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Complexity in Energy Systems Read chapter Read first chapter

2018 | OriginalPaper | Chapter

15. Operational Planning in Energy Systems: A Literature Review

Authors : Cengiz Kahraman, Sezi Çevik Onar, Başar Öztayşi, Ali Karaşan

Published in: Energy Management—Collective and Computational Intelligence with Theory and Applications

Publisher: Springer International Publishing

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Abstract

Operational planning is the process of planning and organizing the resources to achieve organization’s strategic plan. Planning the supply chain, maintenance, marketing, and production operations are the main parts of operational planning. The operational planning for energy investments is crucial since these investments are costly and the efficiency of the investments necessitates an ample planning process. Also, the type of energy source changes the operational planning need. Understanding these needs and the research gaps can enhance the efficiency of the energy systems. The objective of this chapter is to reveal the primary needs and research focuses on operation planning in energy systems. A comprehensive literature review is conducted to identify the research focuses and the gaps in operational planning in energy systems.

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Literature
Agusdinata, D. B., Lee, S., Zhao, F., & Thissen, W. (2014). Simulation modeling framework for uncovering system behaviors in the biofuels supply chain network. Simulation, 90(9), 1103–1116.CrossRef
Akoka, J., et al. (2017). Research on big data—A systematic mapping study. Computer Standards and Interfaces, 54, 105–115.CrossRef
Alippi, C., & Galperti, C. (2008). An adaptive system for opimal solar energy harvesting in wireless sensor network nodes. IEEE Transactions on Circuits and Systems I: Regular Papers, 55(6), 1742–1750.MathSciNetCrossRef
Balaman, Ş. Y., & Selim, H. (2014). A fuzzy multiobjective linear programming model for design and management of anaerobic digestion based bioenergy supply chains. Energy, 74, 928–940.CrossRef
Beeftink, H. H., Van der Heijden, R. T. J. M., & Heijnen, J. J. (1990). Maintenance requirements: energy supply from simultaneous endogenous respiration and substrate consumption. FEMS Microbiology Letters, 73(3), 203–209.CrossRef
Belyaev, L. S., Marchenko, O. V., Filippov, S. P., Solomin, S. V., Stepanova, T. B., & Kokorin, A. L. (2002). World energy and transition to sustainable development. Boston: Kluwer.CrossRef
Ben-Daya, M., Ait-Kadi, D., Duffuaa, S. O., Knezevic, J., & Raouf, A. (2009). Handbook of maintenance management and engineering (Vol. 7). London: Springer.CrossRef
Bergonzini, C., et al. (2009). Algorithms for harvested energy prediction in batteryless wireless sensor networks. In 3rd International Workshop on Advances in Sensors and Interfaces, IWASI 2009.
Bodansky, D. (2004). Nuclear energy: Principles practices and prospects. Oxford: Springer.
Cambero, C., et al. (2015). Strategic optimization of forest residues to bioenergy and biofuel supply chain. International Journal of Energy Research, 39(4), 439–452.CrossRef
Castillo-Villar, K. K. (2014). Metaheuristic algorithms applied to bioenergy supply chain problems: theory, review, challenges, and future. Energies, 7(11), 7640–7672.CrossRef
Ceci, M., et al. (2015). Big data techniques for supporting accurate predictions of energy production from renewable sources. In ACM International Conference Proceeding Series.
Chapman, S. N. (2006). The fundamentals of production planning and control. Prentice Hall.
Chen, S., et al. (2012). A simple asymptotically optimal energy allocation and routing scheme in rechargeable sensor networks. In Proceedings—IEEE INFOCOM.
Chopra, S., & Meindl, P. (2007). Supply chain management. Strategy, planning & operation. Das summa summarum des management (pp. 265–275).
Cristaldi, L., Faifer, M., Rossi, M., & Ponci, F. (2011). Monitoring of a PV system: The role of the panel model. In Applied Measurements for Power Systems (s. 90–95). IEEE.
Cuadra, L., Salcedo-Sanz, S., Nieto-Borge, J. C., Alexandre, E., & Rodríguez, G. (2016). Computational intelligence in wave energy: Comprehensive review and case study. Renewable and Sustainable Energy Reviews, 58, 1223–1246.CrossRef
