Multi-objective, multi-level, multi-dimensional least-cost planning for long-term electric power generation development in the least-developing countries : a case study of Sudan / Hussein A. Elhag.

Format:

Book

Manuscript

Microformat

Thesis/Dissertation

Author/Creator:

Elhag, Hussein A.

Contributor:

Adams, F. Gerry, advisor.

University of Pennsylvania.

Language:

English

Subjects (All):

Penn dissertations--Energy management and policy.

Energy management and policy--Penn dissertations.

Local Subjects:

Penn dissertations--Energy management and policy.

Energy management and policy--Penn dissertations.

Physical Description:

xviii, 567 pages : illustrations ; 29 cm

Production:

2001.

Summary:

This research argues that the United States' version of the L&barbelow;east-C&barbelow;ost P&barbelow;lanning (LCP) for electric power long-term development is insufficient to fully accommodate the problems associated with planning for this sub-sector in the L&barbelow;east-D&barbelow;eveloping C&barbelow;ountries (LDC's). This insufficiency is due to diverse and often conflicting objectives among these countries' national and socio-economic development priorities. It then suggests a modified LCP framework, to be based on multi-objective decision-making process, to integrate the objectives of the electric power sub-sector with those of broad social and national economic development concerns. This modified approach has termed by this research as the M&barbelow;ulti-O&barbelow;bjective L&barbelow;east-C&barbelow;ost P&barbelow;lanning (MOLCP). The solution of this model was based on the analysis of two other models, which are supportive and created specifically for the analysis of this research, and based on valid weighting methods.

The first is the P&barbelow;rioritization D&barbelow;ecision-M&barbelow;aking model (PDM) which was actually based on the Analytical Hierarchy Process technique. The function of this model is to allocate the limited domestic energy resources among all energy-consuming sectors on the basis of the availability or scarcity of other energy substitutes for primary energy sources mainly used in each sector. The outcome of this model determines the type and amount of fuels that would be available for each sector, including electric power generation. This, in turn, would indeed determine the type of generating technologies that might be introduced in the long-term power development. In the second model, nine objectives, subsuming twenty seven associated attributes, are evaluated by means of the M&barbelow;ulti-O&barbelow;bjective M&barbelow;ulti-D&barbelow;imensional D&barbelow;ecision-M&barbelow;aking model (MOMDM). Since not all the objectives enjoy the same load of importance to the planning problem under question, a M&barbelow;ulti-L&barbelow;evel approach was developed to classify these objectives in three group-levels each with a specific weight of importance.

MOMDM model uses a graphical representation method to measure the effectiveness of five future alternative scenarios in fulfilling the stated objectives. It has the capability of generating a single optimum future alternative plan which is practically difficult to achieve through conventional multi-objective models. Since the success of a multi-objective decision-making model is ultimately judged by the degree to which it satisfies the stated objectives, the MOMDM model successfully does that by comparing and ranking how much satisfaction each attribute gets for each alternative with respect to each objective. Efficacy of the theoretical framework and validity of the models are tested by a case study on Sudan as a typical LDC example.

In order to refine the outcome of the MOMDM model, i.e., the selection of the optimum long-term alternative, a series of sensitivity analyses were conducted for the most detrimental factors in power generation planning. Results of this operation proved the validity of the MOMDM model and guaranteed the selection of an optimum future plan in similar cases including those in advanced developed countries.

Notes:

Supervisor: F. Gerry Adams.

Thesis (Ph.D. in Energy Management and Policy) -- University of Pennsylvania, 2001.

Includes bibliographical references and index.

Local Notes:

University Microfilms order no.: 3015309.

OCLC:

244972445