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International Journal of Renewable, Green, and Sustainable Energy

Open Access Peer Review International
Open Access

COORDINATED MULTI-OBJECTIVE OPTIMIZATION FOR GREEN POWER SYSTEM SCHEDULING AND CONSUMPTION WITH DIVERSE DEVICES

DOI https://doi.org/10.55640/ijrgse-v02i01-01
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Dr. Hendra Wijaya 1 , Dwi Astuti 1 ,
4 Center for Energy Studies, Universitas Indonesia, Depok, Indonesia
4 Faculty of Engineering, Universitas Airlangga, Surabaya, Indonesia

Abstract

This study proposes a coordinated multi-objective optimization framework for scheduling and managing power consumption in green power systems with diverse energy devices. The system incorporates renewable sources, energy storage units, and controllable loads to enhance energy efficiency, reduce costs, and minimize environmental impact. A multi-objective evolutionary algorithm is employed to balance conflicting goals such as operational cost, emission reduction, and user comfort. Device-level coordination, including electric vehicles, HVAC systems, and smart appliances, is integrated to enable demand-side flexibility. Simulation results demonstrate the effectiveness of the proposed strategy in achieving optimal scheduling under dynamic load and generation conditions, contributing to the realization of intelligent, low-carbon energy systems.

Keywords

Green power systems, multi-objective optimization, energy scheduling

References

Nwagu, C. N., Ujah, C. O., Kallon, D. V. V., and Aigbodion, V. S., Integrating solar and wind energy into the electricity grid for improved power accessibility. Unconv Resour. 2025;5:100129. doi:10.1016/j.uncres.2024.100129.
Zhang, Y., Gao, Q., Li, H., Shi, X., and Zhou, D., Navigating the energy transition with the carbon-energy-green-electricity scheme: an industrial chain-based approach for China’s carbon neutrality. Energy Econ. 2024;140:107984. doi:10.1016/j.eneco.2024.107984.
Melo, G. d. A., Cyrino Oliveira, F. L., Maçaira, P. M., and Meira, E., Exploring complementary effects of solar and wind power generation. Renew Sustain Energy Rev. 2025;209:115139. doi:10.1016/j.rser.2024.115139.
Lv, M., Gou, K., Chen, H., Lei, J., Zhang, G., and Liu, T., Optimal design of Wind-Solar complementary power generation systems considering the maximum capacity of renewable energy. Energy. 2024;312:133650. doi:10.1016/j.energy.2024.133650.
Liang, C., Ding, C., Zuo, X., Li, J., and Guo, Q., Capacity configuration optimization of wind-solar combined power generation system based on improved grasshopper algorithm. Electr Power Syst Res. 2023;225:109770. doi:10.1016/j.epsr.2023.109770.
Gou, H., Ma, C., and Liu, L., Optimal wind and solar sizing in a novel hybrid power system incorporating concentrating solar power and considering ultra-high voltage transmission. J Clean Prod. 2024;470:143361. doi:10.1016/j.jclepro.2024.143361.
Li, F., Chen, S., Ju, C., Zhang, X., Ma, G., and Huang, W., Research on short-term joint optimization scheduling strategy for hydro-wind-solar hybrid systems considering uncertainty in renewable energy generation. Energy Strategy Rev. 2023;50:101242. doi:10.1016/j.esr.2023.101242.
Yavari, M. and Bohreghi, I. M., Developing a green-resilient power network and supply chain: integrating renewable and traditional energy sources in the face of disruptions. Appl Energy. 2025;377:124654. doi:10.1016/j.apenergy.2024.124654.
Jayabal, R., Towards a carbon-free society: innovations in green energy for a sustainable future. Results Eng. 2024;24:103121. doi:10.1016/j.rineng.2024.103121.
Das, T. K., Assessment of grid-integrated electric vehicle charging station based on solar-wind hybrid: a case study of coastal cities. Alex Eng J. 2024;103:288–312. doi:10.1016/j.aej.2024.05.103.
Li, W., Qian, T., Zhang, Y., Shen, Y., Wu, C., and Tang, W., Distributionally robust chance-constrained planning for regional integrated electricity-heat systems with data centers considering wind power uncertainty. Appl Energy. 2023;336:120787. doi:10.1016/j.apenergy.2023.120787.
Liu, X., Wu, Y., Li, H., and Zhou, H., Design and development of pilot plant applied to wind and light abandonment power conversion: electromagnetic heating of solid particles and steam generator. J Clean Prod. 2024;470:143313. doi:10.1016/j.jclepro.2024.143313.
Ren, Y., Yao, X., Liu, D., Qiao, R., Zhang, L., Zhang, K., et al., Optimal design of hydro-wind-PV multi-energy complementary systems considering smooth power output. Sustain Energy Technol Assess. 2022;50:101832. doi:10.1016/j.seta.2021.101832.
Wei, D., He, M., Zhang, J., Liu, D., and Mahmud, M. A., Enhancing the economic efficiency of wind-photovoltaic-hydrogen complementary power systems via optimizing capacity allocation. J Energy Storage. 2024;104:114531. doi:10.1016/j.est.2024.114531.
Koholé, Y. W., Wankouo Ngouleu, C. A., Fohagui, F. C. V., and Tchuen, G., A comprehensive comparison of battery, hydrogen, pumped-hydro and thermal energy storage technologies for hybrid renewable energy systems integration. J Energy Storage. 2024;93:112299. doi:10.1016/j.est.2024.112299.
