FEATURES OF STOCHASTIC OPTIMIZATION FOR HYBRID POWER SYSTEMS WITH THE RENEWABLE SOURCES
Problems of RES integrating into grids need to be solved systematically, in order to use their capabilities efficiently, to avoid reducing the reliability of operating and the quality of energy, to ensure economic and environmental optimality. Existing approaches to power systems are predominantly deterministic, but the presence of variable energy sources requires a stochastic approach to optimality criteria and optimization tasks.
The optimal ratio of elements of the power system with renewable sources is established taking into account many factors. Optimization of the structure is carried out according to economic indicators, such as the cost of energy, as well as technical, taking into account the reliability of energy supply.
A correctly formulated extreme problem must contain a target function, or criterion, equations of state and restrictions. In the case of a combined power system, the power characteristics of system elements (power curves, battery charging characteristics, etc.) can be used as state equations. Restrictions in the form of inequalities would describe the general parameters of the power system, as network throughput, consumer needs, energy potential. As an additional optimization criteria may be used such indicators as power loss index, load loss index, energy loss index and other that depend on the changing nature of wind and sun. System adequacy indexes may also be part of the constraints. In general, the task is to find the minimum cost of the system configuration, which would meet the demand for the adequate quality of energy.
Some examples of the stochastic programming tasks for some combined power systems are offered. The choice of a specific type of task depends on the requirements to the grid, available information and the purpose of the study. The obtained indicators of the power system adequacy has a probabilistic assessment, which ensures the possibility of taking into account different criteria and assessing the quality of energy supply.
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