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Optimal operation of distribution networks with presence of distributed generations and battery energy storage systems considering uncertainties and risk analysis
This paper presents a probabilistic framework for the operation of distribution networks considering distributed generations (DGs) and battery energy storage systems. This framework considers the uncertainty of electricity prices and output power of DGs. To account for uncertainties, the probability distribution function is used, which generates scenarios by Monte Carlo Simulation at each hour. The aim of this paper is to calculate the distribution of daily profit and risk analysis. Value at Risk (VaR) is used as risk measure, and sensitivity of VaR with respect to changes in standard deviation is assessed. Numerical examples for two case studies are presented to illustrate the impact of uncertainty of DGs and prices on the profit and risk.
Optimal operation of distribution networks with presence of distributed generations and battery energy storage systems considering uncertainties and risk analysis
This paper presents a probabilistic framework for the operation of distribution networks considering distributed generations (DGs) and battery energy storage systems. This framework considers the uncertainty of electricity prices and output power of DGs. To account for uncertainties, the probability distribution function is used, which generates scenarios by Monte Carlo Simulation at each hour. The aim of this paper is to calculate the distribution of daily profit and risk analysis. Value at Risk (VaR) is used as risk measure, and sensitivity of VaR with respect to changes in standard deviation is assessed. Numerical examples for two case studies are presented to illustrate the impact of uncertainty of DGs and prices on the profit and risk.
Optimal operation of distribution networks with presence of distributed generations and battery energy storage systems considering uncertainties and risk analysis
Afshan, Razieh (author) / Salehi, Javad (author)
2017-01-01
12 pages
Article (Journal)
Electronic Resource
English
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