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A multi-follower bilevel stochastic programming approach for energy management of combined heat and power micro-grids

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  • Alipour, Manijeh
  • Zare, Kazem
  • Seyedi, Heresh

Abstract

This paper presents a multi-follower bilevel programming approach to solve the 24-h decision-making problem faced by a combined heat and power (CHP) based micro-grid (MG). The framework contains the interests of two different agents: the MG operator/owner (MGO), who procures the maximization of total profit incurred in attending the forecasted demand of consumers via demand response program (DRP) as well as day-ahead (DA) and real-time (RT) markets participation, and the various CHP owners (CHPOs) who procure the maximization of the profits obtained from the thermal and electrical energy sales. The interaction between the entities is determined in a bilateral contract. Further, to deal with various uncertainties, each level is formulated as a stochastic two-stage problem, where the volatility nature of consumers' loads, RT market price and wind speed uncertainties are modeled using autoregressive moving average (ARMA) technique. In this paper, in order to consider realistic model of the problem, on the contrary to the most CHP-based MG scheduling literature, the network operation constraints such as voltage magnitude of buses and line flow limits are taken into account.

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  • Alipour, Manijeh & Zare, Kazem & Seyedi, Heresh, 2018. "A multi-follower bilevel stochastic programming approach for energy management of combined heat and power micro-grids," Energy, Elsevier, vol. 149(C), pages 135-146.
    • Handle: RePEc:eee:energy:v:149:y:2018:i:c:p:135-146
    DOI: 10.1016/j.energy.2018.02.013
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    1. RUIZ, Carlos & CONEJO, Antonio J. & SMEERS, Yves, 2012. "Equilibria in an oligopolistic electricity pool with stepwise offer curves," LIDAM Reprints CORE 2395, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Alipour, Manijeh & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2014. "Short-term scheduling of combined heat and power generation units in the presence of demand response programs," Energy, Elsevier, vol. 71(C), pages 289-301.
    3. Mahani, Khashayar & Farzan, Farbod & Jafari, Mohsen A., 2017. "Network-aware approach for energy storage planning and control in the network with high penetration of renewables," Applied Energy, Elsevier, vol. 195(C), pages 974-990.
    4. Garci'a-Bertrand, Raquel & Conejo, Antonio J. & Gabriel, Steven, 2006. "Electricity market near-equilibrium under locational marginal pricing and minimum profit conditions," European Journal of Operational Research, Elsevier, vol. 174(1), pages 457-479, October.
    5. Nazari, M.E. & Ardehali, M.M., 2017. "Profit-based unit commitment of integrated CHP-thermal-heat only units in energy and spinning reserve markets with considerations for environmental CO2 emission cost and valve-point effects," Energy, Elsevier, vol. 133(C), pages 621-635.
    6. Jie Lu & Chenggen Shi & Guangquan Zhang & Da Ruan, 2007. "An Extended Branch And Bound Algorithm For Bilevel Multi-Follower Decision Making In A Referential-Uncooperative Situation," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 6(02), pages 371-388.
    7. Warren, Peter, 2014. "A review of demand-side management policy in the UK," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 941-951.
    8. Motevasel, Mehdi & Seifi, Ali Reza & Niknam, Taher, 2013. "Multi-objective energy management of CHP (combined heat and power)-based micro-grid," Energy, Elsevier, vol. 51(C), pages 123-136.
    9. Lahdelma, Risto & Hakonen, Henri, 2003. "An efficient linear programming algorithm for combined heat and power production," European Journal of Operational Research, Elsevier, vol. 148(1), pages 141-151, July.
    10. Yousefi, Shaghayegh & Moghaddam, Mohsen Parsa & Majd, Vahid Johari, 2011. "Optimal real time pricing in an agent-based retail market using a comprehensive demand response model," Energy, Elsevier, vol. 36(9), pages 5716-5727.
    11. Wang, Fei & Xu, Hanchen & Xu, Ti & Li, Kangping & Shafie-khah, Miadreza & Catalão, João. P.S., 2017. "The values of market-based demand response on improving power system reliability under extreme circumstances," Applied Energy, Elsevier, vol. 193(C), pages 220-231.
    12. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems)," Energy, Elsevier, vol. 55(C), pages 1044-1054.
    Full references (including those not matched with items on IDEAS)

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    4. Carlos Henggeler Antunes & Maria João Alves & Billur Ecer, 2020. "Bilevel optimization to deal with demand response in power grids: models, methods and challenges," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 814-842, October.
    5. Roy, Kallol & Mandal, Kamal Krishna & Mandal, Atis Chandra, 2019. "Ant-Lion Optimizer algorithm and recurrent neural network for energy management of micro grid connected system," Energy, Elsevier, vol. 167(C), pages 402-416.
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    8. Morteza Nazari-Heris & Behnam Mohammadi-Ivatloo & Somayeh Asadi, 2020. "Optimal Operation of Multi-Carrier Energy Networks Considering Uncertain Parameters and Thermal Energy Storage," Sustainability, MDPI, vol. 12(12), pages 1-20, June.
    9. Xiang, Yue & Cai, Hanhu & Gu, Chenghong & Shen, Xiaodong, 2020. "Cost-benefit analysis of integrated energy system planning considering demand response," Energy, Elsevier, vol. 192(C).
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