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Wang X.,Shanghai JiaoTong University | Jiang C.,Shanghai JiaoTong University | Ren Y.,Yingda Changan Insurance Brokers Co. | Zhou X.,Yingda Changan Insurance Brokers Co. | Lin J.,Yingda Changan Insurance Brokers Co.
Dianli Xitong Zidonghua/Automation of Electric Power Systems | Year: 2012

In order to mobilize the enthusiasm of wind power plants to improve the reliability and power quality, different reliability levels of the insurance mechanism are proposed. The mechanism allows power companies to buy electricity from wind power plants at different prices, and wind power plants can also sign a level of insurance contract most suitable for their purchasing power characteristics. Power companies provide a strong economic signal to wind power plants, which is conducive to wind power plants making capital and technology investment economically and effectively. Meanwhile, with the introduction of the insurance mechanism, the risk of power loss will be shared by both parties. This paper also describes an insurance program example, and shows how the insurance can bring profit to both wind power plants and power companies so as to increase social benefits.

Liu Y.,Shanghai JiaoTong University | Lin L.,Yingda Changan Insurance Brokers Co. | Jiang C.,Shanghai JiaoTong University | Jin X.,Shanghai University of Electric Power | Ren Y.,Yingda Changan Insurance Brokers Co.
International Review of Electrical Engineering | Year: 2012

Uncertainty of wind generations increases the difficulty of balancing cost and risk during making spinning reserve plans. To meet this challenge, this article builds a multi-objective spare optimization model with the consideration of cost expectations and conditional value at risk. And it proposes a risk decision-making model based on fuzzy theory to finalize the reserve plan. Multi-objective immune algorithm and Monte Carlo scenario simulation are used to solve the optimization algorithms. The example shows that the multi-objective model can effectively find the front-set of cost expectations and conditional value at risk; fuzzy risk decision-making model expand the effective range of the risk tolerance coefficient than the traditional one, and it can reflect the risk attitudes more clearly; the model considering both expectation and risk is more advantage than the one with just expectation from the view of risk aversion, and it can be seen as a risk management tool of decision-makers. © 2012 Praise Worthy Prize S.r.l. - All rights reserved.

Liu Y.-J.,Shanghai JiaoTong University | Wang X.,Shanghai JiaoTong University | Jiang C.-W.,Shanghai JiaoTong University | Zhou X.-B.,Yingda Changan Insurance Brokers Co.
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | Year: 2013

With integration of large scale wind generation, many power systems utilize the chance constrained reserve plan instead of the traditional one. It brings not only the high utilization of wind energy but also outage risks. The paper thus proposes a risk transformation method with insurances for reserve risks. This paper considers both forecasting error and unit outage loss as stochastic variables to conduct research based on three types of distributions of forecasting errors and four types of distributions of unit outage loss, and to evaluate the risks with their expectation, value at risk and expected shortfall. The example results show that the forecasting error distribution would have decisive roles on the expectations and value at risks with low credit, but the tail loss with small probability including the expected shortfall and value-at-risk with high degree of confidence would be decided by both distributions of forecasting error and unit outage loss. The results also show that the power grid and insurance company can achieve win-win via the risk aversion of insurance mechanism.

Liu Y.,Shanghai JiaoTong University | Jin X.,Shanghai Key Laboratory of Power Station Automation Technology | Jiang C.,Shanghai JiaoTong University | Zhou X.,Yingda Changan Insurance Brokers Co.
Energy Education Science and Technology Part A: Energy Science and Research | Year: 2012

Uncertainties of renewable generations and electricity prices cause economic risks for owners of renewable generations when they make supply bid in electricity market. Previous works mostly adopted the risk management method to reach a compromise between economic risks and expected costs. However, the owners might face unbearable economic losses when large forecasting errors of outputs of renewable generations and electricity prices happen at the same time. This paper proposes a risk transformation method for those owners to avoid those accidental but huge losses though covering insurances. The proposed method utilizes insurances to convert the rare and unbearable economic losses to the deterministic and acceptable ones. Simulation results show that the proposed method will enlarge the expectation of economic losses but reduce the conditional value at risk of owners of renewable generation; meanwhile, the insurance company also gets opportunities to acquire more profits from the business. All those performances prove that the proposed method can solve the tail risks which are the intractable problems for traditional risk management methods. © Sila Science. All Rights Reserved.

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