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Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system

Author

Listed:
  • Jiang, Yibo
  • Xu, Jian
  • Sun, Yuanzhang
  • Wei, Congying
  • Wang, Jing
  • Ke, Deping
  • Li, Xiong
  • Yang, Jun
  • Peng, Xiaotao
  • Tang, Bowen

Abstract

As the installed capacity of wind power is growing, the stochastic variability of wind power leads to the mismatch of demand and generated power. Employing the regulating capability of demand to improve the utilization of wind power has become a new research direction. Meanwhile, the micro combined heat and power (micro-CHP) allows residential consumers to choose whether generating electricity by themselves or purchasing from the utility company, which forms a residential hybrid energy system. However, the impact of the demand response with hybrid energy system contained micro-CHP on the large-scale wind power utilization has not been analyzed quantitatively. This paper proposes an operation optimization model of the residential hybrid energy system based on price response, integrating micro-CHP and smart appliances intelligently. Moreover, a novel load aggregation method is adopted to centralize scattered response capability of residential load. At the power grid level, a day-ahead stochastic economic dispatch model considering demand response and wind power is constructed. Furthermore, simulation is conducted respectively on the modified 6-bus system and IEEE 118-bus system. The results show that with the method proposed, the wind power curtailment of the system decreases by 78% in 6-bus system. In the meantime, the energy costs of residential consumers and the operating costs of the power system reduced by 10.7% and 11.7% in 118-bus system, respectively.

Suggested Citation

  • Jiang, Yibo & Xu, Jian & Sun, Yuanzhang & Wei, Congying & Wang, Jing & Ke, Deping & Li, Xiong & Yang, Jun & Peng, Xiaotao & Tang, Bowen, 2017. "Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system," Applied Energy, Elsevier, vol. 190(C), pages 1126-1137.
  • Handle: RePEc:eee:appene:v:190:y:2017:i:c:p:1126-1137
    DOI: 10.1016/j.apenergy.2017.01.030
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    References listed on IDEAS

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    1. Siano, Pierluigi, 2014. "Demand response and smart grids—A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 461-478.
    2. Wang, Xu & Jiang, Chuanwen & Li, Bosong, 2016. "Active robust optimization for wind integrated power system economic dispatch considering hourly demand response," Renewable Energy, Elsevier, vol. 97(C), pages 798-808.
    3. Azizipanah-Abarghooee, Rasoul & Golestaneh, Faranak & Gooi, Hoay Beng & Lin, Jeremy & Bavafa, Farhad & Terzija, Vladimir, 2016. "Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power," Applied Energy, Elsevier, vol. 182(C), pages 634-651.
    4. Yanine, Franco Fernando & Caballero, Federico I. & Sauma, Enzo E. & Córdova, Felisa M., 2014. "Homeostatic control, smart metering and efficient energy supply and consumption criteria: A means to building more sustainable hybrid micro-generation systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 235-258.
    5. Najafi, Behzad & Haghighat Mamaghani, Alireza & Rinaldi, Fabio & Casalegno, Andrea, 2015. "Long-term performance analysis of an HT-PEM fuel cell based micro-CHP system: Operational strategies," Applied Energy, Elsevier, vol. 147(C), pages 582-592.
    6. Mongibello, Luigi & Bianco, Nicola & Caliano, Martina & Graditi, Giorgio, 2016. "Comparison between two different operation strategies for a heat-driven residential natural gas-fired CHP system: Heat dumping vs. load partialization," Applied Energy, Elsevier, vol. 184(C), pages 55-67.
    7. Cui, Hantao & Li, Fangxing & Hu, Qinran & Bai, Linquan & Fang, Xin, 2016. "Day-ahead coordinated operation of utility-scale electricity and natural gas networks considering demand response based virtual power plants," Applied Energy, Elsevier, vol. 176(C), pages 183-195.
    8. Reihani, Ehsan & Motalleb, Mahdi & Thornton, Matsu & Ghorbani, Reza, 2016. "A novel approach using flexible scheduling and aggregation to optimize demand response in the developing interactive grid market architecture," Applied Energy, Elsevier, vol. 183(C), pages 445-455.
    9. Fubara, Tekena Craig & Cecelja, Franjo & Yang, Aidong, 2014. "Modelling and selection of micro-CHP systems for domestic energy supply: The dimension of network-wide primary energy consumption," Applied Energy, Elsevier, vol. 114(C), pages 327-334.
    10. Caballero, F. & Sauma, E. & Yanine, F., 2013. "Business optimal design of a grid-connected hybrid PV (photovoltaic)-wind energy system without energy storage for an Easter Island's block," Energy, Elsevier, vol. 61(C), pages 248-261.
    11. Yanine, Franco Fernando & Caballero, Federico I. & Sauma, Enzo E. & Córdova, Felisa M., 2014. "Building sustainable energy systems: Homeostatic control of grid-connected microgrids, as a means to reconcile power supply and energy demand response management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 1168-1191.
    12. Dehnavi, Ehsan & Abdi, Hamdi, 2016. "Optimal pricing in time of use demand response by integrating with dynamic economic dispatch problem," Energy, Elsevier, vol. 109(C), pages 1086-1094.
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