Cui, C., Li, X., Sui, H., & Sun, J. (2017). Optimization of coal-based methanol distillation scheme using process superstructure method to maximize energy efficiency. Energy, 119, 110–120.CrossRef
Cunico, M. C., Flores, J. R., & Vecchietti, A. (2017). Investment in the energy sector: An optimization model that contemplates several uncertain parameters. Energy, 138, 831–845. (1 Nov 2017).CrossRef
Daneshi-Far, Z., et al. (2010). Review of failures and condition monitoring in wind turbine generators. In 19th International Conference on Electrical Machines, ICEM 2010.
Daut, M. A. M., Hassan, M. Y., Abdullah, H., Rahman, H. A., Abdullahab, M. P., & Hussin, F. (2017). Building electrical energy consumption forecasting analysis using conventional and artificial intelligence methods: A review. Renewable and Sustainable Energy Reviews, 70, 1108–1118.CrossRef
Dehghani, E., Jabalameli, M. S., & Jabbarzadeh, A. (2018). Robust design and optimization of solar photovoltaic supply chain in an uncertain environment. Energy, 142, 139–156.CrossRef
Demirel, Y. (2012). Green energy and technology. Berlin: Springer.
Dondi, D., et al. (2008). Modeling and optimization of a solar energy harvester system for self-powered wireless sensor networks. IEEE Transactions on Industrial Electronics, 55(7), 2759–2766.CrossRef
Drummond, J., & Hanna, F. (2001). Selling power: Marketing energy under deregulation.
Elia, J. A., et al. (2011). Optimal energy supply network determination and life cycle analysis for hybrid coal, biomass, and natural gas to liquid (CBGTL) plants using carbon-based hydrogen production. Computers & Chemical Engineering, 35(8), 1399–1430.CrossRef
Felzien, D., et al. (2003). IT requirements for market participant interaction with ISOs/RTOs. IEEE Transactions on Power Systems, 18(2), 517–519.CrossRef
Ferrari, S., Lazzaroni, M., Piuri, V., Salman, A., Cristaldi, L., Faifer, M., et al. (2016). Solar panel modelling through computational intelligence techniques. Measurement, 93, 572–580.CrossRef
Flodén, J., & Williamsson, J. (2016). Business models for sustainable biofuel transport: The potential for intermodal transport. Journal of Cleaner Production, 113, 426–437.CrossRef
Frackowiak, E., & Beguin, F. (2001). Carbon materials for the electrochemical storage of energy in capacitors. Carbon, 39(6), 937–950.CrossRef
Gabaldón, A., et al. (2008). Development of a methodology for improving the effectiveness of customer response policies through electricity-price patterns. In IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES.
García-Valverde, R., et al. (2010). Life cycle analysis of organic photovoltaic technologies. Progress in Photovoltaics: Research and Applications, 18(7), 535–538.CrossRef
Ghaffari, R., & Venkatesh, B. (2015). Network constrained model for options based reserve procurement by wind generators using binomial tree. Renewable Energy, 80, 348–358.CrossRef
Gossling, S., et al. (2005). A target group-specific approach to “green” power retailing: Students as consumers of renewable energy. Renewable and Sustainable Energy Reviews, 9(1), 69–83.CrossRef
Gupta, P. K. (1999). Renewable energy sources-a longway to go in India. Renewable Energy, 16(1–4), 1216–1219.CrossRef
Gupta, S. C., et al. (2007). Optimal sizing of solar-wind hybrid system. In IET Seminar Digest.
Hashemian, H. M. (2011). On-line monitoring applications in nuclear power plants. Progress in Nuclear Energy, 53(2), 167–181.CrossRef
Hashemian, H. M., & Bean, W. C. (2011). State-of-the-art predictive maintenance techniques. IEEE Transactions on Instrumentation and Measurement, 60(10), 3480–3492.CrossRef
Hashemian, H. M., et al. (2011). Wireless sensor applications in nuclear power plants. Nuclear Technology, 173(1), 8–16.CrossRef
Hu, M.-C., Lu, S.-Y., Chen, Y.-H. (2016). Stochastic programming and market equilibrium analysis of microgrids energy management systems. Energy, 113, 662–670, ISSN 0360–5442.
Hugo, A., Rutter, P., Pistikopoulos, E. N., Amorelli, A., & Zoia, G. (2005). Hydrogen infrastructure strategic planning using multi-objective optimization. International Journal of Hydrogen Energy, 30(15), 1523–1534.CrossRef
Iakovou, E., Karagiannidis, A., Vlachos, D., Toka, A., & Malamakis, A. (2010). Waste biomass-to-energy supply chain management: A critical synthesis. Waste Management, 30(10), 1860–1870.CrossRef
