Cost Analysis and Optimization of Modern Power System Operations

The reliable and economical operation of modern power systems is increasingly complex due to the integration of diverse energy sources and dynamic load patterns. A critical challenge is maintaining the balance between electricity supply and demand within various operational constraints. This study addresses the economic scheduling of generation units using a Mixed Integer Programming (MIP) optimization model. Key constraints considered include reserve requirements, ramp rate limits, and minimum up/down time. Simulations are performed across multiple scenarios, including systems with spinning reserves, responsive demand, renewable energy integration, and energy storage systems. For each scenario, the optimal mix of generation resources is determined to meet a 24 h load forecast while minimizing operating costs. The results show that incorporating demand responsiveness and renewable resources enhances the economic efficiency, reliability, and flexibility of the power system.

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Publication Details

Journal
Applied Sciences
Published
2025-07-30
DOI
https://doi.org/10.3390/app15158481
Primary Topic
Electric Power System Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Cost Analysis and Optimization of Modern Power System Operations

Ivo Palu, Sulabh Sachan, Praveen Prakash Singh, Ahto Pärl
Applied Sciences
Electric Power System Optimization
article

Cost Analysis and Optimization of Modern Power System Operations

Ivo Palu, Sulabh Sachan, Praveen Prakash Singh, Ahto Pärl
article en

Abstract

The reliable and economical operation of modern power systems is increasingly complex due to the integration of diverse energy sources and dynamic load patterns. A critical challenge is maintaining the balance between electricity supply and demand within various operational constraints. This study addresses the economic scheduling of generation units using a Mixed Integer Programming (MIP) optimization model. Key constraints considered include reserve requirements, ramp rate limits, and minimum up/down time. Simulations are performed across multiple scenarios, including systems with spinning reserves, responsive demand, renewable energy integration, and energy storage systems. For each scenario, the optimal mix of generation resources is determined to meet a 24 h load forecast while minimizing operating costs. The results show that incorporating demand responsiveness and renewable resources enhances the economic efficiency, reliability, and flexibility of the power system.

Applied SciencesVol. 15(15)
Tallinn University of Technology (EE), University of South-Eastern Norway (NO)
Affordable and clean energy
Openalex Percentile: Top 81%
Electric Power System Optimization
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