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access icon free Research on heat and electricity coordinated dispatch model for better integration of wind power based on electric boiler with thermal storage

The thermal-electric coupling characteristics of combined heat and power (CHP) units make it critical problem to improve wind power accommodation ability in the heating season. This study establishes a CHP dispatch model for better integration of wind power based on electric boiler with thermal storage (EBTS). A start–stop strategy of EBTS is formulated that takes only the abandoned wind as the heat source. The electric boiler runs at maximum power during the wind curtailment, and the heat output of EBTS is changed by controlling the endothermic and exothermic rates of the thermal storage. Considering the scheduling difficulty of the CHP system with EBTS, the multi-agent model of heat and electricity is built. Through information exchange and load distribution between the agents, electric load is balanced by all units while thermal load by CHP units and EBTS. Finally, the Newton–Raphson iterative method is applied to solve the proposed model. The results of numerical examples validate effectiveness and economic improvement of the proposed method.

References

    1. 1)
      • 27. Sampaio, R.F., Melo, L.S., Leão, R.P.S., et al: ‘Automatic restoration system for power distribution networks based on multi-agent systems’, IET Gener. Transm. Distrib., 2017, 11, (2), pp. 475484.
    2. 2)
      • 28. Wang, L., Singh, C.: ‘Stochastic combined heat and power dispatch based on multi-objective particle swarm optimization’, Int. J. Electr. Power Energy Syst., 2008, 30, (3), pp. 226234.
    3. 3)
      • 24. Wong, S., Pinard, J.P.: ‘Opportunities for smart electric thermal storage on electric grids with renewable energy’, IEEE Trans. Smart Grid, 2017, PP, (99), pp. 19.
    4. 4)
      • 16. Kiviluoma, J., Heinen, S., Qazi, H., et al: ‘Harnessing flexibility from hot and cold: heat storage and hybrid systems can play a major role’, IEEE Power Energy Mag., 2017, 15, (1), pp. 2533.
    5. 5)
      • 12. Dai, Y., Chen, L., Min, Y., et al: ‘Dispatch model of combined heat and power plant considering heat transfer process’, IEEE Trans. Sustain. Energy, 2017, 8, (3), pp. 12251236.
    6. 6)
      • 17. Makhloufi, S., Koussa, S.D., Pillai, G.G.: ‘Cuckoo search algorithm for integration wind power generation to meet load demand growth’. IEEE Int. Conf. on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe, Milan, Italy, June 2017, pp. 16.
    7. 7)
      • 23. Li, Z., Wu, W., Shahidehpour, M., et al: ‘Combined heat and power dispatch considering pipeline energy storage of district heating network’, IEEE Trans. Sustain. Energy, 2016, 7, (1), pp. 1222.
    8. 8)
      • 20. Lan, Y., Guan, X., Wu, J.: ‘Rollout strategies for real-time multi-energy scheduling in microgrid with storage system’, IET Gener. Transm. Distrib., 2016, 10, (3), pp. 688696.
    9. 9)
      • 8. MuñOz, C., Sauma, E., Contreras, J., et al: ‘Impact of high wind power penetration on transmission network expansion planning’, IET Gener. Trans. Distrib., 2012, 6, (12), pp. 12811291.
    10. 10)
      • 1. Shi, L., Sun, S., Yao, L., et al: ‘Effects of wind generation intermittency and volatility on power system transient stability’, IET Renew. Power Gener., 2013, 8, (5), pp. 509521.
    11. 11)
      • 5. Knezovic, K., Soroudi, A., Keane, A., et al: ‘Robust multi-objective PQ scheduling for electric vehicles in flexible unbalanced distribution grids’, IET Gener. Transm. Distrib., 2017, 11, (16), pp. 40314040.
    12. 12)
      • 25. Zhang, X., Zhang, B.: ‘Equal incremental rate economic dispatching and optimal power flow for the union system of microgrid and external grid’. PES General Meeting | Conf. & Exposition, National Harbor, MD, USA, July 2014, pp. 11.
    13. 13)