Irizarry, F., & Seemer, R. H. (1986). Human resource planning: A nuclear application. In Proceedings—Fall Industrial Engineering Conference (Institute of Industrial Engineers).
Ismail, M., & Sanavullah, M. Y. (2008). Security topology in wireless sensor networks with routing optimisation. In Proceedings of the 4th International Conference on Wireless Communication and Sensor Networks, WCSN 2008.
Jauhari, V., & Dutta, K. (2009). Services: Marketing, operations, and managment. Oxford University Press.
Jha, S. K., Bilalovic, J., Jha, A., Patel, N., & Zhang, H. (2017). Renewable energy: Present research and future scope of artificial intelligence. Renewable and Sustainable Energy Reviews, 77, 297–317.CrossRef
Kayakutlu, G., & Mercier-Laurent, E. (2017). Intelligence for Energy. In Intelligence in energy (pp. 79–116).
Kebede, K. Y., et al. (2014). After-sales service and local presence: Key factors for solar energy innovations diffusion in developing countries. In PICMET 2014—Portland International Center for Management of Engineering and Technology, Proceedings: Infrastructure and Service Integration.
Kejariwal, A., & Orsini, F. (2016). On the definition of real-time: Applications and systems. In Proceedings—15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 10th IEEE International Conference on Big Data Science and Engineering and 14th IEEE International Symposium on Parallel and Distributed Processing with Applications, IEEE TrustCom/BigDataSE/ISPA 2016.
Kwon, S., Won, W., & Kim, J. (2016). A superstructure model of an isolated power supply system using renewable energy: Development and application to Jeju Island, Korea. Renewable Energy, 97, 177–188.CrossRef
Lei, X., & Sandborn, P. A. (2018). Maintenance scheduling based on remaining useful life predictions for wind farms managed using power purchase agreements. Renewable Energy, 116, 188–198.CrossRef
Lin, K., & Holbert, K. E. (2009). Blockage diagnostics for nuclear power plant pressure transmitter sensing lines. Nuclear Engineering and Design, 239(2), 365–372.CrossRef
Liu, P., Pistikopoulos, E. N., & Li, Z. (2009a). A mixed-integer optimization approach for polygeneration energy systems design. Computers & Chemical Engineering, 33(3), 759–768.CrossRef
Liu, P., Pistikopoulos, E. N., & Li, Z. (2009b). A multi-objective optimization approach to polygeneration energy systems design. AIChE Journal, 56(5), 1218–1234.CrossRef
Liu, P., Psitikopoulos, N. E., & Li, Z. (2010). Energy systems engineering: methodologies and applications. Frontiers in Energy, 4(2), 131–142.
Lusby, R., et al. (2013). A solution approach based on Benders decomposition for the preventive maintenance scheduling problem of a stochastic large-scale energy system. Journal of Scheduling, 16(6), 605–628.MathSciNetCrossRefMATH
Martinot, E., et al. (2001). World Bank/GEF solar home system projects: Experiences and lessons learned 1993–2000. Renewable and Sustainable Energy Reviews, 5(1), 39–57.CrossRef
Meadows, J., et al. (2014). The potential supply of biomass for energy from Hardwood Plantations in the Sunshine Coast Council Region of South-East Queensland, Australia. Small-scale Forestry, 13(4), 461–481.CrossRef
Medidi, M., & Zhou, Y. (2006). Maintaining an energy-efficient bluetooth scatternet. In Performance, Computing, and Communications Conference (s. 8). IEEE.
Mirabella, N., et al. (2013). Life cycle assessment of bio-based products: A disposable diaper case study. International Journal of Life Cycle Assessment, 18(5), 1036–1047.CrossRef
Mohamed, M. A., Eltamaly, A. M., & Alolah, A. I. (2017). Swarm intelligence-based optimization of grid-dependent hybrid renewable energy systems. Renewable and Sustainable Energy Reviews, 77, 515–524.CrossRef
Mont, O. K. (2002). Clarifying the concept of product–service system. Journal of Cleaner Production, 10(3), 237–245.CrossRef
Mueller, T. S. (2017). Consumer perceptions of electric utilities: Insights from the center for Analytics Research & Education Project in the United States. Energy Research and Social Science, 26, 34–39.CrossRef
Murilo, P. S., Alexandre, S., & Davi, M. V. (2017). On the solution variability reduction of stochastic dual dynamic programming applied to energy planning. European Journal of Operational Research, 258(2), 743–760.MathSciNetCrossRef
Ni, M., Leung, M. K., Sumathy, K., & Leung, D. Y. (2006). Potential of renewable hydrogen production for energy supply in Hong Kong. International Journal of Hydrogen Energy, 31(10), 1401–1412.CrossRef
