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Electric Power and Heat Generation Expansion Planning

机译：电力和发热膨胀规划

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摘要

A short-term electric power and heat generation augmentation planning (EPHGAP) is portrayed and evaluated here. The objective of EPHGAP is to find out the most cost-effective and dependable expansion plan for meeting the forecasted electrical power demand and heat demand over a long-range horizon while fulfilling a large number of technical, cost-effective, reliability, and social constraints. The EPHGAP problem is a big-dimensional highly constrained mixed integer nonlinear programing (MINLP) problem. The general algebraic modeling system (GAMS) environment has been used to implement the proposed formulation, and the EPHGAP problem is solved by using Basic Open-source Nonlinear Mixed Integer (BONMIN) solver. An archetypal test system with existing thermal power plants, cascaded hydropower plants, cogeneration units, heat-only units and candidate cogeneration units, and cascaded hydro plants is considered to evaluate the proposed methodology. Simulation outcomes of the test system have been matched up to those acquired by differential evolution and particle swarm optimization. It has been observed from the comparison that the recommended BONMIN solver has the capability to bestow with superior quality solution.
机译：这里描绘和评估了短期电力和发热增强规划（EPHGAP）。 Ephgap的目标是找出最具成本效益和可靠的扩展计划，以满足预测的电力需求和远程地平线的热需求，同时满足大量技术，经济效益，可靠性和社会限制。 Ephgap问题是一个大维度高度约束的混合整数非线性编程（MINLP）问题。一般代数建模系统（GAMS）环境已被用于实施所提出的配方，通过使用基本开源非线性混合整数（Bonmin）求解器来解决Ephgap问题。具有现有火力发电厂，级联水电站，热电联产单位，散热单位和候选电生电设备以及级联水电植物的原型测试系统被认为是评估所提出的方法。测试系统的仿真结果已与差分演化和粒子群优化获得的那些匹配。从比较中观察到推荐的邦敏求解器具有卓越的质量解决方案的能力。

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