Оптимизация планирования микросетей: современные подходы и перспективы

АКТУАЛЬНОСТЬ. В данной статье представлен обзор современных подходов к оптимизации планирования микросетей, включая методы многоцелевой оптимизации, учет неопределенностей и применение интеллектуальных алгоритмов. Микросети, как ключевой элемент современных энергетических систем, объединяют распределенные источники энергии, устройства накопления и нагрузки, что позволяет повысить эффективность, надежность и экологичность энергоснабжения. МЕТОДЫ. В работе рассмотрены основные модели оптимизации, такие как минимизация эксплуатационных затрат, снижение выбросов и повышение надежности электроснабжения. Особое внимание уделено методам учета неопределенностей, связанных с возобновляемыми источниками энергии и нагрузкой, а также роли систем накопления энергии и управления спросом. В статье также анализируются традиционные и интеллектуальные алгоритмы оптимизации, включая генетические алгоритмы, методы роя частиц и глубокое обучение. РЕЗУЛЬТАТЫ. Применение современных моделей, таких как SRSM-SOCR, модифицированный алгоритм Bet (MBA), глубокое обучение с подкреплением (DRL) и глубокая рекуррентная нейронная сеть (DRNN), позволило достичь сокращения эксплуатационных издержек микросетей на 18-25%, увеличения доли генерации из возобновляемых источников до 70-75% и снижения выбросов CO₂ до 60%. Также представлены реальные примеры внедрения микросетей в Германии и Греции, подтверждающие эффективность указанных подходов. ЗАКЛЮЧЕНИЕ. На основе анализа литературы выделены ключевые направления для будущих исследований, такие как интеграция миграционного обучения и глубокого обучения с подкреплением для повышения адаптивности моделей. Результаты исследования могут быть полезны для разработки эффективных стратегий управления микросетями в условиях растущей доли возобновляемых источников энергии и изменяющихся требований к энергосистемам.

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