The integration of variable renewable energy sources reduces greenhouse gas emissions but introduces significant operational challenges to modern power systems. Grid-scale energy storage systems provide the essential flexibility required to mitigate these short-term uncertainties. Furthermore, these technologies enable a more economical system operation and actively assist in reducing overall greenhouse gas emissions. This paper proposes a stochastic multi-objective formulation for the optimal sizing and siting of grid-scale energy storage systems. The model simultaneously minimizes the total expected system costs and the expected thermal emissions. The Augmented $\varepsilon $ -Constraint (AUGMECON) method is implemented to generate the exact Pareto frontier. The proposed stochastic framework captures load and renewable generation uncertainties using representative daily scenarios. The mathematical formulation fully integrates the strict unit commitment constraints of the conventional thermal fleet. Case studies are conducted on the modified IEEE 24-bus Reliability Test System. The results demonstrate how the trade-off between financial savings and environmental priorities fundamentally alters the optimal spatial allocation and capacity requirements of the energy storage systems.
The increasing demand for clean and cost-effective energy has driven the development of hybrid renewable energy systems, particularly those combining wind and solar power. This paper introduces a practical optimization model for sizing hybrid onshore wind and photovoltaic power plants, incorporating critical systemic c...
Levi Freitas Fernandes Távora, Danielle Costa Morais· International Journal of Sus...· 0 citations
The increasing integration of distributed energy resources and flexible loads has transformed university campuses into complex energy systems that require coordinated operational strategies capable of managing renewable uncertainty while maintaining economic and environmental performance. This paper proposes a two-stag...
Edwin M. Garcia, C. Cuji, A. Aguila Téllez et al.· Sustainability· 1 citation
High renewable energy penetration and surging electrical demand challenge the operation of integrated electricity–gas systems (IEGS) due to source and load uncertainties. This paper proposes a multi-objective optimal scheduling framework that harnesses flexible resources within the IEGS to balance economic, environment...
Hong Fan, Jia-Wen Yu, Feng You et al.· Applied Sciences· 0 citations
The growing penetration of renewable energy sources introduces significant uncertainties into integrated energy systems (IESs). Conventional single-timescale management strategies, typically designed for static power balance, fail to address the symmetry of source-load uncertainties arising from both supply and demand...
Mu Li, Shou-Yuan Wu, Yu-Man Song· Symmetry· 0 citations
Hybrid renewable microgrids are increasingly considered a practical solution for supplying reliable and sustainable electricity to remote regions. However, many planning studies do not consider the longer-term effects of battery degradation and the effect of changing operating conditions on system performance. This stu...
A. G. M. A. Aziz, Abdullah M. Alharbi, Mohamed B. Farghaly et al.· Mathematics· 0 citations
The high integration of renewable energy sources significantly increases operational uncertainties in power systems, while traditional stochastic programming and robust optimization methods exhibit limitations when dealing with incomplete probability distribution information. This paper proposes a multi-objective distr...
