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Short-term optimal energy management in stand-alone microgrid with battery energy storage

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The optimal energy management (OEM) in a stand-alone microgrid (SMG) is a challenging job because of uncertain and intermittent behavior of clean energy sources (CESs) such as a photovoltaic (PV), wind turbine (WT). This paper presents the effective role of battery energy storage (BES) in optimal scheduling of generation sources to fulfill the load demand in an SMG under the intermittency of theWT and PV power. The OEM is performed by minimizing the operational cost of the SMG for the chosen moderate weather profile using an artificial bee colony algorithm (ABC) in four different cases, i.e. without the BES and with the BES having a various level of initial capacity. The results show the efficient role of the BES in keeping the reliability of the SMG with the reduction in carbon-emissions and uncertainty of the CES power. Also, prove that the ABC provides better cost values compared to particle swarm optimization (PSO) and a genetic algorithm (GA). Further, the robustness of system reliability using the BES is tested for the mean data of the considered weather profile.
Rocznik
Strony
499--–513
Opis fizyczny
Bibliogr. 24 poz., rys., tab., wz.
Twórcy
  • Motilal Nehru National Institute of Technology Allahabad, India
autor
  • Motilal Nehru National Institute of Technology Allahabad, India
autor
  • Motilal Nehru National Institute of Technology Allahabad, India
Bibliografia
  • [1] Hatziargyriou N., Asano H., Iravani R., Marnay C., Microgrids: An overview of ongoing research, development, and demonstration projects, IEEE Power Energy Mag., vol. 5, no. 4, pp. 78–94 (2007).
  • [2] Driesen J., Katiraei F., Design for distributed energy resources, IEEE Power Energy Mag., vol. 6, pp. 30–40 (2008).
  • [3] Chen C., Duan S., Cai T., Liu B., Hu G., Smart energy management system for optimal microgrid economic operation, IET Renewable Power Generation, vol. 5, no. 3, pp. 258–267 (2011).
  • [4] Paliwal N. K., Singh N. K., Singh A. K., Energy scheduling of wind-battery-hydro based hybrid micro-grid system using heuristic techniques, IEEE 2016 Annual India Conf. (INDICON), Bangalore, India, pp. 1–6 (2016).
  • [5] Paliwal N. K., Singh N. K., Singh A. K., Optimal power flow in grid connected microgrid using artificial bee colony algorithm, IEEE 2016 Region 10 Conf. (TENCON), Singapore, pp. 671–675 (2016).
  • [6] SuW.,Wang J., Roh J., Stochastic energy scheduling in microgrids with intermittent renewable energy resources, IEEE Transactions on Smart Grid., vol. 5, no. 4, pp. 1876–1883 (2014).
  • [7] Bogaraj T., Kanakaraj J., Kumar K. M., Optimal sizing and cost analysis of hybrid power system for a stand-alone application in Coimbatore region: a case study, Archives of Electrical Engineering, vol. 64, no. 1, pp. 139–155 (2015).
  • [8] Liu H.,Wu Y., Qian C., Liu X., The application of dynamic programming in the stand-alone microgrid optimal operation, IEEE 2012 APPEEC, Shanghai, pp. 1–5 (2012).
  • [9] Komarnicki P., Energy storage systems: power grid and energy market use cases, Archives of Electrical Engineering, vol. 65, no. 3, pp. 495–511 (2016).
  • [10] Sachs J., Sawodny O., A two-stage model predictive control strategy for economic diesel-PV-battery island microgrid operation in rural areas, IEEE Transactions on Sustainable Energy., vol. 7, no. 3, pp. 903–913 (2016).
  • [11] Wu X., Wang X., Qu C., A hierarchical framework for generation scheduling of microgrids, IEEE Transactions on Power Delivery, vol. 29, no. 6, pp. 2448–2457 (2014).
  • [12] Jiang Q., Xue M., Geng G., Energy management of microgrid in grid-connected and stand-alone modes, IEEE Transactions on Power Systems, vol. 28, no. 3, pp. 3380–3389 (2013).
  • [13] Izadbakhsh M., Gandomkar M.,Rezvani A., Ahmadi A., Short-termresource scheduling of a renewable energy based microgrid, Renewable Energy, vol. 75, pp. 598–606 (2015).
  • [14] Moghaddam A. A., Seifi A., Niknam T., Pahlavani M. R. A.., Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source, Energy, vol. 36, no. 11, pp. 6490–6507 (2011).
  • [15] Li P., Xu D., Zhou Z., Lee W. J., Zhao B., Stochastic optimal operation of microgrid based on chaotic binary particle swarm optimization, IEEE Transactions on Smart Grid, vol. 7, no. 1, pp. 66–73 (2016).
  • [16] Zhao B., Zhang X., Chen J., Wang C., Guo L., Operation optimization of standalone microgrids considering lifetime characteristics of battery energy storage system, IEEE Transactions on Sustainable Energy, vol. 4, no. 4, pp. 934–943 (2013).
  • [17] Karaboga D., Basturk B., A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm, Journal of Global Optimization, vol. 39, pp. 171–459 (2007).
  • [18] http://www.nrel.gov/midc/nwtc_m2/, accessed June 2017.
  • [19] Kazem H.A., Khatib T., A novel numerical algorithm for optimal sizing of a photovoltaic/wind/diesel generator/battery microgrid using loss of load probability index, International Journal of Photoenergy, p. 8 (2013).
  • [20] Lemaire-Potteau E., Mattera F., Delaille A., Malbranche P., Assessment of storage ageing in different types of PV systems technical and economical aspects, 2008 Proc. 24th EU Photovoltaic Solar Energy Conf., Valencia, Spain (2008).
  • [21] Kennedy J., Eberhart R. C., Particle swarm optimization, Proc. of the 1995 IEEE International Conf. on Neural Networks, Piscataway, NJ (1995).
  • [22] Holland J. H., Adaptation in Natural and Artificial Systems, Ann Arbor, MI: University of Michigan Press (1975).
  • [23] Climate Investment Funds, 2015 Meeting of the SERP sub-committee,Washington D.C., vol. 4, no. 14, pp. 1–113 (2015).
  • [24] Ortega-Vazquez M., Optimizing the spinning reserve requirements, Univ. of Manchester, Sch. of Elect. and Electron. Eng., UK., pp. 1–219 (2006)
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-5d38b5c7-b2e5-46a5-abe9-5388b1dbd294
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