De Mel, I. A., Demis, P., Dorneanu, B., Klymenko, O. V., Mechleri, E. D., and Arellano-Garcia, H., Global sensitivity analysis for design and operation of distributed energy systems: a two-stage approach. Sustain Energy Technol Assess. 2023;56:103064. doi:10.1016/j.seta.2023.103064.
Mbungu, N. T., Bansal, R. C., Naidoo, R. M., Siti, M. W., Ismail, A. A., Elnady, A., et al., Performance analysis of different control models for smart demand-supply energy management system. J Energy Storage. 2024;90:111809. doi:10.1016/j.est.2024.111809.
de Siqueira, L. M. S. and Peng, W., Control strategy to smooth wind power output using battery energy storage system: a review. J Energy Storage. 2021;35:102252. doi:10.1016/j.est.2021.102252.
Chang, F., Li, Y., Peng, Y., Cao, Y., Yu, H., Wang, S., et al., A dual-layer cooperative control strategy of battery energy storage units for smoothing wind power fluctuations. J Energy Storage. 2023;70:107789. doi:10.1016/j.est.2023.107789.
Lehtola, T., Solar energy and wind power supply supported by battery storage and vehicle to grid operations. Electr Power Syst Res. 2024;228:110035. doi:10.1016/j.epsr.2023.110035.
Ali, M. F., Sheikh, M. R. I., Akter, R., Islam, K. M. N., and Ferdous, A. H. M. I., Grid-connected hybrid microgrids with PV/wind/battery: sustainable energy solutions for rural education in Bangladesh. Results Eng. 2025;25:103774. doi:10.1016/j.rineng.2024.103774.
Poti, K. D., Naidoo, R. M., Mbungu, N. T., and Bansal, R. C., Optimal hybrid power dispatch through smart solar power forecasting and battery storage integration. J Energy Storage. 2024;86:111246. doi:10.1016/j.est.2024.111246.
Rayit, N. S., Chowdhury, J. I., and Balta-Ozkan, N., Techno-economic optimisation of battery storage for grid-level energy services using curtailed energy from wind. J Energy Storage. 2021;39:102641. doi:10.1016/j.est.2021.102641.
Vega-Garita, V., Alpizar-Gutierrez, V., Calderon-Obaldia, F., Núñez-Mata, O., Arguello, A., and Immonen, E., Iterative sizing methodology for photovoltaic plants coupled with battery energy storage systems to ensure smooth power output and power availability. Energy Convers Manag X. 2024;24:100716. doi:10.1016/j.ecmx.2024.100716.
Zhao, P., Gou, F., Xu, W., Shi, H., and Wang, J., Energy, exergy, economic and environmental (4E) analyses of an integrated system based on CH-CAES and electrical boiler for wind power penetration and CHP unit heat-power decoupling in wind enrichment region. Energy. 2023;263:125917. doi:10.1016/j.energy.2022.125917.
Verma, M., Ghritlahre, H. K., Chaurasiya, P. K., Ahmed, S., and Bajpai, S., Optimization of wind power plant sizing and placement by the application of multi-objective genetic algorithm (GA) in Madhya Pradesh. India Sustain Comput Inform Syst. 2021;32:100606. doi:10.1016/j.suscom.2021.100606.
Liu, A., Zhao, P., Sun, J., Xu, W., Ma, N., and Wang, J., Performance analysis of an electric-heat integrated energy system based on a CHP unit and a multi-level CCES system for better wind power penetration and load satisfaction. Appl Therm Eng. 2025;258:124644. doi:10.1016/j.applthermaleng.2024.124644.
He, Y., Hong, X., and Xian, N., Long-term scheduling strategy of hydro-wind-solar complementary system based on chaotic elite selection differential evolution algorithm with death penalty function. Eng Appl Artif Intell. 2025;142:109878. doi:10.1016/j.engappai.2024.109878.
Bade, S. O. and Tomomewo, O. S., Optimizing a hybrid wind-solar-biomass system with battery and hydrogen storage using generic algorithm-particle swarm optimization for performance assessment. Clean Energy Syst. 2024;9:100157. doi:10.1016/j.cles.2024.100157.
Alghamdi, H., Khan, T. A., Hua, L. G., Hafeez, G., Khan, I., Ullah, S., et al., A novel intelligent optimal control methodology for energy balancing of microgrids with renewable energy and storage batteries. J Energy Storage. 2024;90:111657. doi:10.1016/j.est.2024.111657.
Soheyli, S., Shafiei, M. M. H., and Mehrjoo, M., Modeling a novel CCHP system including solar and wind renewable energy resources and sizing by a CC-MOPSO algorithm. Appl Energy. 2016;184:375–95. doi:10.1016/j.apenergy.2016.09.110.
Li, J., Hao, J., Feng, Q., Sun, X., and Liu, M., Optimal selection of heterogeneous ensemble strategies of time series forecasting with multi-objective programming. Expert Syst Appl. 2021;166:114091. doi:10.1016/j.eswa.2020.114091.
Xu, X., Hu, W., Cao, D., Huang, Q., Chen, C., and Chen, Z., Optimized sizing of a standalone PV-wind-hydropower station with pumped-storage installation hybrid energy system. Renew Energy. 2020;147:1418–31. doi:10.1016/j.renene.2019.09.099.
Zhao, P., Gou, F., Xu, W., Shi, H., and Wang, J., Multi-objective optimization of a hybrid system based on combined heat and compressed air energy storage and electrical boiler for wind power penetration and heat-power decoupling purposes. J Energy Storage. 2023;58:106353. doi:10.1016/j.est.2022.106353.
Plathottam, S. J. and Salehfar, H., Unbiased economic dispatch in control areas with conventional and renewable generation sources. Electr Power Syst Res. 2015;119:313–21. doi:10.1016/j.epsr.2014.09.025.

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