Integrated Electricity- Heat-Gas Systems: Techno-Economic Modeling, Optimization, and Application to Multienergy Districts

被引:74
作者
Martinez Cesena, Eduardo Alejandro [1 ]
Loukarakis, Emmanouil [2 ,3 ]
Good, Nicholas [2 ,4 ]
Mancarella, Pierluigi [5 ,6 ]
机构
[1] Univ Manchester UoM, Dept Elect & Elect Engn EEE, Manchester M13 9PL, Lancs, England
[2] Univ Manchester UoM, Manchester M13 9PL, Lancs, England
[3] Levelise Ltd, Oxford OX4 4GB, England
[4] Upside Energy Ltd, Manchester M1 1DF, Lancs, England
[5] Univ Melbourne, Dept Elect & Elect Engn, Melbourne, Vic 3010, Australia
[6] Univ Manchester, Manchester M13 9PL, Lancs, England
基金
英国工程与自然科学研究理事会;
关键词
Buildings; Optimization; Mathematical model; Cogeneration; Resistance heating; Renewable energy sources; Linear systems; Energy measurement; Integrated electricity-heat-gas networks; integrated energy systems; multienergy district (MED); multienergy systems (MES); power system flexibility; POWER-TO-GAS; BUSINESS CASE ASSESSMENT; NATURAL-GAS; DEMAND RESPONSE; ENERGY-HUB; UNIT COMMITMENT; FLOW ANALYSIS; NETWORK; FLEXIBILITY; INFRASTRUCTURE;
D O I
10.1109/JPROC.2020.2989382
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Multienergy systems (MES) can optimally deploy their internal operational flexibility to use combinations of different energy vectors to meet the needs of end-users and potentially support the wider system. Key relevant applications of MES are multienergy districts (MEDs) with, for example, integrated electricity and gas distribution and district heating networks. Simulation and optimization of MEDs is a grand challenge requiring sophisticated techno-economic tools that are capable of modeling buildings and distributed energy resources (DERs) across multienergy networks. This article provides a tutorial-like overview of the state-of-the-art concepts for techno-economic modeling and optimization of integrated electricity-heat-gas systems in flexible MEDs, also considering operational uncertainty and multiple grid support services. Relevant mixed integer linear programming (MILP) formulations for two-stage stochastic scheduling of buildings and DER, iteratively soft-coupled to nonlinear network models, are then presented as the basis of a practical network-constrained MED energy management tool developed in several projects. The concepts presented are demonstrated through real-world applications based on The University of Manchester MED case study, the details of which are also provided as a testbed for future research.
引用
收藏
页码:1392 / 1410
页数:19
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