Estimating the net electricity energy generation and demand using the ant colony optimization approach: Case of Turkey
Estimating the net electricity energy generation and demand using the ant colony optimization approach: Case of Turkey
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DOI：
10.1016/j.enpol.2008.11.017
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发表时间：
2009-03
期刊：
影响因子：
9
通讯作者：
M. Toksari
中科院分区：
文献类型：
--
作者：
M. Toksari
本文介绍了土耳其的净发电量和需求的基础上的经济指标。首次提出了基于蚁群算法的电力系统发电量和需求量预测模型。它是一种多智能体系统，其中每一只蚂蚁的行为都受到真实的蚂蚁觅食行为的启发来解决优化问题。利用人口、国内生产总值（GDP）、进出口等数据建立了蚁群优化电能估算模型。这里提出的所有方程都是线性电能生产和需求（线性_ACOEEGE和线性ACOEEDE）和二次电能生产和需求（二次_ACOEEGE和二次ACOEEDE）。由于经济指标的波动，发电量和需求量的二次模型提供了更好的拟合解。ACOEEGE和ACOEEDE模型根据三种情景显示了土耳其到2025年的净发电量和需求。
This paper presents Turkey's net electricity energy generation and demand based on economic indicators. Forecasting model for electricity energy generation and demand is first proposed by the ant colony optimization (ACO) approach. It is multi-agent system in which the behavior of each ant is inspired by the foraging behavior of real ants to solve optimization problem. Ant colony optimization electricity energy estimation (ACOEEE) model is developed using population, gross domestic product (GDP), import and export. All equations proposed here are linear electricity energy generation and demand (linear_ACOEEGE and linear ACOEEDE) and quadratic energy generation and demand (quadratic_ACOEEGE and quadratic ACOEEDE). Quadratic models for both generation and demand provided better fit solution due to the fluctuations of the economic indicators. The ACOEEGE and ACOEEDE models indicate Turkey's net electricity energy generation and demand until 2025 according to three scenarios.