| Facing the double pressure of fossil energy depletion and environmental degradation,the global society is in a critical period of energy technology innovation and development.In this context,improving the penetration of renewable energy generation which is represented by wind power and photovoltaic power is one of the essential ways to solve the energy problems of human society.At the same time,considering the coupling of various types of energy to improve energy consumption efficiency is also an important method to achieve social sustainable development,and the concept of an integrated energy system has been proposed.However,the uncertainty of renewable energy further enhances the disorder and mismatch between the energy supply side and the energy consumption side.Therefore,energy storage,as an energy transfer carrier,plays an important role in modern energy networks and is a key link of integrated energy systems,which has many functions such as improving energy efficiency and system flexibility.With the progress of energy storage technologies,its application scenarios and functions are also expanded.In terms of the energy storage optimization problem in the user-side integrated energy system,this paper studies the energy storage allocation and energy management,and provides suggestions on energy storage configuration and scheduling for industrial users in different scenarios.The main research work of this paper is as follows:1.A planning and scheduling model for the battery energy storage system(BESS)considering user-side demand management is proposed.Under a two-part time-sharing electricity price mechanism,the model takes the total net proceeds of user-side BESS within its life cycle as the outer level objective function,considering the income of peak load shaving,arbitrage income,and life cycle cost.The model takes a net daily income of BESS as the inner level objective function to optimize the charge-discharge curve of BESS.The genetic algorithm combined with mixed integer linear programming is adopted to solve the bi-level optimization model based on a practical project.The configurations,peak shaving rates,and net proceeds of the lithium-ion battery and the lead-carbon battery are compared through case studies,and the effects of load curve characteristics,cost of unit energy storage,and energy conversion efficiency on economic benefit are analyzed,and some suggestions on industrial user-side configuration plan of the battery are provided.2.An optimal sizing method for electrical/thermal hybrid energy storage in the user-side integrated energy system considering the degradation of energy storage is proposed,in which the profit strategies include reducing wind curtailment,optimizing the electric and thermal load curves,and coordinated operation with combined heat and power generation units.The discrete Fourier transform is used to analyze the load data and obtain the period of the load curve,so as to determine the energy storage scheduling period.Load characteristic indexes are selected to reduce the dimension of load data,and typical load curves are obtained by the clustering algorithm.A hybrid energy storage optimal configuration model of the integrated energy system considering energy storage loss is established and the minimum energy cost of the system in the energy storage life cost is taken as the objective function.Based on the proposed model,the optimal configuration scheme of hybrid energy storage in the integrated energy system is presented.Furthermore,the impact of the energy storage scheduling cycle and typical load curves on energy storage configuration results is analyzed.3.A two-stage coordinated scheduling method is proposed for the user-side integrated energy system that considers energy storage multiple services to minimize long-term operation costs.Besides,the proposed scheduling model is based on a two-part time-of-use electricity price mechanism.The first stage of the model determines the daily initial state of charge of energy storage,the demand management coefficient,and the baseline of demand response.The second stage is intra-day rolling scheduling,and the power scheduling of each unit in the system is optimized under the premise that the closer the time period,the higher the prediction accuracy.Energy storage is investigated for four main service options: 1)demand management;2)demand response;3)energy arbitrage;4)providing reserve capacity.At the same time,a linear energy storage degradation cost model is established.The combined goal programming and dependent chance programming in the fuzzy environment is implemented to obtain a scheduling plan efficiently and to ensure the system’s economy and the most possibility of the events of power balance in an uncertain environment.The effectiveness of the proposed model is verified by comparing and analyzing different energy storage loss cost models,system scheduling strategies,and different solutions in the fuzzy environment.The impact of electricity price policy and power unbalance on the system operation cost is analyzed.4.A robust optimization scheduling method for interconnected user-side multi-energy microgrids considering equipment rescheduling is proposed.Firstly,the architecture of the multi-energy microgrids system with electrical/thermal energy interconnection is introduced,and the rescheduling models of power generation equipment and energy storage equipment are presented,in which the energy coupling of energy storage in the scheduling and regulation stages is considered.Secondly,the regional day-ahead robust scheduling model of multi-energy microgrids considering electric/thermal energy sharing network is established,which takes into account the scheduling cost based on prediction scenarios and the regulation cost considering uncertain scenarios.Finally,the robust optimization module in the solver is called to solve the centralized optimization.The simulation example proves that the interconnected system improves the region’s flexibility and the efficiency of the two-stage energy storage scheduling model. |
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