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Risk measurement and optimization model of coal generation contracts for the difference between prospect M-V and normal triangular fuzzy stochastic variables

Weiwei Li (School of Management, Heilongjiang University of Science and Technology, Harbin, China)
Chong Wu (School of Management, Harbin Institute of Technology, Harbin, China)
He Dong (School of Management, Harbin Institute of Technology, Harbin, China)
Huan Wang (School of Management, Harbin Institute of Technology, Harbin, China)
Mei Li (School of Economics and Management, Guangxi Teachers Education University, Nanning, China)

Kybernetes

ISSN: 0368-492X

Article publication date: 5 September 2016

183

Abstract

Purpose

Coal and power generation are related upstream and downstream industries. Coal price marketization and electricity price regulation have caused the price of coal to be sensitive to the benefits of generators. The paper aims to discuss these issues.

Design/methodology/approach

As a financial tool, contracts for differences can both help balance interests and reduce risks caused by spot price fluctuation. This thesis regards coal demand as a triangular fuzzy stochastic variable while directing a levelling consideration towards risk returns for coal and power enterprises that are involved in coal generation contracts for differences. Risk and benefit measurement models were established between coal suppliers and power generators, and risk and benefit balance optimization models for contract negotiation were constructed.

Findings

A numerical example showed that the above models can be effectively used to avoid the risks of coal-electricity parties.

Originality/value

This thesis regards coal demand as a triangular fuzzy random variable while directing a levelling consideration towards the risk return to coal and power enterprises that are involved with coal generation contracts for differences. The features of this thesis are the following: demand information is regarded as a fuzzy random variable instead of a random variable. With historical data, sales experience and increasingly clear macro-economic conditions, coal and power enterprises are able to make a fuzzy decision – to a certain extent – when the transaction approaches. Accurate market information enables the supply chain system to satisfy the clients’ needs better, improve the profit level or avoid severe financial damages; by developing a feasible set of contracts for different parameters, it is possible to estimate whether the price difference enables supply chain coordination, requires changes or gives accounts to all involved parties of the supply chain; and without the assumption that the traditional M-V rule is unfavourable to decision makers, this thesis proposes the prospect M-V rule, which involves decision makers’ projections of future coal generation prices and enables wide applicability of the response method to contracts for differences.

Keywords

Acknowledgements

Conflicts of interest: the authors declare no conflicts of interest.

This research was supported by the National Natural Science Foundation of China under Grant No. 71271070; Hei long jiang Social Science Foundation under Grant No. 12E040.

Citation

Li, W., Wu, C., Dong, H., Wang, H. and Li, M. (2016), "Risk measurement and optimization model of coal generation contracts for the difference between prospect M-V and normal triangular fuzzy stochastic variables", Kybernetes, Vol. 45 No. 8, pp. 1323-1339. https://doi.org/10.1108/K-10-2015-0266

Publisher

:

Emerald Group Publishing Limited

Copyright © 2016, Emerald Group Publishing Limited

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