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An inexact two-stage stochastic robust programming for residential micro-grid management-based on random demand

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  • Ji, L.
  • Niu, D.X.
  • Huang, G.H.

Abstract

In this paper a stochastic robust optimization problem of residential micro-grid energy management is presented. Combined cooling, heating and electricity technology (CCHP) is introduced to satisfy various energy demands. Two-stage programming is utilized to find the optimal installed capacity investment and operation control of CCHP (combined cooling heating and power). Moreover, interval programming and robust stochastic optimization methods are exploited to gain interval robust solutions under different robustness levels which are feasible for uncertain data. The obtained results can help micro-grid managers minimizing the investment and operation cost with lower system failure risk when facing fluctuant energy market and uncertain technology parameters. The different robustness levels reflect the risk preference of micro-grid manager. The proposed approach is applied to residential area energy management in North China. Detailed computational results under different robustness level are presented and analyzed for providing investment decision and operation strategies.

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  • Ji, L. & Niu, D.X. & Huang, G.H., 2014. "An inexact two-stage stochastic robust programming for residential micro-grid management-based on random demand," Energy, Elsevier, vol. 67(C), pages 186-199.
    • Handle: RePEc:eee:energy:v:67:y:2014:i:c:p:186-199
    DOI: 10.1016/j.energy.2014.01.099
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    as
    1. Dong, C. & Huang, G.H. & Cai, Y.P. & Xu, Y., 2011. "An interval-parameter minimax regret programming approach for power management systems planning under uncertainty," Applied Energy, Elsevier, vol. 88(8), pages 2835-2845, August.
    2. Maqsood, Imran & Huang, Guo H. & Scott Yeomans, Julian, 2005. "An interval-parameter fuzzy two-stage stochastic program for water resources management under uncertainty," European Journal of Operational Research, Elsevier, vol. 167(1), pages 208-225, November.
    3. Zhou, Zhe & Zhang, Jianyun & Liu, Pei & Li, Zheng & Georgiadis, Michael C. & Pistikopoulos, Efstratios N., 2013. "A two-stage stochastic programming model for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 103(C), pages 135-144.
    4. Al-Mayyahi, Mohmmad A. & Hoadley, Andrew F.A. & Rangaiah, G.P., 2013. "A novel graphical approach to target CO2 emissions for energy resource planning and utility system optimization," Applied Energy, Elsevier, vol. 104(C), pages 783-790.
    5. Bale, Catherine S.E. & Foxon, Timothy J. & Hannon, Matthew J. & Gale, William F., 2012. "Strategic energy planning within local authorities in the UK: A study of the city of Leeds," Energy Policy, Elsevier, vol. 48(C), pages 242-251.
    6. Niknam, Taher & Golestaneh, Faranak & Shafiei, Mehdi, 2013. "Probabilistic energy management of a renewable microgrid with hydrogen storage using self-adaptive charge search algorithm," Energy, Elsevier, vol. 49(C), pages 252-267.
    7. Tan, Q. & Huang, G.H. & Cai, Y.P., 2011. "Radial interval chance-constrained programming for agricultural non-point source water pollution control under uncertainty," Agricultural Water Management, Elsevier, vol. 98(10), pages 1595-1606, August.
    8. Arcuri, P. & Florio, G. & Fragiacomo, P., 2007. "A mixed integer programming model for optimal design of trigeneration in a hospital complex," Energy, Elsevier, vol. 32(8), pages 1430-1447.
    9. Cai, Y.P. & Huang, G.H. & Tan, Q. & Chen, B., 2011. "Identification of optimal strategies for improving eco-resilience to floods in ecologically vulnerable regions of a wetland," Ecological Modelling, Elsevier, vol. 222(2), pages 360-369.
    10. Xie, Y.L. & Li, Y.P. & Huang, G.H. & Li, Y.F., 2010. "An interval fixed-mix stochastic programming method for greenhouse gas mitigation in energy systems under uncertainty," Energy, Elsevier, vol. 35(12), pages 4627-4644.
    11. Yu, Chian-Son & Li, Han-Lin, 2000. "A robust optimization model for stochastic logistic problems," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 385-397, March.
    12. Chen, Yen-Haw & Lu, Su-Ying & Chang, Yung-Ruei & Lee, Ta-Tung & Hu, Ming-Che, 2013. "Economic analysis and optimal energy management models for microgrid systems: A case study in Taiwan," Applied Energy, Elsevier, vol. 103(C), pages 145-154.
    13. 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.
    14. Lund, Henrik & Clark, Woodrow W., 2002. "Management of fluctuations in wind power and CHP comparing two possible Danish strategies," Energy, Elsevier, vol. 27(5), pages 471-483.
    15. Moradi, Mohammad H. & Hajinazari, Mehdi & Jamasb, Shahriar & Paripour, Mahmoud, 2013. "An energy management system (EMS) strategy for combined heat and power (CHP) systems based on a hybrid optimization method employing fuzzy programming," Energy, Elsevier, vol. 49(C), pages 86-101.
    16. Mehleri, Eugenia D. & Sarimveis, Haralambos & Markatos, Nikolaos C. & Papageorgiou, Lazaros G., 2012. "A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level," Energy, Elsevier, vol. 44(1), pages 96-104.
    17. Vazhayil, Joy P. & Balasubramanian, R., 2013. "Optimization of India's power sector strategies using weight-restricted stochastic data envelopment analysis," Energy Policy, Elsevier, vol. 56(C), pages 456-465.
    18. Yeo, In-Ae & Yoon, Seong-Hwan & Yee, Jurng-Jae, 2013. "Development of an Environment and energy Geographical Information System (E-GIS) construction model to support environmentally friendly urban planning," Applied Energy, Elsevier, vol. 104(C), pages 723-739.
    19. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
    20. Klaassen, R.E. & Patel, M.K., 2013. "District heating in the Netherlands today: A techno-economic assessment for NGCC-CHP (Natural Gas Combined Cycle combined heat and power)," Energy, Elsevier, vol. 54(C), pages 63-73.
    21. Dong, C. & Huang, G.H. & Cai, Y.P. & Liu, Y., 2012. "An inexact optimization modeling approach for supporting energy systems planning and air pollution mitigation in Beijing city," Energy, Elsevier, vol. 37(1), pages 673-688.
    22. Wu, Jing-yi & Wang, Jia-long & Li, Sheng, 2012. "Multi-objective optimal operation strategy study of micro-CCHP system," Energy, Elsevier, vol. 48(1), pages 472-483.
    23. Birge, John R. & Louveaux, Francois V., 1988. "A multicut algorithm for two-stage stochastic linear programs," European Journal of Operational Research, Elsevier, vol. 34(3), pages 384-392, March.
    24. Cai, Y.P. & Huang, G.H. & Yang, Z.F. & Tan, Q., 2009. "Identification of optimal strategies for energy management systems planning under multiple uncertainties," Applied Energy, Elsevier, vol. 86(4), pages 480-495, April.
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