A technique for multi-attribute utility expansion planning under uncertainty: with focus on incorporating environmental factors into the planning process

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Virginia Tech


Within the past two decades, the planning arena has changed considerably and increasing awareness of the impacts of utility generation, intensifying pressure from the public and regulators, and growing competition from other energy and electricity suppliers have made the utility planning process rather complex. The variety of players in utility planning has introduced new priorities and a new set of competing objectives. Increased resource scarcity, the requirement for economic efficiency and the need to view the electricity production and utilization process in its entirety also necessitate an integrated resource planning approach, resulting in a wider array of expansion alternatives that must be evaluated. Another characteristic that makes planning so complicated is the uncertainty in the factors that influence the cost of the power system plan.

Public concern for the environment has resulted in a series of legislations for controlling emissions of acid rain precursors (SO₂ and NOx) and other pollutants. More and more regulators are also requiring electric utilities to internalize environmental externalities in their planning processes. The potential for new legislation on currently uncontrolled effluents like CO₂ likewise remains. There is thus a need to examine the modeling of emissions that would reflect not only the cost of control but the environmental impacts of these emissions as well.

This thesis combines the features of the trade-off and decision analysis techniques to address the multiplicity of objectives and the uncertainties of planning. It draws on Saaty's analytic hierarchy process (AHP) and the interdependent data analysis (IDA) technique developed at Virginia Tech to develop priority weights among objectives and probability distributions of uncertainties. It elucidates the relationship between the competing techniques of trade-off analysis and the method of weights in terms of the economic theory of the firm. The confidence intervals determined with the IDA technique are then used to obtain a range of alternatives that satisfy the requirements of both approaches for evaluation by the decision maker (DM).

Special attention is given to the environmental impacts of the generation plan and the model accounts for these issues as attributes in the planning process as well as being legislation uncertainties.



generation planning, multi-objective decision making, emission reduction