Optimization of electric power system modes under conditions of partial uncertainty of initial infor-mation

Abstract

Relevance: In problems of optimal planning of short-term power system states, partially uncertain load capacity is considered. The partially uncertain nature of active node loads is associated with many factors, which creates certain difficulties. Existing methods for forecasting node loads do not allow for the determination of load schedules for the planning period, taking into account all influencing factors. As a result, optimization results obtained using such load schedules typically contain significant errors, reducing optimization effectiveness. Therefore, given current operating conditions, improving methods and algorithms for optimal planning of short-term power system states under conditions of partial uncertainty of initial data is a pressing issue.

Objective: Improving the algorithm for optimizing short-term power system states under conditions of partial uncertainty of initial data.

Aim: Improving the algorithm for optimizing short-term power system modes under conditions of partial uncertainty of initial information.

Methods: Comparative analysis methods and optimization algorithms are applied taking into account international experience and requirements.

Results: Оптимальное планирование краткосрочных режимов в сфере ЭЭС в Узбекистане в условиях четиной неопределённости исходных данных, проверка эффективности предложенного алгоритма на тестовых схемах.