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Optimal scheduled unit commitment considering suitable power of electric vehicle and photovoltaic uncertainty
In this paper, a method to review the role of renewable energy as an energy producer in scheduling a problem unit commitment is presented. Today, renewable energy sources, due to the lack of environmental pollution, and consequently a very low marginal cost, have been receiving considerable attention in power systems. The correct management of the unit commitment (UC) is a controversial and important issue in the power production unit, which requires suitable scheduled hours to obtain a minimum cost. This study was conducted to investigate the presence of electric vehicles and photovoltaic sources in UC and their impact to reduce production costs and improve load profiles. To achieve the optimum solution, a meta-heuristic Cuckoo search algorithm with high convergence speed is used to solve the UC problem. An IEEE 10-unit test system is employed to investigate the impacts of PEVs and PV on generation scheduling. Since the PV system is associated with uncertainty, in this study, the Uncertainty problem has been modeled using an iterative algorithm randomly with the allocation of density functions that fits the solar radiation. So, the used stochastic Monte Carlo optimization algorithm is capable of handling uncertain outputs of solar power. The simulation results show the effectiveness of the proposed method in reducing production costs and improving load profiles.
Optimal scheduled unit commitment considering suitable power of electric vehicle and photovoltaic uncertainty
In this paper, a method to review the role of renewable energy as an energy producer in scheduling a problem unit commitment is presented. Today, renewable energy sources, due to the lack of environmental pollution, and consequently a very low marginal cost, have been receiving considerable attention in power systems. The correct management of the unit commitment (UC) is a controversial and important issue in the power production unit, which requires suitable scheduled hours to obtain a minimum cost. This study was conducted to investigate the presence of electric vehicles and photovoltaic sources in UC and their impact to reduce production costs and improve load profiles. To achieve the optimum solution, a meta-heuristic Cuckoo search algorithm with high convergence speed is used to solve the UC problem. An IEEE 10-unit test system is employed to investigate the impacts of PEVs and PV on generation scheduling. Since the PV system is associated with uncertainty, in this study, the Uncertainty problem has been modeled using an iterative algorithm randomly with the allocation of density functions that fits the solar radiation. So, the used stochastic Monte Carlo optimization algorithm is capable of handling uncertain outputs of solar power. The simulation results show the effectiveness of the proposed method in reducing production costs and improving load profiles.
Optimal scheduled unit commitment considering suitable power of electric vehicle and photovoltaic uncertainty
Maghsudlu, Saniya (author) / Mohammadi, Sirus (author)
2018-07-01
19 pages
Article (Journal)
Electronic Resource
English
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