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An effective approach for optimal placement of non-dispatchable renewable distributed generation
In this paper, an effective approach is introduced for optimal placement of Non-Dispatchable Renewable Distributed Generation (NDRDG) including wind turbines and solar cells. Optimal placement is determined with the aim of reducing loss and improving the voltage profile. Since the output power of such distributed generation (DG) depends on the environmental and weather conditions, power generation through DG is variable throughout the year. On the other hand, load demand is not constant during the year and varies monthly and seasonally. Therefore, the best places for NDRDG may change with the variation in network conditions. This makes the optimal placement of NDRDG installations a controversial problem. In this paper, the optimal place for NDRDG is determined daily for each objective function considering the statistical information on wind speed, sun irradiation, and load demand. The final best places for NDRDG are determined using two introduced factors known as the cumulative frequency factor and the cumulative fitness factor based on the statistical analysis of yearly results. In this paper, a highly accurate yearly load profile is considered based on the variation trend of residential, commercial, and industrial load sectors. The proposed approach is applied on an IEEE 33-bus radial test system and the results are discussed.
An effective approach for optimal placement of non-dispatchable renewable distributed generation
In this paper, an effective approach is introduced for optimal placement of Non-Dispatchable Renewable Distributed Generation (NDRDG) including wind turbines and solar cells. Optimal placement is determined with the aim of reducing loss and improving the voltage profile. Since the output power of such distributed generation (DG) depends on the environmental and weather conditions, power generation through DG is variable throughout the year. On the other hand, load demand is not constant during the year and varies monthly and seasonally. Therefore, the best places for NDRDG may change with the variation in network conditions. This makes the optimal placement of NDRDG installations a controversial problem. In this paper, the optimal place for NDRDG is determined daily for each objective function considering the statistical information on wind speed, sun irradiation, and load demand. The final best places for NDRDG are determined using two introduced factors known as the cumulative frequency factor and the cumulative fitness factor based on the statistical analysis of yearly results. In this paper, a highly accurate yearly load profile is considered based on the variation trend of residential, commercial, and industrial load sectors. The proposed approach is applied on an IEEE 33-bus radial test system and the results are discussed.
An effective approach for optimal placement of non-dispatchable renewable distributed generation
Rahiminejad, A. (author) / Faramarzi, D. (author) / Hosseinian, S. H. (author) / Vahidi, B. (author)
2017-01-01
16 pages
Article (Journal)
Electronic Resource
English
| DOAJ | 2020
| British Library Online Contents | 2018
| British Library Online Contents | 2018