{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T13:39:39Z","timestamp":1765546779684,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T00:00:00Z","timestamp":1625616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>This work focuses on energy management for a system operated by multiple energy sources which include batteries, super capacitors, a hydrogen fuel cell, and a photovoltaic cell. The overall objective is to minimize the power consumption from all sources needed to satisfy the system\u2019s power demand by optimizing the switching between the different energy sources. A dynamic mathematical model representing the energy sources is developed taking into account the different constraints on the system, i.e., primarily the state-of-charge of the battery and the super capacitors. In addition to the model, a heuristic approach is developed and compared with the mathematical model. Both approaches were tested on a multi-energy source ground robot as a prototype. The novelty of this work is that the scheduling of an energy system consisting of four different types of sources is compared by performing analysis via dynamic programming, and a heuristic approach. The results generated using both methods are analyzed and compared to a standard mode of operation. The comparison validated that the proposed approaches minimize the average power consumption across all sources. The dynamic modeling approach performs well in terms of optimization and provided a superior switching sequence, while the heuristic approach offers the definite advantages in terms of ease of implementation and simple computation requirements. Additionally, the switching sequence provided by the dynamic approach was able to meet the power demand for all simulations performed and showed that the average power consumption across all sources is minimized.<\/jats:p>","DOI":"10.3390\/a14070206","type":"journal-article","created":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T12:31:25Z","timestamp":1625661085000},"page":"206","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Energy Management of a Multi-Source Power System"],"prefix":"10.3390","volume":"14","author":[{"given":"Omar","family":"Salah","sequence":"first","affiliation":[{"name":"Engineering Systems Management Program, American University of Sharjah, Sharjah 26666, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0214-7052","authenticated-orcid":false,"given":"Abdulrahim","family":"Shamayleh","sequence":"additional","affiliation":[{"name":"Engineering Systems Management Program, American University of Sharjah, Sharjah 26666, United Arab Emirates"},{"name":"Department of Industrial Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7941-780X","authenticated-orcid":false,"given":"Shayok","family":"Mukhopadhyay","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,7]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1869","DOI":"10.1109\/TITS.2014.2309674","article-title":"Supervisory Power Management Control Algorithms for Hybrid Electric Vehicles: A Survey","volume":"15","author":"Malikopoulos","year":"2014","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1109\/TMECH.2014.2336264","article-title":"Optimal Dimensioning and Power Management of a Fuel Cell\/Battery Hybrid Bus via Convex Programming","volume":"20","author":"Hu","year":"2015","journal-title":"IEEE\/ASME Trans. Mechatronics"},{"key":"ref_3","first-page":"779","article-title":"Improving Multiple Source Power Management Using State Flow Approach","volume":"22","author":"Naamane","year":"2013","journal-title":"Blockchain Technol. Innov. Bus. Process."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Keller, S., Christmann, K., Gonzalez, M.S.-A., and Heuer, A. (2017, January 14\u201317). A Modular Fuel Cell Battery Hybrid Propulsion System for Powering Small Utility Vehicles. Proceedings of the 2017 IEEE Vehicle Power and Propulsion Conference (VPPC), Belfort, France.","DOI":"10.1109\/VPPC.2017.8330969"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1968","DOI":"10.1109\/TIE.2019.2898606","article-title":"Distributed Cooperative Control of Multiple Hybrid Energy Storage Systems in a DC Microgrid Using Consensus Protocol","volume":"67","author":"Chen","year":"2019","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Su\u00e1rez- Suarez-Velazquez, G., Mejia-Ruiz, G.E., and Garcia-Vite, P.M. (2020, January 4\u20136). Control and Grid Connection of Fuel Cell Power System. Proceedings of the 2020 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), Ixtapa, M\u00e9xico.","DOI":"10.1109\/ROPEC50909.2020.9258729"},{"key":"ref_7","first-page":"374","article-title":"Optimization of a truck-drone in tandem delivery network using k-means and genetic algorithm","volume":"9","author":"Ferrandez","year":"2016","journal-title":"J. Ind. Eng. Manag."