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Cited by 526

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Optimal Investment Planning for Distributed Generation in a Competitive Electricity Market

El-Khattam, W., Bhattacharya, K., Hegazy, Y., Salama, M.M.A.·2004·IEEE Transactions on Power Systems

Abstract

This paper proposes a new heuristic approach for distributed generation (DG) capacity investment planning from the perspective of a distribution company (disco). Optimal sizing and siting decisions for DG capacity is obtained through a cost-benefit analysis approach based on a new optimization model. The model aims to minimize the disco's investment and operating costs as well as payment toward loss compensation. Bus-wise cost-benefit analysis is carried out on an hourly basis for different forecasted peak demand and market price scenarios. This approach arrives at the optimal feasible DG capacity investment plan under competitive electricity market auction as well as fixed bilateral contract scenarios. The proposed heuristic method helps alleviate the use of binary variables in the optimization model thus easing the computational burden substantially.

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Metadata

Authors
El-Khattam, W., Bhattacharya, K., Hegazy, Y., & Salama, M. M. A.
Venue
IEEE Transactions on Power Systems
Published
2004-08
Volume
19
Issue
3
Pages
1674-1684
ISSN
0885-8950 (ISSN-L)
OpenAlex
W2164802766
Cited by
526
References
0
FWCI
11.44
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Optimal Investment Planning for Distributed Generation in a Competitive Electricity Market. https://app.cochat.ai/papers/10.1109/tpwrs.2004.831699
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El-Khattam, W., Bhattacharya, K., Hegazy, Y., & Salama, M. M. A. (2004). Optimal Investment Planning for Distributed Generation in a Competitive Electricity Market. IEEE Transactions on Power Systems. https://doi.org/10.1109/tpwrs.2004.831699

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.