Reports on Mathematics from North China Electric Power University Provide New Insights (Optimal Offering and Operating Strategies for Wind-storage System Participating In Spot Electricity Markets With Progressive Stochastic-robust Hybrid …)

2019 AUG 14 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A new study on Mathematics is now available. According to news reporting originating from Baoding, People’s Republic of China, by NewsRx correspondents, research stated, “With the increase of wind power installed capacity and the development of energy storage technologies, it is gradually accepted that integrating wind farms with energy storage devices to participate in spot electricity market (EM) is a promising way for improving wind power uncertainty accommodation and bringing considerable profit. Hence, research on reasonable offering and operating strategies for integrated wind farm-energy storage system (WF-ESS) under spot EM circumstances has important theoretical and practical significance.”

Financial supporters for this research include Major State Research and Development Program of China, Fundamental Research Funds for the Central Universities.

Our news editors obtained a quote from the research from North China Electric Power University, “In this paper, a newly progressive stochastic-robust hybrid optimization model series is proposed for yielding such strategies. In the day-ahead stage, day-ahead and balancing prices uncertainties are formulated by applying joint stochastic scenarios, and real-time available wind power uncertainties are modeled by using the seasonal auto-regression (AR) based dynamic uncertainty set. Then, the first model of this model series is established and utilized for cooptimizing both the day-ahead offering and nominal real-time operating strategies. In the balancing stages, wind power uncertainty set and balancing prices stochastic scenarios are dynamically updated with the newly realized data. Then, each model from the remaining of this model series is established and utilized period by period for obtaining the optimal balancing/real-time offering/operating strategies adjusted from the nominal ones. Robust optimization (RO) in this progressive framework makes the operation of WF-ESS dynamically accommodate wind power uncertainties while maintaining relatively low computational complexity. Stochastic optimization (SO) in this progressive framework makes the WF-ESS avoid pursuing profit maximization strictly under the worst-case scenarios of prices uncertainties. Moreover, by adding a risk-aversion term in form of conditional value at risk (CVaR) into the objective functions of this model series, the optimization models additionally provide flexibility in reaching a trade-off between profit maximization and risk management.”

According to the news editors, the research concluded: “Simulation and profit comparisons with other existing methods validate the scientificity, feasibility, and effectiveness of applying our proposed model series.”

For more information on this research see: Optimal Offering and Operating Strategies for Wind-storage System Participating In Spot Electricity Markets With Progressive Stochastic-robust Hybrid Optimization Model Series. Mathematical Problems in Engineering, 2019;2019():. Mathematical Problems in Engineering can be contacted at: Hindawi Ltd, Adam House, 3RD Flr, 1 Fitzroy Sq, London, W1T 5HF, England. (Hindawi Publishing - www.hindawi.com; Mathematical Problems in Engineering - http://www.hindawi.com/journals/mpe/)

The news editors report that additional information may be obtained by contacting Y.W. Wang, North China Electric Power University, Dept. of Economics Management, Baoding 071003, People’s Republic of China. Additional authors for this research include H.R. Zhao and P. Li.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1155/2019/2142050. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

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