Abstract

The past decade has not only witnessed a great shift in the energy mix, with electricity gaining a more and more prominent role, but has also seen electricity coming increasingly from renewable energy sources, whose proportion is forecasted to reach 50% by 2030. As the integration of photovoltaic energy cannot be deemed successful without the electricity supply being both sustainable and secure, such far-reaching developments prompt legislations and policy makers, including those of the European Union, to make changes to accommodate not only ever-changing technologies, including energy storage solutions, but also new players in the market. Currently, battery energy storage systems are not used for enhancing the precision of photovoltaic power generation schedules, so actors in the market find it difficult to make well-grounded decisions on the viability of utilizing batteries for such a purpose. The innovative novelty of the procedure presented in this paper is that it is suitable for the planning, analysis and evaluation of the schedule accuracy enhancing impacts of sodium-sulfur and lithium-ion-based battery energy storage systems of various capacities. By the examples of two European Union countries, this article studied the deviations of day-ahead and intraday photovoltaic power generation forecasts from the actual electricity generation of 1000 MWp photovoltaic systems. The two main objectives of the project were to investigate the amount of the photovoltaic balancing needs, based on actual data compared to the day-ahead and intraday forecasts, and to establish to what extent sodium-sulfur and lithium-ion-based battery storage systems can decrease those requirements. Furthermore, by using a model for simulation, the potentials of a number of different energy storage capacities (nominal net storage capacities from 10 MWh to 10,000 MWh) for reducing grid balancing needs were assessed. The practical use of the model is that its application makes it possible to create a dynamic design, analysis and assessment system mechanism that can allow one to establish the multilevel schedule accuracy enhancing impacts of sodium-sulfur and lithium-ion energy storage systems linked to solar power plant systems. Real photovoltaic data from Belgium and Hungary were used to find out how the accuracy of PV power generation forecasts influence the level of the annual utilization of energy storage systems.

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