NONE 20260513092924918 wseas/wseas content-registration-form+ja@crossref.org content-registration-form WSEAS TRANSACTIONS ON CIRCUITS AND SYSTEMS 1109-2734 2224-266X David O. Briceño Departamento de Ingeniería Eléctrica y Electrónica Universidad Nacional de Colombia Ave Cra 30 #45-3 Bogotá D.C. COLOMBIA Diana S. López Departamento de Ingeniería Eléctrica y Electrónica Universidad Nacional de Colombia Ave Cra 30 #45-3 Bogotá D.C. COLOMBIA Sergio R. Rivera Departamento de Ingeniería Eléctrica y Electrónica Universidad Nacional de Colombia Ave Cra 30 #45-3 Bogotá D.C. COLOMBIA This paper presents a probabilistic and risk-aware framework for microgrid dispatch under renewable generation. In this way, solar irradiance is modeled using a log-normal distribution, on other hand, wind speed follows a Rayleigh distribution. We used a combined multi-regime wind turbine power curve for the eolic part. A scenario-based Monte Carlo approach got multiple realizations of renewable output per hour, enabling the explicit evaluation of intermittence or stochastic variability. In order to quantify operational risk, we formulate Uncertainty Cost Functions that integrates: (i) the expected operational cost, (ii) the Conditional Value-at-Risk (CVaR), and (iii) the variability of the battery State of Charge (SOC). The proposed approach is validated in a microgrid with solar, wind, battery storage, and flexible loads. Results demonstrate that the risk-aware dispatch significantly reduces tail-risk exposure, mitigates SOC fluctuations, and enhances operational resilience when compared to a conventional riskneutral strategy. 05 13 2026 05 13 2026 89 8 https://creativecommons.org/licenses/by/4.0/deed.en_US 10.37394/23201.2026.25.8 https://wseas.com/journals/cas/2026/a165101-006(2026).pdf J. Hetzer, D. C. Yu and K. Bhattarai, ”An Economic Dispatch Model Incorporating Wind Power,” in IEEE Transactions on Energy Conversion, vol. 23, no. 2, pp. 603-611, June 2008, https://doi.org/10.1109/TEC. 2007.914171. T. Clavier, Nima Razavi-Ghods, François Glineur, David González-Ovejero, Eloy de Lera Acedo, Christophe Craeye, ”A GlobalLocal Synthesis Approach for Large NonRegular Arrays,” in IEEE Transactions on Antennas and Propagation, vol. 62, no. 4, pp. 1596-1606, April 2014, https://doi.org/10. 1109/TAP.2013.2284816. J. Zhao, F. Wen, Z. Y. Dong, Y. Xue and K. P. Wong, ”Optimal Dispatch of Electric Vehicles and Wind Power Using Enhanced Particle Swarm Optimization,” in IEEE Transactions on Industrial Informatics, vol. 8, no. 4, pp. 889-899, Nov. 2012, https://doi.org/ 10.1109/TII.2012.2205398. S. Surender Reddy, P. R. Bijwe and A. R. Abhyankar, ”Real-Time Economic Dispatch Considering Renewable Power Generation Variability and Uncertainty Over Scheduling Period,” in IEEE Systems Journal, vol. 9, no. 4, pp. 1440-1451, Dec. 2015, https://doi. org/10.1109/JSYST.2014.2325967. Cardell, J. B., Anderson, C. L.: Analysis of the system costs of wind variability through Monte Carlo simulation. Presented at the 43rd Hawaii International Conference on System Sciences (HICSS), Honolulu, HI, 2010, pp. 1– 8, https://doi.org/10.1109/HICSS.2010. 61. Anderson, C. L., Cardell, J. B.: Analysis of wind penetration and network reliability through Monte Carlo simulation. Presented at the 2009 Winter Simulation Conference (WSC), Austin, TX, 2009, pp. 1503– 1510, https://doi.org/10.1109/WSC.2009. 