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Masjosthusmann, C., Kohler, U., Decius, N., and Buker, U. (2012, January 9\u201312). A vehicle energy management system for a Battery Electric Vehicle. Proceedings of the 2012 IEEE Vehicle Power and Propulsion Conference (VPPC), Seoul, Korea.","DOI":"10.1109\/VPPC.2012.6422676"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2454","DOI":"10.1161\/CIRCULATIONAHA.116.026318","article-title":"Optimizing a Drone Network to Deliver Automated External Defibrillators","volume":"135","author":"Boutilier","year":"2017","journal-title":"Circulation"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Lee, J. (2017, January 24\u201327). Optimization of a modular drone delivery system. Proceedings of the 2017 Annual IEEE International Systems Conference (SysCon), Montreal, QC, Canada.","DOI":"10.1109\/SYSCON.2017.7934790"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Banerjee, A., and Roychoudhury, A. (2017, January 22\u201323). Future of Mobile Software for Smartphones and Drones: Energy and Performance. Proceedings of the 2017 IEEE\/ACM 4th International Conference on Mobile Software Engineering and Systems (MOBILESoft), Buenos Aires, Argentina.","DOI":"10.1109\/MOBILESoft.2017.1"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1109\/TII.2013.2245140","article-title":"Predictive Control for the Energy Management of a Fuel-Cell\u2013Battery\u2013Supercapacitor Tramway","volume":"10","author":"Torreglosa","year":"2014","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2672","DOI":"10.1016\/j.egypro.2017.03.773","article-title":"Plug-In Hybrid Electric Bus Energy Management Based on Stochastic Model Predictive Control","volume":"105","author":"Xie","year":"2017","journal-title":"Energy Procedia"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.ifacol.2016.08.041","article-title":"Convex Optimization for Energy Management of Parallel Hybrid Electric Vehicles","volume":"49","author":"Colin","year":"2016","journal-title":"IFAC-PapersOnLine"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3223","DOI":"10.1109\/TIE.2014.2376883","article-title":"A Real-Time Energy Management Architecture for Multisource Electric Vehicles","volume":"62","author":"Trovao","year":"2015","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"5540","DOI":"10.1109\/TVT.2016.2636282","article-title":"Energy- and Power-Split Management of Dual Energy Storage System for a Three-Wheel Electric Vehicle","volume":"66","author":"Trovao","year":"2017","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zhou, D., Gao, F., Ravey, A., Al-Durra, A., and Simoes, M.G. (2017, January 22\u201324). Online energy management strategy of fuel cell hybrid electric vehicles based on time series prediction. Proceedings of the 2017 IEEE Transportation Electrification Conference and Expo (ITEC), Chicago, IL, USA.","DOI":"10.1109\/ITEC.2017.7993256"},{"key":"ref_18","first-page":"1","article-title":"Online Energy Management of Plug-In Hybrid Electric Vehicles for Prolongation of All-Electric Range Based on Dynamic Programming","volume":"2015","author":"Chen","year":"2015","journal-title":"Math. Probl. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Qin, F., Li, W., Hu, Y., and Xu, G. (2018). An Online Energy Management Control for Hybrid Electric Vehicles Based on Neuro-Dynamic Programming. Algorithms, 11.","DOI":"10.3390\/a11030033"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.jprocont.2020.12.005","article-title":"Robust online scheduling for optimal short-term operation of cascaded hydropower systems under uncertainty","volume":"98","author":"Mathur","year":"2021","journal-title":"J. Process. Control."