Fuzzy stochastic long-term model with consideration of uncertainties for deployment of distributed energy resources using interactive honey bee mating optimization

被引:73
作者
Ahmadian I. [1 ]
Abedinia O. [2 ]
Ghadimi N. [2 ]
机构
[1] West Regional Electric Company-Electrical Transmission Department of Ilam, Ilam
[2] Department of Electrical Engineering, Ardabil Branch, Islamic Azad University, Ardabil
关键词
Component; Distributed energy resources; Fuzzy optimization; Interactive honey bee mating optimization (IHBMO); Loss reduction; Stochastic programming; Voltage deviation reduction;
D O I
10.1007/s11708-014-0315-9
中图分类号
学科分类号
摘要
This paper presents a novel modified interactive honey bee mating optimization (IHBMO) base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting. A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduction in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power of DERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method. © Higher Education Press and Springer-Verlag Berlin Heidelberg 2014.
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页码:412 / 425
页数:13
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共 21 条
  • [1] Pai P.F., Yang S.L., Chang P.T., Forecasting output of integrated circuit industry by support vector regression models with marriage honey-bees optimization algorithms, Expert Systems with Applications, 36, 7, pp. 10746-10751, (2009)
  • [2] Ghasemi A., A fuzzified multi objective interactive honey bee mating optimization for environmental/economic power dispatch with valve point effect, International Journal of Electrical Power and Energy Systems, 49, pp. 308-321, (2013)
  • [3] Shayeghi H., Ghasemi A., Multiple PSS design using an improved honey bee mating optimization algorithm to enhance low frequency oscillations, International Review of Electrical Engineering (I.R.E. E.), 6, 7, pp. 3122-3133, (2011)
  • [4] Jain N., Singh S.N., Srivastava S.C., A generalized approach for DG planning and viability analysis under market scenario, IEEE Transactions on Industrial Electronics, 60, 11, pp. 5075-5085, (2013)
  • [5] Gil H.A., Joos G., Models for quantifying the economic benefits of distributed generation, IEEE Transactions on Power Systems, 23, 2, pp. 327-335, (2008)
  • [6] Chiradeja P., Ramakumar R., An approach to quantify the technical benefits of distributed generation, IEEE Transactions on Power Systems, 19, 4, pp. 764-773, (2004)
  • [7] Prenc R., Skrlec D., Komen V., Distributed generation allocation based on average daily load and power production curves, International Journal of Electrical Power & Energy Systems, 53, pp. 612-622, (2013)
  • [8] Wang C., Nehrir M.H., Analytical approaches for optimal placement of distributed generation sources in power systems, IEEE Transactions on Power Systems, 19, 4, pp. 2068-2076, (2004)
  • [9] Georgilakis P.S., Hatziargyriou N.D., Optimal distributed generation placement in power distribution networks: models, methods, and future research, IEEE Transactions on Power Systems, 28, 3, pp. 3420-3428, (2013)
  • [10] El-Khattan W., Bhattacharya K., Hegazy Y., Salama M.M.A., Optimal investment planning for distributed generation in a competitive electricity market, IEEE Transactions on Power Systems, 20, 4, pp. 1718-1727, (2005)