Multi-Objective Optimization Strategy of Integrated Electric-Heat System Based on Energy Storage Situation Division

There are the transmission loss of the electric power network, the delay and loss of the heating network, the insufficient utilization of flexible resources such as energy storage in the integrated electric-heat system, which may lead to the imbalance of supply and demand and energy waste. In this paper, the coordinated dispatch of integrated electric-heat system (IEHS) considering the transmission characteristics of the electric power network and heating network, which is formulated as a convex quadratic program. The strong linkage of electric power and heat supplies can be decoupled to reduce wind power curtailment by exploiting the energy storage and regulation capabilities of the district heating network (DHN), storage batteries, electric boilers (EBs) and heat storage tanks (HSs). The energy storage system works according to the situation division strategy designed in this paper. This paper introduces the wind curtailment boundary power and optimizes dispatch based on the wind curtailment boundary power and unit output, which can make full use of the energy storage capacity and reduce the wind abandonment power. Since the electric power system (EPS) and the distribution heating system (DHS) are controlled separately by different operation organizations, IEHS is solved using double- $\lambda $ iterative algorithm. The double- $\lambda $ iterative algorithm, with guaranteed convergence for convex programs, can achieve a fully distributed solution for the IEHS and requires only a small amount boundary information exchange between the EPS and the DHS. At last, one integrated electric-heat system was studied to demonstrate the effectiveness of the proposed method which achieves the effective solution in a moderate number of iterations. This system includes two 10-nodes heating system and one 14-nodes electric power system.

[1]  Qinghua Wu,et al.  Modelling and operation optimization of an integrated energy based direct district water-heating system , 2014 .

[2]  M. Jaberipour,et al.  Harmony search algorithm for solving combined heat and power economic dispatch problems , 2011 .

[3]  Tao Guo,et al.  An algorithm for combined heat and power economic dispatch , 1996 .

[4]  Sayyad Nojavan,et al.  Energy storage system and demand response program effects on stochastic energy procurement of large consumers considering renewable generation , 2016 .

[5]  Vijay Vittal,et al.  Statistical Characterization of Wind Power Ramps Via Extreme Value Analysis , 2014, IEEE Transactions on Power Systems.

[6]  Haibo Lan,et al.  Hierarchical Model Predictive Control Strategy Based on Dynamic Active Power Dispatch for Wind Power Cluster Integration , 2019, IEEE Transactions on Power Systems.

[7]  L. Yao,et al.  Two-Stage Optimization of Battery Energy Storage Capacity to Decrease Wind Power Curtailment in Grid-Connected Wind Farms , 2018, IEEE Transactions on Power Systems.

[8]  Yue Li,et al.  Evaluating system reliability and targeted hardening strategies of power distribution systems subjected to hurricanes , 2015, Reliab. Eng. Syst. Saf..

[9]  G. W. Becker,et al.  Storm & flood hardening of electrical substations , 2014, 2014 IEEE PES T&D Conference and Exposition.

[10]  Xue Li,et al.  Collaborative scheduling and flexibility assessment of integrated electricity and district heating systems utilizing thermal inertia of district heating network and aggregated buildings , 2020 .

[11]  Mehmet Yesilbudak,et al.  Clustering analysis of multidimensional wind speed data using k-means approach , 2016, 2016 IEEE International Conference on Renewable Energy Research and Applications (ICRERA).

[12]  Beni Cukurel,et al.  Economic Dispatch of a Single Micro-Gas Turbine Under CHP Operation with Uncertain Demands , 2017, ArXiv.

[13]  Ali Reza Seifi,et al.  Stochastic multi-objective optimization of combined heat and power economic/emission dispatch , 2017 .

[14]  Zhe Chen,et al.  Optimal Operation of the Integrated Electrical and Heating Systems to Accommodate the Intermittent Renewable Sources , 2016 .

[15]  Mohammad Shahidehpour,et al.  Combined Heat and Power Dispatch Considering Pipeline Energy Storage of District Heating Network , 2016, IEEE Transactions on Sustainable Energy.

[16]  Hongbin Sun,et al.  Feasible region method based integrated heat and electricity dispatch considering building thermal inertia , 2017 .

[17]  Yaroslav D. Sergeyev,et al.  Solving the Lexicographic Multi-Objective Mixed-Integer Linear Programming Problem using branch-and-bound and grossone methodology , 2020, Commun. Nonlinear Sci. Numer. Simul..

[18]  Chongqing Kang,et al.  Reducing curtailment of wind electricity in China by employing electric boilers for heat and pumped hydro for energy storage , 2016 .

[19]  Jinbo Huang,et al.  Coordinated dispatch of electric power and district heating networks: A decentralized solution using optimality condition decomposition , 2017 .

[20]  Hongbin Sun,et al.  Fully Distributed Quasi-Newton Multi-Area Dynamic Economic Dispatch Method for Active Distribution Networks , 2018, IEEE Transactions on Power Systems.

[21]  Q. H. Wu,et al.  Multi-objective optimization and decision making for power dispatch of a large-scale integrated energy system with distributed DHCs embedded , 2015 .

[22]  Henrik Madsen,et al.  Economic valuation of heat pumps and electric boilers in the Danish energy system , 2016 .

[23]  T. J. Stonham,et al.  Combined heat and power economic dispatch by improved ant colony search algorithm , 1999 .

[24]  Risto Lahdelma,et al.  Developing a multicriteria decision support framework for CHP based combined district heating systems , 2017 .

[25]  B. Mohammadi-ivatloo,et al.  Combined heat and power economic dispatch problem solution using particle swarm optimization with ti , 2013 .

[26]  Zhao Yang Dong,et al.  Optimal operation of DES/CCHP based regional multi-energy prosumer with demand response , 2016 .