不确定条件下基于蒙特卡洛模拟的发电投资评估模型

伴随经济、能源的可持续发展,电力行业面临更多的不确定性挑战,传统发电投资决策方法不能适应解决新问题的要求。分析了当前发电投资评估面临的问题,从这些问题出发,对发电规划进行投资组合评估。在给定需求弹性条件下,确定由于发电成本变化而导致的负荷变化量,并将间歇性可再生能源视为对负荷的负的修正,对传统负荷持续曲线进行了改进。引入蒙特卡洛模拟方法,构建了各种不确定性因素的概率分布,包括资本成本、燃料和碳价格、负荷需求,并在投资组合成本风险中考虑了这些不确定性因素及其之间的相关性,进而将不确定性问题融入了投资组合分析中。以广东省能源规划为算例,对构建模型进行验证,算例给出了不同碳价格下的发电组合有效边界以及发电成本、CO2排放和风险的趋势变化,研究表明,碳排放政策对清洁能源发展具有促进作用,而且核电在目前的政策环境下将会有较大的发展潜力。算例验证了模型的有效性。

Generation Investment Evaluation Model Under Uncertainty Based on Monte Carlo Simulation

With the sustainable development of the economy and energy, electric power industry is faced with more uncertainty challenges, while conventional power generation decision-making methods are not able to meet the requirement for solving new problems. The current problems facing the power generation investment assessment are analyzed, on the basis of which, the generation portfolios are assessed. Firstly, under given elastic conditions of demand, the amount of change of load due to the change of generation cost is determined, with the intermittent renewable energy sources regarded as negative load correction. As an improvement on the conventional load duration curve, the impact of demand elasticity and intermittent energy is considered. Secondly, the Monte Carlo simulation method is used to simulate the uncertainties, including capital cost, load, fuel and carbon price to have the uncertainties merged into power generation investment portfolio assessment. Finally, a case study is analyzed with the example of Guangdong Province, the effective boundary, generation cost, CO2 emission and cost risk are obtained therefrom. The research results show that the carbon emissions policy is helpful to the development of clean energy, while the nuclear power will have greater development potential in the current policy environment. The proposed methodology is proved effective. This work is supported by National Soft Science Research Program (No. 2012GXS4B064) and National Natural Science Foundation of China (No. 71271082).