Abstract
The unevenness of the electricity consumption schedule at enterprises leads to a peak power increase, which leads to an increase in the cost of electricity supply. Energy storage devices can optimize the energy schedule by compensating the planned schedule deviations, as well as reducing consumption from the external network when participating in a demand response. However, during the day, there may be several peaks in consumption, which lead to a complete discharge of the battery to one of the peaks; as a result, total peak power consumption does not decrease. To optimize the operation of storage devices, a day-ahead forecast is often used, which allows to determine the total number of peaks. However, the power of the storage system may not be sufficient for optimal peak compensation. In this study, a long-term forecast of power consumption based on the use of exogenous parameters in the decision tree model is used. Based on the forecast, a novel algorithm for determining the optimal storage capacity for a specific consumer is developed, which optimizes the costs of leveling the load schedule.
Highlights
The capacity of energy storage systems takes an increasing share in the total installed capacity of the energy system
It could be concluded that the electricity consumption was uneven and the load graph was subject to significant fluctuations
The results obtained in this article made it possible to use the resource of an energy storage system (ESS) with maximum efficiency, which could lead to an increase in the share of an ESS in the installed capacity of the power system
Summary
The capacity of energy storage systems takes an increasing share in the total installed capacity of the energy system. The areas of the application of energy storage systems are extensive today; they can be used in power supply systems of enterprises, systems of filling stations for electric vehicles, as well as system-wide energy storage systems for optimizing renewable energy sources, and an increase in the total capacity of energy storage systems increases their overall efficiency [1]. This is primarily due to the rapid development and integration of renewable energy sources based on solar and wind, which are characterized by an inconsistent power generation. Such solutions allow an increase in the share of distributed RES at the level of residential consumers; the capacity of individual consumers is not enough for a significant contribution to the unified energy system, and the storage units can be used only for their own needs
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