Article ID Journal Published Year Pages File Type
399852 International Journal of Electrical Power & Energy Systems 2013 9 Pages PDF
Abstract

Electricity price is influenced by a number of factors. The power pricing mechanism currently in place in China does not reflect the scientific relationship between the price and those factors, so that a rational assessment of the electricity price chain is a major problem for China. This paper will argue from a system point of view that a comprehensive electricity price risk assessment model can be established which is based the Interpretative Structural Modelling (ISM) and Error Correction Modelling (ECM). The factors which influence the chain of electricity price were first analysed from an ISM perspective, after which the layered structure diagram and transmission chain of risk factors to power sale price (PSP) were constructed and sorted. The influences of various risk factors were quantified based on the input–output method and ECM, while the sequence and the comprehensive influence coefficients of various factors known to affect PSP were calculated. Based on analysis of the case study, the power generation sector and the fluctuations of alternative energy prices are seen to have greater influences on PSP as compared to other risk chains, while coal price is the most direct and critical risk factor, with a comprehensive influence coefficient of 0.37. Avoiding electricity price risk can be achieved by first improving the mechanism of the coal–electricity price linkage. This model describes a new way to assess electricity price risk, which in turn can provide a decision basis for electricity price management and risk prevention in developing countries.

► Power price risk chain assessment should consider various factors comprehensively. ► Coal price is the most critical and direct power price risk factor. ► It is significant to improve the mechanism of coal–electricity price linkage. ► International energy price risk warning system should be gradually established. ► The rapid development of electrical vehicle would impact energy prices greatly.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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