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STATISTICAL APPROACH TO EVALUATE POWER GENERATION SOURCES’ INFLUENCE ON ELECTRICITY MARKET PRICE: LITHUANIA CASE
Mindaugas Cesnavicius, Inga Konstantinaviciute

ABSTRACT: This article introduces a statistical approach that helps to evaluate different power generation sources’ influence on electricity market prices. The methodology involves certain regions’ electricity market and power grid data time series analysis. The two-stage correlation analysis method is used to determine electricity sources that meaningfully influence electricity prices and do not correlate with electricity load. Those electricity generation sources are selected for the linear regression where the dependent variable is electricity market price and independent variables are identified generation sources. The regression equation is a final methodology tool that assesses different power generation sources’ impact on electricity market price. Coefficient value, besides each independent variable, identifies the magnitude of the impact, while positive and negative signs determine if the electricity market price would increase or decrease if an average monthly generation of a certain source would be increased. The proposed approach allowed us to estimate different electricity sources’ influence on electricity prices in Lithuania. Run-of-river generation and electricity import are identified as two variables meaningfully influencing electricity market prices in Lithuania. Regression analysis showed that a 1 MW increase in an average monthly run-of-river generation could decrease electricity price by 0.131 € while a 1 MW increase in average monthly electricity import could increase electricity price by 0.017 €.

KEYWORDS:  electricity market price, power generation sources evaluation, methodology, correlation, regression.

JEL classification:  C10, C20, Q47.