantages such as vast data collection,heavy communication burden and complex optimization model of traditional centralized pattern,a decentralized framework is proposed while synchronous and asynchronous ADMM algorithms are compared.On this basis,price-based DR is considered for IES operational economy.Electricity users can be guided to shift their peak load to off-peak periods by price signal,and system congestion is therefore alleviated.The proposed decoupled-coordinated dispatch method can realize the autonomous decision-making of intelligent agents while guaranteeing information privacy among them.(4)A stochastic optimization method for Energy Intenet considering integrated demand-side response is put forward.Typical scenarios for wind power fluctuations are obtained by backward scenario reduction,whose impacts on system operational economy and renewable energy consumption are analyzed.Facing El environment,demand response program is expanded into internal DR realized through the optimal configuration within energy hubs,and external DR realized through end-users' adjustment.For solution efficiency,linear matrix is applied to describe the output-input relationship in each energy hub,and a unified model coupling transmission network and energy hubs is established.Sequential linearization method is proposed to balance solution accuracy and computational efficiency. |
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