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

Abstract 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.

[1]  Bishwajit Dey,et al.  Solving multi-objective economic emission dispatch of a renewable integrated microgrid using latest bio-inspired algorithms , 2019, Engineering Science and Technology, an International Journal.

[2]  Joao P. S. Catalao,et al.  Integration of emerging resources in IGDT-based robust scheduling of combined power and natural gas systems considering flexible ramping products , 2019 .

[3]  Mostafa Sedighizadeh,et al.  Stochastic multi-objective energy management in residential microgrids with combined cooling, heating, and power units considering battery energy storage systems and plug-in hybrid electric vehicles , 2018, Journal of Cleaner Production.

[4]  Wayes Tushar,et al.  Energy Management for Joint Operation of CHP and PV Prosumers Inside a Grid-Connected Microgrid: A Game Theoretic Approach , 2016, IEEE Transactions on Industrial Informatics.

[5]  Behnam Mohammadi-Ivatloo,et al.  Flexible scheduling of reconfigurable microgrid-based distribution networks considering demand response program , 2020 .

[6]  Yongli Wang,et al.  Energy management of smart micro-grid with response loads and distributed generation considering demand response , 2018, Journal of Cleaner Production.

[7]  B. Llamas,et al.  Mini-CAES as a reliable and novel approach to storing renewable energy in salt domes , 2018 .

[8]  Behnam Mohammadi-Ivatloo,et al.  Network constrained economic dispatch of renewable energy and CHP based microgrids , 2019, International Journal of Electrical Power & Energy Systems.

[9]  S. M. Moghaddas-Tafreshi,et al.  Microgrid operation and management using probabilistic reconfiguration and unit commitment , 2016 .

[10]  Miguel Brito,et al.  Impact of solar and wind forecast uncertainties on demand response of isolated microgrids , 2016 .

[11]  Manijeh Alipour,et al.  Stochastic Scheduling of Renewable and CHP-Based Microgrids , 2015, IEEE Transactions on Industrial Informatics.

[12]  Amjad Anvari-Moghaddam,et al.  Optimal Operational Scheduling of Reconfigurable Microgrids in Presence of Renewable Energy Sources , 2019 .

[13]  Wei-Jen Lee,et al.  A bi-level program for the planning of an islanded microgrid including CAES , 2016, 2015 IEEE Industry Applications Society Annual Meeting.

[14]  Servando Álvarez Domínguez,et al.  Building thermal storage technology: Compensating renewable energy fluctuations , 2020 .

[15]  S.M.T. Bathaee,et al.  Techno-economic optimization of hybrid photovoltaic/wind generation together with energy storage system in a stand-alone micro-grid subjected to demand response , 2017 .

[16]  M. M. Ardehali,et al.  A novel approach for optimal economic dispatch scheduling of integrated combined heat and power systems for maximum economic profit and minimum environmental emissions based on Benders decomposition , 2016 .

[17]  Wei Gu,et al.  A two-stage optimization and control for CCHP microgrid energy management , 2017 .

[18]  Abdolsalam Ghaderi,et al.  Simultaneous power and heat scheduling of microgrids considering operational uncertainties: A new stochastic p-robust optimization approach , 2019, Energy.

[19]  Amir Abdollahi,et al.  A MILP IGDT-based self-scheduling model for participating in electricity markets , 2016, 2016 24th Iranian Conference on Electrical Engineering (ICEE).

[20]  Yan Xu,et al.  Optimal coordinated energy dispatch of a multi-energy microgrid in grid-connected and islanded modes , 2018 .

[21]  Mehdi Abapour,et al.  A novel hybrid two-stage framework for flexible bidding strategy of reconfigurable micro-grid in day-ahead and real-time markets , 2020 .

[22]  A. Surendar,et al.  A robust optimization method for bidding strategy by considering the compressed air energy storage , 2019 .

[23]  Behnam Mohammadi-Ivatloo,et al.  Stochastic multi-objective dynamic dispatch of renewable and CHP-based islanded microgrids , 2019, Electric Power Systems Research.

