Поиск по каталогу |
(строгое соответствие)
|
- Профессиональная
- Научно-популярная
- Художественная
- Публицистика
- Детская
- Искусство
- Хобби, семья, дом
- Спорт
- Путеводители
- Блокноты, тетради, открытки
Clustering Based Unit Commitment Employing Soft Computing Techniques. Implementation Of Clustering Based Unit Commitment Employing Soft Computing Techniques
В наличии
Местонахождение: Алматы | Состояние экземпляра: новый |
Бумажная
версия
версия
Автор: Chandra Jagan Mohan Vyza
ISBN: 9786200479891
Год издания: 2019
Формат книги: 60×90/16 (145×215 мм)
Количество страниц: 128
Издательство: LAP LAMBERT Academic Publishing
Цена: 36272 тг
Положить в корзину
Способы доставки в город Алматы * комплектация (срок до отгрузки) не более 2 рабочих дней |
Самовывоз из города Алматы (пункты самовывоза партнёра CDEK) |
Курьерская доставка CDEK из города Москва |
Доставка Почтой России из города Москва |
Аннотация: Unit Commitment is an important and vital optimization task in a power control centre. After load forecasting it is the second step in the planning process. It consists of two linked optimization problems. It comprises unit ON/OFF scheduling problem and the economic dispatch sub-problem. The ON/OFF scheduling problem is a 0-1 combinatorial problem with equality and inequality constraints, while the economic dispatch sub-problem is a nonlinear constrained optimization problem.Unit commitment is a nonlinear, large scale, combinatorial, constrained optimization problem. The complete unit commitment optimization problem is to minimize the total production cost (TPC) of utility in such a way that the constraints such as load demand, spinning reserve, minimum and maximum power limits of units, minimum up (MUT) and minimum down times (MDT) are satisfied. Therefore, based on the forecasted load demand, preparing proper ON/OFF schedule of generators can result in cost saving for utility. It is much more difficult problem to solve due to its high dimensionality.The main issues in the UCP are complexity (high dimensions) of search space, generation of initial feasible schedules,
Ключевые слова: To develop new techniques for Unit Commitment Problem, Employing Soft Computing Techniques, Soft computing techniques, Clustering