Aggregator as cost optimization tool for energy demand
2018
Zvirgzdina, M., Riga Technical Univ. (Latvia) | Bogdanova, O., Riga Technical Univ. (Latvia) | Spiridonovs, J., Riga International School of Economics and Business Administration (Latvia)
Historically, the absolute price flexibility and perfect competition was always considered as purely theoretical issue. Even in well developed markets flexibility of demand is usually hindered by lack of information on differences in offers available on the market. Similar pattern characterises power market as well. Electricity users are usually consuming the same amount of power regardless the changes of the power price, which makes the electricity consumption inelastic to the electricity price. Consequently, to meet a given demand, the same constant volume has been classically ensured on supply side by stable centralized power generation. However, due to climate protection policy the share of renewable energy sources in power generation is growing rapidly. It means more variable energy supply and more explicit electricity price fluctuations. The development of smart technologies and aggregation tools ensure a great opportunity to adjust the electricity consumption to the generated energy in a certain time. In this way, the available energy sources can be used to their fullest potential, the electricity system can be stabilised by levelling out the peak load hours and the electricity prices can be stabilised avoiding big fluctuations. The aim of the research is to analyse aggregators as a tool to facilitate power price flexibility through electricity demand response development, therewith demonstrating how the classical principle of economics’ theories on demand-supply flexibility find their practical application. In the research generally accepted quantitative and qualitative methods of economic science, comparative analysis, statistical data processing, synthesis, inductive, deductive, logically constructive, parameter estimation and economically mathematical modelling methods are applied.
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