A Stochastic Program for Siting and Sizing Fast Charging Stations and Small Wind Turbines in Urban Areas
Autor: | Abdelrahman Amer, Maher A. Azzouz, Ahmed Azab, Ahmed S. A. Awad |
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Rok vydání: | 2021 |
Předmět: |
Wind power
Present value Renewable Energy Sustainability and the Environment business.industry 020209 energy 020208 electrical & electronic engineering 02 engineering and technology Environmental economics Investment (macroeconomics) 7. Clean energy Turbine Maintenance engineering Profit (economics) Electric distribution network 11. Sustainability 0202 electrical engineering electronic engineering information engineering Carbon footprint Environmental science business |
Zdroj: | IEEE Transactions on Sustainable Energy. 12:1217-1228 |
ISSN: | 1949-3037 1949-3029 |
DOI: | 10.1109/tste.2020.3039910 |
Popis: | Small wind turbines (SWTs) are promoted to be used in urban areas to mitigate the carbon footprint and expensive upgrades expected from high penetration levels of fast charging stations (FCSs). In this paper, a planning framework is proposed to amplify the total benefit for the owners of FCSs and SWTs as well as local distribution companies (LDCs). A stochastic program is developed to site and size SWTs along with FCSs in urban and suburban areas considering their specific wind characteristics, statutory regulations, turbine clustering studies, and geographic constraints. A worthiness metric is also proposed to rank FCS candidate locations based on their attractiveness to electric-vehicle (EV) drivers. An electric distribution network is overlaid onto a geographic map of downtown Chicago to assess the introduced planning framework. Results show that new efficient SWTs in urban areas can realistically justify their own investments over the long-term, and reduce the overall system losses and support FCS loads. In the case study presented, the investments yield a present value of $15M in profit, in 20 years, with an investment of $23M—only $6M of which is capital due in year one, while the rest consists of annual operation and maintenance costs. |
Databáze: | OpenAIRE |
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