The implementation of the market mechanism, which includes electricity price fluctuation, and a wide integration of intermittent generation, namely solar PV and wind energy, in energy production have changed the role and operation manner of conventional generation. It is partly or not at all adapted to new running conditions. Therefore, the efficiency and flexibility of conventional generation has to be improved. The numerical approach is developed in the context of combined cycle gas turbine (CCGT) technology to adapt its running conditions to the electricity market mechanism. The developed approach was verified on a case study of the Baltic States (Latvia) examples in a multi-paradigm numerical computing environment MATLab. The obtained results show that the added profit is gained through production of supplementary electricity, and the impact of cycling operation is reduced through the decrease of cycling operation ranges numbers and the substitution of start-up with a less adverse one from a technical and economical point of view. The developed approach can be adapted to various technologies and situations by adding appropriate characteristics and constraints of technology.

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The paper describes modelling, design and testing of the developed Energy Management Strategy (EMS) system simulation model. The project was carried out by NTNU and IPE contributing to CloudGrid, with the aim to develop a new real-time simulation model with price-based Demand Response (DR) program for future implementation as consumer flexibility tool. Real load data were used as the basis of the model that was tested in Real-time Simulator in Norwegian National Smart Grid Laboratory at NTNU, with an algorithm and measurements provided from IPE member side.

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In the research, the influence of optimised combined cycle gas turbine unit-according to the previously developed EM & OM approach with its use in the intraday market-is evaluated on the generation portfolio. It consists of the two combined cycle gas turbine units. The introduced evaluation algorithm saves the power and heat balance before and after the performance of EM & OM approach by making changes in the generation profile of units. The aim of this algorithm is profit maximisation of the generation portfolio. The evaluation algorithm is implemented in multi-paradigm numerical computing environment MATLab on the example of Riga CHP-2. The results show that the use of EM & OM approach in the intraday market can be profitable or unprofitable. It depends on the initial state of generation units in the intraday market and on the content of the generation portfolio.