Abstract 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.

中文翻译：

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电力热力扩建规划

摘要 这里描述和评估了短期电力和热能增加计划 (EPHGAP)。EPHGAP 的目标是找出最具成本效益和最可靠的扩展计划，以满足长期预测的电力需求和热量需求，同时满足大量的技术、成本效益、可靠性和社会约束. EPHGAP 问题是一个大维高约束混合整数非线性规划 (MINLP) 问题。已使用通用代数建模系统 (GAMS) 环境来实现所提出的公式，并且使用基本开源非线性混合整数 (BONMIN) 求解器解决了 EPHGAP 问题。一个原型测试系统，包括现有的火力发电厂、级联水力发电厂、热电联产机组、考虑使用纯热机组和候选热电联产机组以及级联水力发电厂来评估所提出的方法。测试系统的仿真结果与差分进化和粒子群优化获得的结果相匹配。从比较中可以看出，推荐的 BONMIN 求解器具有提供优质解决方案的能力。