      • 2. Xu, C., Zhao, F., He, S., et al: ‘An economic dispatch model considering the volatility and uncertainty of wind power’. Power and Energy Engineering Conf., Kowloon, China, December 2014, pp. 15.
    14. 14)
      • 19. Benam, M.R., Madani, S.S., Alavi, S.M., et al: ‘Optimal configuration of the CHP system using stochastic programming’, IEEE Trans. Power Deliv., 2015, 30, (3), pp. 10481056.
    15. 15)
      • 3. Zhang, Y., Zhou, J., Zheng, Y., et al: ‘Control optimisation for pumped storage unit in micro-grid with wind power penetration using improved grey wolf optimiser’, IET Gener. Transm. Distrib., 2017, 11, (13), pp. 32463256.
    16. 16)
      • 18. Biglarbegian, M., Vatani, B., Mazhari, I., et al: ‘Thermal storage capacity to enhance network flexibility in dual demand side management’. North American Power Symp., Charlotte, NC, USA, October 2015, pp. 15.
    17. 17)
      • 21. Cheng, L., Qi, G., Jin, L., et al: ‘Research on control strategy of electric heat storage boiler based on multi-agent’. Int. Conf. on Power and Renewable Energy, Shanghai, China, October 2016, pp. 508512.
    18. 18)
      • 26. Pazouki, S., Mohsenzadeh, A., Ardalan, S., et al: ‘Optimal place, size, and operation of combined heat and power in multi carrier energy networks considering network reliability, power loss, and voltage profile’, IET Gener. Transm. Distrib., 2016, 10, (7), pp. 16151621.
    19. 19)
      • 29. Basu, M.: ‘Bee colony optimization for combined heat and power economic dispatch’, Expert Syst. Appl., 2011, 38, (11), pp. 1352713531.
    20. 20)
      • 11. Alipour, M., Mohammadi-Ivatloo, B., Zare, K.: ‘Stochastic scheduling of renewable and CHP-based microgrids’, IEEE Trans. Ind. Inf., 2015, 11, (5), pp. 10491058.
    21. 21)
      • 13. Chen, X., Kang, C., O'Malley, M., et al: ‘Increasing the flexibility of combined heat and power for wind power integration in China: modeling and implications’, IEEE Trans. Power Syst., 2015, 30, (4), pp. 18481857.
    22. 22)
      • 14. Salimi, M., Ghasemi, H., Adelpour, M., et al: ‘Optimal planning of energy hubs in interconnected energy systems: a case study for natural gas and electricity’, IET Gener. Transm. Distrib., 2015, 9, (8), pp. 695707.
    23. 23)
      • 22. Li, Z., Wu, W., Wang, J., et al: ‘Transmission-constrained unit commitment considering combined electricity and district heating networks’, IEEE Trans. Sustain. Energy, 2016, 7, (2), pp. 480492.
    24. 24)
      • 6. Abdelsamad, S.F., Morsi, W.G., Sidhu, T.S.: ‘Impact of wind-based distributed generation on electric energy in distribution systems embedded with electric vehicles’, IEEE Trans. Sustain. Energy, 2017, 6, (1), pp. 7987.
    25. 25)
      • 4. Lin, S., Liu, M., Li, Q., et al: ‘Normalised normal constraint algorithm applied to multi-objective security-constrained optimal generation dispatch of large-scale power systems with wind farms and pumped-storage hydroelectric stations’, IET Gener. Transm. Distrib., 2017, 11, (6), pp. 15391548.
    26. 26)
      • 9. Ma, L., Liu, N., Zhang, J., et al: ‘Energy management for joint operation of CHP and PV prosumers inside a grid-connected microgrid: a game theoretic approach’, IEEE Trans. Ind. Inf., 2016, 12, (5), pp. 19301942.
    27. 27)
      • 7. Guan, L., Fan, X., Liu, Y., et al: ‘Dual-mode control of AC/VSC-HVDC hybrid transmission systems with wind power integrated’, IEEE Trans. Power Deliv., 2015, 30, (4), pp. 16861693.
    28. 28)
      • 15. Sadeghian, H., Wang, Z.: ‘Combined heat and power unit commitment with smart parking lots of plug-in electric vehicles’. North American Power Symp., Morgantown, WV, USA, September 2017, pp. 16.
    29. 29)
      • 10. Hellmers, A., Zugno, M., Skajaa, A., et al: ‘Operational strategies for a portfolio of wind farms and CHP plants in a two-price balancing market’, IEEE Trans. Power Syst., 2016, 31, (3), pp. 21822191.
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