5429298. Thomopoulos, N.: Essentials of Monte Carlo simulations. Statistical methods for building simulation models, Illinois Institute of Technology, ISBN 978-1-4614-6021-3, Springer Science (2013), https://doi.org/10.1007/ 978-1-4614-6022-0. Tomás Valencia-Zuluaga, Daniel AgudeloMartinez, Dario Arango-Angarita, Camilo Acosta-Urrego, Sergio Rivera, Diego Rodríguez-Medina, ”A Fast Decomposition Method to Solve a Security-Constrained Optimal Power Flow (SCOPF) Problem Through Constraint Handling,” in IEEE Access, vol. 9, pp. 52812-52824, 2021, https: //doi.org/10.1109/ACCESS.2021.3067206. Meng, J., Li, G., Du., Y.: Economic dispatch for power systems with wind and solar energy integration considering reserve risk. Presented at Power and Energy Engineering Conference (APPEEC), 8-11 Dec., 2013, https://doi. org/10.1109/APPEEC.2013.6837207. Guo, Q., Han, J., Yoon, M., Jang, G.: A study of economic dispatch with emission constraint in smart grid including wind turbines and electric vehicles. Presented at the Vehicle Power and Propulsion Conference (VPPC), 9- 12 Oct., 2012, pp. 1002–1005, https://doi. org/10.1109/VPPC.2012.6422753. 11] Xie, F., Huang, M., Zhang, W., Li, J.: Research on electric vehicle charging station load forecasting. Presented at International Conference on the Advanced Power System Automation and Protection (APAP), 2011, https://doi.org/10.1109/ APAP.2011.6180772. Xie, F., Huang, M., Zhang, W., Li, J.: Research on electric vehicle charging station load forecasting. Presented at International Conference on the Advanced Power System Automation and Protection (APAP), 2011, https://doi.org/10.1109/ APAP.2011.6180772. Sufen, T., Youbing, Z., Jun, Q.: Impact of electric vehicles as interruptible load on economic dispatch incorporating wind power. Presented at the International Conference on Sustainable Power Generation and Supply (SUPERGEN 2012), 8-9 Sept., 2012, https: //doi.org/10.1049/cp.2012.1816. D. Midence, S. Rivera and A. Vargas, ”Reliability assessment in power distribution networks by logical and matrix operations,” 2008 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America, Bogota, Colombia, 2008, pp. 1-6, https: //doi.org/10.1109/TDC-LA.2008.4641696. S. Mohseni and A. C. Brent, ”A noncooperative game-theoretic approach for the flexible operation of multi-microgrids,” 2023 IEEE Power Energy Society General Meeting (PESGM), Orlando, FL, USA, 2023, pp. 1- 5, https://doi.org/10.1109/PESGM52003. 2023.10253073. Mahdi Azimian, Reza Habibifar, Vahid Amir, Elham Shirazi, Mohammad Sadegh Javadi, Ali Esmaeel Nezhad, ”Planning and Financing Strategy for Clustered Multi-Carrier Microgrids,” in IEEE Access, vol. 11, pp. 72050-72069, 2023, https://doi.org/10. 1109/ACCESS.2023.3294482. S. Mohseni and A. C. Brent, ”Maximizing the Utilization of Demand Response in Multi-Microgrids: A Game-Theoretic Approach,” 2024 IEEE Power Energy Society General Meeting (PESGM), Seattle, WA, USA, 2024, pp. 1-5, https://doi.org/10. 1109/PESGM51994.2024.10688921. Y. Yao, Y. Xu, W. Gu, K. Liu, S. Lu and L. Mili, ”Inverse Uncertainty Quantification Assisted Forward Uncertainty Quantification in Power System Dynamic Simulations,” in IEEE Transactions on Power Systems, vol. 40, no. 5, pp. 4307-4321, Sept. 2025, https: //doi.org/10.1109/TPWRS.2025.3537758. A. Latifi and C. M. Scoglio, ”A Survey on Uncertainty Quantification in Dynamical Systems,” in IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 55, no. 8, pp. 5137-5151, Aug. 2025, https://doi. org/10.1109/TSMC.2025.3564984.