Optimal Scheduling Of Integrated Electricity And District Heating Systems Considering Demand Flexibility Of Aggregated Building Thermal Load

Recently,electricity and heat have become major forms of final energy consumption.The ever-increasing coupling and interactions among electricity and heat is based combined heat and power(CHP)units,which can also improve energy efficiency.Therefore,the development of heat and electricity integrated energy system(IHES)is a key means to solve the problems of fossil energy depletion and environmental pollution.Operational flexibility is one of the important attributes of IHES,which characterizes the ability of the system to cope with supply and demand fluctuations and other uncertain factors.The high flexibility has become the basis for coordinating electrical and heat energy and realizing large-scale integration of renewable energy.Thus,how to tap and utilize potential resources and improve the flexibility of the IHES has become a hotspot and challenge in energy field.Based on the above background,supported by National Science Fund for Distinguished Young Scholars(51725701),this paper focuses on the flexibility assessment method and optimization of the aggregated building thermal loads in IHES,which is aim to fully exploit and utilize the flexibility of the demand side and avoid the negative impact of its uncertainty,and significantly improve the operation efficiency and renewable energy integration of the IHES.The contributions can be summarized as:A model and data hybrid driven approach for quantifying the meteorologydependent potential flexibility of buildings thermal loads is proposed,which has twofold advantages of interpretability and learnability.First,the key parameters which have the obvious influence on demand flexibility of thermal loads are analyzed.To solve the problem that the key parameters are difficult to extract and measure,a twostage regression method based on the adaptive temporal data resolution is first proposed to extract them from the historical data,which can realize the description and assessment of historical thermal loads’ demand flexibility.Then,the particle swarm optimization optimized radial basis function neural network is used to establish the relationship between the key parameters and the meteorological parameters,so as to realize the accurate prediction of demand flexibility of aggregated buildings.The results show that when the proposed method is used to describe the flexibility level of thermal load,the time-varying of key parameters can improve the accuracy by about 10%.Further,when radial basis neural network is optimized by particle swarm,the prediction accuracy compared with the ordinary radial basis neural network can be improved by nearly 20%.Based on the prediction method of demand flexibility of aggregated buildings’ thermal loads,in this part,the optimal operation model of single-area of IHES which considers the demand flexibility of aggregated building thermal loads is proposed.First,causes of multi-source uncertainty in the process of demand flexibility prediction of aggregated building thermal loads are analyzed.Aiming at the large difference in the magnitude of the multi-source information describing the uncertainty of some key parameters,an improved evidence theory is proposed to integrate the multi-source information contained in the uncertainty to obtain expert opinions describing the uncertainty.Then,combining Latin Hypercube Sampling and fuzzy clustering technology to generate typical scenarios describing the randomness of expert opinion.Last,a cooperative scheduling model of IHES based on random scenarios is proposed.The objective function is to minimize the operating cost.The results show that when the influence of multi-source uncertainty is comprehensively considered,the prediction accuracy of demand flexibility is improved by nearly 50%.The wind curtailment of the6-node and large-scale regional IHES decreased by 6.7% and 2.6%,respectively.On the basis of the above-mentioned coordinated dispatch model of the singleregion IHES,the multi-area IHES coordinated dispatch model is established,which has considered the sharing of demand flexibility of thermal loads and the coordinated dispatch solution method.First,the limitations of single-area IHES cooperative operation in performance of wind integration are analyzed.Combining transmission characteristics of electric and heat,the demand flexibility sharing mode of multi-area IHES is established.Then,a joint optimal operation model of the multi-area IHES is established.Last,the alternating direction method of multipliers is used to solve the regional-level distributed solution of the multi-area IHES,the cases analysis shows that:through flexible sharing of multiple areas,the wind curtailment in each area can be significantly improved and achieve the dual purpose of independent energy dispatching between areas and improvement of the energy efficiency and flexibility of the entire system.