A Technique for Incorporating Uncertain Environmental Factors into the Utility Planning Process

拟议的研究工作试图开发一个 技术来模拟和研究的影响， 不确定的环境因素， 公用事业规划过程。 电力公司交易 在可用性方面存在不确定性， 以及替代能源、燃料和新能源的成本 减排技术。 也有 能源需求预测的不确定性，以及 需求侧管理计划的影响。 排放上限和排放交易特点 《清洁空气法修正案》 1990年的CAAA为 不确定性的问题。 有很大 市场价格估计的变化 排放限额。 同时，专家 政府在多大程度上 应该并将利用立法和条例， 限制排放。 鉴于这些 不确定性，公用事业规划者必须探索 各种可能的情况，以解决一个 稳健的发电计划。 评估工具， 目前正在应用假设可用性 不确定性和专家的措施 装饰它们。 这显然并不总是 案子 所提出的技术旨在 促进战略电力系统规划， 不确定性，通过生成概率估计 使用相互依赖的数据的专家意见 分析（IDA）技术正在开发中， 弗吉尼亚理工大学 这使决策者能够 仍在形成的典型观点。 应用 通过决策树/影响图分析， 可以产生一个强大的方法来量化 与环境因素有关的不确定性 公用事业规划过程。

The proposed research effort attempts to develop a technique to model and study the effects of uncertain environmental factors in the electric utility planning process. The electric utility deals with uncertainties with respect to the availability and costs of alternative generation, fuels, and new emission reduction technologies. There are also uncertainties in demand an energy projections, and the impact of demand side management programs. Emissions caps and emissions trading features provide for by the Clean Air Act Amendments (CAAA) of 1990 have added a new dimension to the problem of uncertainty. There are wide variations in estimates on the market price of emission allowances. At the same time experts disagree on the extent to which government legislation and regulations should and will be used to limit emissions. In the light of those uncertainties, the utility planner must explore a variety of probable scenarios in order to settle on a robust generation plan. The evaluation tools which are currently being applied assume the availability of the measures of uncertainty and of experts furnishing them. This is obviously not always the case. The proposed technique is designed to facilitate the strategic power system planning under uncertainty by generating probability estimates for expert opinions using the interdependent data analysis (IDA) technique being developed at Virginia Tech. This enables the decision maker to model opinions which are still forming. Applied with decision tree/influence diagram analysis, this can result in a robust methodology to quantify uncertainties related to environmental factors in the utility planning process.