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Park, S., Zhang, L., and Chakraborty, S. (2017, January 24\u201326). Battery assignment and scheduling for drone delivery businesses. Proceedings of the 2017 IEEE\/ACM International Symposium on Low Power Electronics and Design (ISLPED), Taipei, Taiwan.","DOI":"10.1109\/ISLPED.2017.8009165"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.omega.2016.04.005","article-title":"A linear programming based heuristic algorithm for charge and discharge scheduling of electric vehicles in a building energy management system","volume":"67","author":"Umetani","year":"2017","journal-title":"Omega"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1016\/j.jprocont.2016.08.011","article-title":"An optimization model design for energy systems planning andmanagement under considering air pollution control in TangshanCity, China","volume":"47","author":"Zhen","year":"2016","journal-title":"J. Process. Control"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.jprocont.2017.08.015","article-title":"A Sequential Linear Programming algorithm for economicoptimization of Hybrid Renewable Energy Systems","volume":"74","author":"Vaccari","year":"2019","journal-title":"J. Process. Control"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"504","DOI":"10.1109\/TEC.2006.874229","article-title":"Accurate Electrical Battery Model Capable of Predicting Runtime and I\u2013V Performance","volume":"21","author":"Chen","year":"2006","journal-title":"IEEE Trans. Energy Convers."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3882","DOI":"10.1109\/TVT.2009.2027909","article-title":"Influence of Battery\/Ultracapacitor Energy-Storage Sizing on Battery Lifetime in a Fuel Cell Hybrid Electric Vehicle","volume":"58","author":"Schaltz","year":"2009","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"4131","DOI":"10.1007\/s00500-019-04180-3","article-title":"Minimizing the state of health degradation of Li-ion batteries onboard low earth orbit satellites","volume":"24","author":"Lami","year":"2019","journal-title":"Soft Comput."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3168","DOI":"10.1109\/TVT.2009.2014684","article-title":"Fuel-Cell Hybrid Powertrain: Toward Minimization of Hydrogen Consumption","volume":"58","author":"Bernard","year":"2009","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Pukrushpan, J. (2003). Modeling and Control of Fuel Cell Systems and Fuel Processors, University of Michigan.","DOI":"10.1109\/ACC.2002.1025268"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"829","DOI":"10.1109\/7.869502","article-title":"Classical equivalent circuit parameters for a double-layer capacitor","volume":"36","author":"Spyker","year":"2000","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1109\/TIE.2009.2032195","article-title":"Power-Electronics-Based Solutions for Plug-in Hybrid Electric Vehicle Energy Storage and Management Systems","volume":"57","author":"Amjadi","year":"2010","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Saaty, T. (1980). The Analytic Hierarchy Process, McGraw-Hill.","DOI":"10.21236\/ADA214804"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.jpowsour.2003.12.016","article-title":"A cost comparison of fuel-cell and battery electric vehicles","volume":"130","author":"Eaves","year":"2004","journal-title":"J. Power Sources"},{"key":"ref_34","first-page":"77","article-title":"Fuel Cell Comparison to Alternate Technologies","volume":"1","author":"Kunze","year":"2012","journal-title":"Fuel Cells"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Berckmans, G., Messagie, M., Smekens, J., Omar, N., Vanhaverbeke, L., and Van Mierlo, J. (2017). Cost Projection of State of the Art Lithium-Ion Batteries for Electric Vehicles Up to 2030. Energies, 10.","DOI":"10.3390\/en10091314"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1109\/TPEL.2011.2164581","article-title":"Polynomial Control Method of DC\/DC Converters for DC-Bus Voltage and Currents Management\u2014Battery and Supercapacitors","volume":"27","author":"Camara","year":"2012","journal-title":"IEEE Trans. Power Electron."}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/14\/7\/206\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:27:11Z","timestamp":1760164031000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/14\/7\/206"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,7]]},"references-count":36,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["a14070206"],"URL":"https:\/\/doi.org\/10.3390\/a14070206","relation":{},"ISSN":["1999-4893"],"issn-type":[{"type":"electronic","value":"1999-4893"}],"subject":[],"published":{"date-parts":[[2021,7,7]]}}}