Economic-environmental analysis of combined heat and power-based reconfigurable microgrid integrated with multiple energy storage and demand response program

被引:78
作者
Hemmati, Mohammad [1 ]
Mirzaei, Mohammad Amin [1 ]
Abapour, Mehdi [1 ]
Zare, Kazem [1 ]
Mohammadi-ivatloo, Behnam [1 ,2 ]
Mehrjerdi, Hassan [3 ]
Marzband, Mousa [4 ]
机构
[1] Univ Tabriz, Fac Elect & Comp Engn, Tabriz, Iran
[2] Aalborg Univ, Dept Energy Technol, DK-9220 Aalborg, Denmark
[3] Qatar Univ, Elect Engn Dept, Doha, Qatar
[4] Northumbria Univ, Dept Math Phys & Elect Engn, Newcastle Upon Tyne, Tyne & Wear, England
关键词
Reconfigurable microgrid; Multi-objective optimization; Compressed air energy storage; Emission; RENEWABLE ENERGY; DISPATCH; OPTIMIZATION; GENERATION; MANAGEMENT; SYSTEMS; UNCERTAINTIES; IMPACT; MODEL;
D O I
10.1016/j.scs.2021.102790
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Microgrids (MGs) are solutions to integrate high shares of variable renewable energy which can contribute to more economical and environmental benefits, as well as improving the energy supply efficiency. One significant potential of MGs is an expanded opportunity to use the waste heating energy from the conversion of the primary fuel (such as natural gas) to generate electricity. The use of waste heat in combined heat and power (CHP)-based MG is more efficient to meet local load and decrease the emission pollution. Hence, this paper elaborates on optimal multi-objective scheduling of CHP-based MG coupled with compressed air energy storage (CAES), renewable energy, thermal energy storage (TES), and demand response programs through shiftable loads, which considers a reconfiguration capability. The embedded CAES, in addition to the charging/discharging scheme, can operate in a simple cycling mode and serve as a generation resource to supply local load in an emergency condition. The daily reconfiguration of MG will introduce a new generation of MG named reconfigurable microgrid (RMG) that offers more flexibility and enhances system reliability. The RMG is coupled with TES to facilitate the integration of the CHP unit that enables the operator to participate in the thermal market, in addition to the power market. The main intents of the proposed multi-objective problem are to minimize the operation cost along with a reduction in carbon emission. The epsilon-constraint technique is used to solve the multi-objective problem while fuzzy decision making is implemented to select an optimal solution among all the Pareto solutions. The electricity prices and wind power generation variation are captured as random variables in the model and the scenario-based stochastic approach is used to handle them. Simulation results prove that the simultaneous integration of multiple technologies in CHP-based RMG decreases the operation cost and emission up to 3 % and 10.28 %, respectively.
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页数:16
相关论文
共 46 条
[1]   Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems) [J].
Aghaei, Jamshid ;
Alizadeh, Mohammad-Iman .
ENERGY, 2013, 55 :1044-1054
[2]   Flexible scheduling of reconfigurable microgrid-based distribution networks considering demand response program [J].
Ajoulabadi, Ata ;
Ravadanegh, Sajad Najafi ;
Mohammadi-Ivatloo, Behnam .
ENERGY, 2020, 196
[3]   Real-time price-based demand response model for combined heat and power systems [J].
Alipour, Manijeh ;
Zare, Kazem ;
Seyedi, Heresh ;
Jalali, Mehdi .
ENERGY, 2019, 168 (1119-1127) :1119-1127
[4]   Stochastic Scheduling of Renewable and CHP-Based Microgrids [J].
Alipour, Manijeh ;
Mohammadi-Ivatloo, Behnam ;
Zare, Kazem .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2015, 11 (05) :1049-1058
[5]   Techno-economic optimization of hybrid photovoltaic/wind generation together with energy storage system in a stand-alone micro-grid subjected to demand response [J].
Amrollahi, Mohammad Hossein ;
Bathaee, Seyyed Mohammad Taghi .
APPLIED ENERGY, 2017, 202 :66-77
[6]   Microgrid reliability modeling and battery scheduling using stochastic linear programming [J].
Cardoso, G. ;
Stadler, M. ;
Siddiqui, A. ;
Marnay, C. ;
DeForest, N. ;
Barbosa-Povoa, A. ;
Ferrao, P. .
ELECTRIC POWER SYSTEMS RESEARCH, 2013, 103 :61-69
[7]   A robust optimization method for bidding strategy by considering the compressed air energy storage [J].
Dash, Surya Narayan ;
Padhi, Radha Krushna ;
Dora, Tapas ;
Surendar, A. ;
Cristan, Karen .
SUSTAINABLE CITIES AND SOCIETY, 2019, 48
[8]   Solving multi-objective economic emission dispatch of a renewable integrated microgrid using latest bio-inspired algorithms [J].
Dey, Bishwajit ;
Roy, Shyamal Krishna ;
Bhattacharyya, Biplab .
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH, 2019, 22 (01) :55-66
[9]   Optimal simultaneous day-ahead scheduling and hourly reconfiguration of distribution systems considering responsive loads [J].
Esmaeili, Saeid ;
Anvari-Moghaddam, Amjad ;
Jadid, Shahram ;
Guerrero, Josep M. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2019, 104 :537-548
[10]  
Gazijahani F. S., 2018, IEEE T SUSTAINABLE E, P1