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Resource Planning

Power Price Layers

Power Price Layers
Source: AEP-East IRP, 2009

The issue
Vertically integrated utilities have an obligation to serve. In order to meet this obligation, utilities engage in vigorous resource planning to ensure they have enough capacity to meet peak customer demand. The result is a plan, known as an Integrated Resource Plan (IRP), to match a utility’s future suite of resources with projected demand for those resources. As such the plan lays out the amount, timing and type of resources that achieve this goal at the lowest reasonable cost, considering all the various constraints – reserve margins, emission limitations, renewable and energy efficiency requirements – that it is mandated to meet.

Planning for future resource requirements during volatile periods can be challenging. Unprecedented economic contraction and varying levels of proposed regulation regarding greenhouse gases and renewable energy are two major drivers of uncertainty that must be addressed during the planning process.

Current supply resources
The initial step in the IRP process is the demonstration of the region-specific capacity resource requirements. This “needs” assessment must consider projections of:

Long-term Forecast Process Flow
Long-term Forecast Process Flow
Source: AEP SEA
  • Existing capacity resources—current levels and anticipated changes
  • Changes in capability due to efficiency and/or environmental retrofit projects
  • Changes resulting from decisions surrounding unit disposition evaluations
  • Regional capacity and transmission constraints/limitations
    • Load and (peak) demand
    • Current DR/EE impacts
    • RTO-specific capacity reserve margin criteria

Planning objectives
In addition to the determination of a fundamental capacity “needs assessment,” the other objective of a resource planning effort is to recommend an optimum system expansion plan, not only from a least-cost perspective, but also from the perspectives of planning flexibility, creation of an optimum asset mix, adaptability to risk and, ultimately, from the perspective of affordability.

Challenges to long-term planning
The increasing number of variables and their uncertainty has added to the complexity of producing an integrated resource plan. No longer are the variables merely the cost to build the generation, a forecast of what had traditionally been stable fuel prices and growth in demand over time. Highly volatile fuel prices and uncertainty surrounding the economy and environmental legislation require that the process used to determine a resource plan is sufficiently flexible to incorporate more subjective criteria.

One way of dealing with uncertainty is to maintain optionality. That is, if there exists the potential for very expensive carbon legislation, one might favor a solution that minimizes carbon emissions, even if that solution is not the least expensive. While there may not yet be a national RPS, procuring or adding wind generation resources now will put a company ahead of the game if one does come to pass. In this way, the company is trading future uncertainty for a known cost. Lastly, adding diversity to the generating portfolio reduces the risk of the overall portfolio. That may not be the least expensive option in a “base” (or most probable) case, but it minimizes exposure to adverse future events and could reduce the ultimate cost of compliance if the resultant demand for renewable resources continues to grow, outpacing the supplier resource base.

Load and demand forecasting
One of the most critical underpinnings of the IRP process is the projection of anticipated resource “needs,” which, in turn, centers on the long-term forecast of load and (peak) demand. The forecast incorporates the effects of energy policy such as the Energy Independence and Security Act of 2007 (EISA) as well as load/price elasticity associated with policy impacts on price. The electric energy and demand forecast process involves three specific forecast model processes, as identified in the figure below.

Load and Demand Forecast Process
Load and Demand Forecast Process
Source: AEP-East IRP, 2009
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