[24]  N. Amjady,et al.  Risk-Constrained Bidding and Offering Strategy for a Merchant Compressed Air Energy Storage Plant , 2017, IEEE Transactions on Power Systems.

[25]  Mostafa Sedighizadeh,et al.  Stochastic multi-objective economic-environmental energy and reserve scheduling of microgrids considering battery energy storage system , 2019, International Journal of Electrical Power & Energy Systems.

[26]  Farhad Samadi Gazijahani,et al.  Robust Design of Microgrids With Reconfigurable Topology Under Severe Uncertainty , 2018, IEEE Transactions on Sustainable Energy.

[27]  Behnam Mohammadi-Ivatloo,et al.  Optimal economic dispatch of FC-CHP based heat and power micro-grids , 2017 .

[28]  Luhao Wang,et al.  Integrated scheduling of energy supply and demand in microgrids under uncertainty: A robust multi-objective optimization approach , 2017 .

[29]  Zhigang Lu,et al.  Optimal Economic and Emission Dispatch of a Microgrid with a Combined Heat and Power System , 2019, Energies.

[30]  Amjad Anvari-Moghaddam,et al.  Optimal simultaneous day-ahead scheduling and hourly reconfiguration of distribution systems considering responsive loads , 2019, International Journal of Electrical Power & Energy Systems.

[31]  Heresh Seyedi,et al.  Real-time price-based demand response model for combined heat and power systems , 2019, Energy.

[32]  Ahmed M. A. Haidar,et al.  Sustainable energy planning for cost minimization of autonomous hybrid microgrid using combined multi-objective optimization algorithm , 2020 .

[33]  Behnam Mohammadi-Ivatloo,et al.  Risk-based optimal scheduling of reconfigurable smart renewable energy based microgrids , 2018, International Journal of Electrical Power & Energy Systems.

[34]  Amjad Anvari-Moghaddam,et al.  Optimal Chance-Constrained Scheduling of Reconfigurable Microgrids Considering Islanding Operation Constraints , 2020, IEEE Systems Journal.

[35]  Hamidreza Zareipour,et al.  Considering Thermodynamic Characteristics of a CAES Facility in Self-Scheduling in Energy and Reserve Markets , 2018, IEEE Transactions on Smart Grid.

[36]  Chris Marnay,et al.  Microgrid Reliability Modeling and Battery Scheduling Using Stochastic Linear Programming , 2013 .

[37]  Mohammadreza Barzegaran,et al.  The impact of customers’ participation level and various incentive values on implementing emergency demand response program in microgrid operation , 2018 .

[38]  Hamidreza Zareipour,et al.  Application of information-gap decision theory to risk-constrained self-scheduling of GenCos , 2013, IEEE Transactions on Power Systems.

[39]  Mehdi Abapour,et al.  Day-ahead profit-based reconfigurable microgrid scheduling considering uncertain renewable generation and load demand in the presence of energy storage , 2020 .

[40]  Venkata Dinavahi,et al.  Distributionally Robust Chance-Constrained Energy Management for Islanded Microgrids , 2019, IEEE Transactions on Smart Grid.

[41]  Alireza Soroudi,et al.  Uncertainty management in decision-making in power system operation , 2020 .

[42]  Mohammed Hassan Ahmed,et al.  Optimization modeling for dynamic price based demand response in microgrids , 2019 .

[43]  Hussein Ibrahim,et al.  Investigation of Usage of Compressed Air Energy Storage for Power Generation System Improving - Application in a Microgrid Integrating Wind Energy☆ , 2015 .

[44]  Alireza Zakariazadeh,et al.  Optimum energy resource scheduling in a microgrid using a distributed algorithm framework , 2018 .

[45]  Jamshid Aghaei,et al.  Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems) , 2013 .

[46]  P. G. Panah,et al.  A techno-economic analysis: Urban reconfigurable microgrids participating in short-term regulating power markets , 2020 .