|کد مقاله||کد نشریه||سال انتشار||مقاله انگلیسی||ترجمه فارسی||نسخه تمام متن|
|4959459||1445945||2018||17 صفحه PDF||سفارش دهید||دانلود کنید|
- The improved screening curve approach accounts for both existing and candidate units.
- Feasible cost polygons are formed based on the Karush-Kuhn-Tucker conditions.
- The geometrical method calculates and finds the cost polygon with the minimum area.
- The proposed method is more efficient and simple than the previous improvements.
In this study, a new method is developed to determine the least cost capacity expansion of a power system by using the screening curve method. The proposed methodology differs from the previous studies by its geometrical solution process to evaluate a capacity expansion problem considering both existing and candidate power plants. The algorithms are computationally more efficient and simple than the ones in previous studies for the same improvement. Further, the interpretation of the optimal capacity expansion plan is enhanced by explicitly exhibiting the results of all considered capacity expansion alternatives. The solution process can be interpreted as minimizing the long run marginal cost of supplying 1 megawatt of capacity during the whole year by finding the optimal combination of units. The developed method calculates and finds the cost polygon with the minimum area by moving along the intersection points of the screening curves to form trapezoids and then joining them to form cost polygons. The intersection points, which are needed to calculate the areas of the cost polygons, are found by using the Karush-Kuhn-Tucker conditions in a recursive manner. The last unit in the merit order of dispatching is determined by scenarios to yield an optimal capacity expansion plan. The scenarios are primarily based on a tradeoff between incurring investment costs by commissioning candidate units or taking online existing units with relatively higher variable costs compared to the candidate units.
Journal: European Journal of Operational Research - Volume 264, Issue 1, 1 January 2018, Pages 310-326