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Defining Distributed Resource Planning

Charles D. Feinstein and Jonathan A. Lesser

Year: 1997
Volume: Volume 18
Number: Distributed Resources: Toward a New Paradigm of the Electricity Business
DOI: 10.5547/ISSN0195-6574-EJ-Vol18-NoSI-3
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Abstract:
The concept and objectives of distributed utility planning, sometimes called distributed resource (DR) planning, are unclear, This paper provides a cogent definition of DR planning and explains some of the emerging fallacies over its purpose. The objective of DR planning should be to meet customers' capacity needs at the lowest expected future cost by determining an optimal investment strategy for a given area. Many advocates of DR planning have erroneously defined the objective as deferral of "traditional" transmission and distribution facilities, and have developed methodologies to determine maximum deferral times. Defining the DR planning objective in this manner will always lead to higher than necessary costs, because cost-minimization is not addressed in an appropriate manner. In general, deferral methodologies have misspecified the objective function, used quantitative tools inappropriately, and, perhaps their most critical shortcoming, failed to incorporate the effects of uncertainty on the optimal investment strategy. The solution is to treat deferral as a consequence of developing a least-expected-cost distribution plan, rather than treating deferral as an objective in itself.



Capacity Planning Under Uncertainty: Developing Local Area Strategies for Integrating Distributed Resources

Charles D. Feinstein, Peter A. Morris and Stephen W. Chapel

Year: 1997
Volume: Volume 18
Number: Distributed Resources: Toward a New Paradigm of the Electricity Business
DOI: 10.5547/ISSN0195-6574-EJ-Vol18-NoSI-5
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Abstract:
This paper presents a methodology that helps DR planners evaluate strategic investment policies under uncertainty. Application of the methodology will not only lower utilities' costs, but also help them prepare for the future with contingency plans and a deeper understanding of the opportunities and risks they face. The formulation responds to the need to evaluate future options as uncertainty unfolds over time. For such problems, the joint consideration of dynamics and uncertainty makes the problem much too large for conventional probabilistic analysis methods and places it beyond the scope of conventional deterministic engineering analyses. The problem is formulated as a dynamic optimization problem under uncertainty. A practical solution technique for solving the problem based on a compact specification of the system state is introduced. An example, taken from actual practice, is presented. The potentially large economic value of DR investments in providing managerial flexibility is quantified. We demonstrate that the optimal level of DR investment found by our approach is superior to the level of DR investment specified by existing methodologies. Although the concepts are presented in the context of electric utility distributed resources planning, they are more widely applicable to other strategic investment problems.





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