Fuzzy stochastic long-term model with consideration of uncertainties for deployment of distributed energy resources using interactive honey bee mating optimization
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-...
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| Vydané v: | Frontiers in Energy Ročník 8; číslo 4; s. 412 - 425 |
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| Hlavní autori: | , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Heidelberg
Higher Education Press
01.12.2014
Springer Nature B.V |
| Predmet: | |
| ISSN: | 2095-1701, 2095-1698 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | 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. |
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| Bibliografia: | This paper presents a novel modified inter- active 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 reduc- tion 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 orDERs 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. component, distributed energy resources,fuzzy optimization, loss reduction, interactive honey beemating optimization （IHBMO）, voltage deviation reduction,stochastic programming 11-6017/TK component voltage deviation reduction interactive honey bee mating optimization (IHBMO) stochastic programming distributed energy resources fuzzy optimization Document accepted on :2013-12-22 Document received on :2013-09-17 loss reduction SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 2095-1701 2095-1698 |
| DOI: | 10.1007/s11708-014-0315-9 |