Paulo, H., et al. (2015). Supply chain optimization of residual forestry biomass for bioenergy production: The case study of Portugal. Biomass and Bioenergy, 83, 245–256.CrossRef
Pereira, C. M. N. A., et al. (2010). A particle swarm optimization (PSO) approach for non-periodic preventive maintenance scheduling programming. Progress in Nuclear Energy, 52(8), 710–714.CrossRef
Phillips, B. R., & Middleton, R. S. (2012). SimWIND: A geospatial infrastructure model for optimizing wind power generation and transmission. Energy Policy, 43, 291–302.CrossRef
Presencia, C. E., & Shafiee, M. (2017). Risk analysis of maintenance ship collisions with offshore wind turbines. International Journal of Sustainable Energy, 1–21.
Richard, T. L. (2010). Challenges in scaling up biofuels infrastructure. Science, 329(5993), 793–796.CrossRef
Rodriguez, C. P., & Anders, G. J. (2004). Energy price forecasting in the Ontario competitive power system market. IEEE Transactions on Power Systems, 19(1), 366–374.CrossRef
Rogers, J. H. (1999). Learning reliability lessons from PV leasing. Progress in Photovoltaics: Research and Applications, 7(3), 235–241.CrossRef
Rulkens, W. (2007). Sewage sludge as a biomass resource for the production of energy: Overview and assessment of the various options. Energy & Fuels, 22(1), 9–15.CrossRef
Sarja, J., & Halonen, V. (2012). Case study of wind turbine sourcing: Manufacturer selection criteria. In 2012 IEEE Electrical Power and Energy Conference, EPEC 2012.
Schaffner, D., Ohnmacht, T., Weibel, C., & Mahrer, M. (2017). Moving into energy-efficient homes: A dynamic approach to understanding residents’ decision-making. Building and Environment, 123, 211–222.CrossRef
Shafiee, M. (2015). Maintenance logistics organization for offshore wind energy: Current progress and future perspectives. Renewable Energy, 77(1), 182–193.CrossRef
Sherrard, J. R., & Horner, T. A. (2007). Developing a quality entry level technician workforce for the twenty-first century commercial nuclear industry. In CONTE 2007: Conference on Nuclear Training and Education.
Sikkema, R., et al. (2014). Legal harvesting, sustainable sourcing and cascaded use of wood for bioenergy: Their coverage through existing certification frameworks for sustainable forest management. Forests, 5(9), 2163–2211.CrossRef
Tascikaraoglu, A., et al. (2014). An adaptive load dispatching and forecasting strategy for a virtual power plant including renewable energy conversion units. Applied Energy, 119, 445–453.CrossRef
Teeuwsen, S. P., Erlich, I., & El-Sharkawi, M. A. (2005). Fast eigenvalue assessment for large interconnected powers systems. In Power Engineering Society General Meeting (s. 1727–1733). IEEE.
Thiaw, L., Sow, G., & Fall, S. (2014). Application of neural networks technique in renewable energy systems. In First International Conference on Systems Informatics, Modelling and Simulation, IEEE Computer Society, Sheffield, United Kingdom, 29 April–1 May 2014.
Tryfonidou, R., & Wagner, H. J. (2004). Multi-megawatt wind turbines for offshore use: Aspects of Life Cycle Assessment. International Journal of Global Energy Issues, 21(3), 255–262.CrossRef
Tsoutsos, T. D. (2002). Marketing solar thermal technologies: Strategies in Europe, experience in Greece. Renewable Energy, 26(1), 33–46.CrossRef
Verdú, S. V., et al. (2006). Classification, filtering, and identification of electrical customer load patterns through the use of self-organizing maps. IEEE Transactions on Power Systems, 21(4), 1672–1682.CrossRef
Voigt, T., et al. (2003). Utilizing solar power in wireless sensor networks. In Proceedings—Conference on Local Computer Networks, LCN.
Voll, P., Klaffke, C., Hennen, M., & Bardow, A. (2013). Automated superstructure-based synthesis and optimization of distributed energy supply systems. Energy, 50, 374–388.CrossRef
Wang, S., & Song, M. (2017). Influences of reverse outsourcing on green technological progress from the perspective of a global supply chain. Science of the Total Environment, 595, 201–208.CrossRef
Wiggelinkhuizen, E., et al. (2008). Assessment of condition monitoring techniques for offshore wind farms. Journal of Solar Energy Engineering, Transactions of the ASME, 130(3), 0310041–0310049.CrossRef
Wirl, F. (1989). Analytics of demand-side conservation programs. Energy systems and policy, 13(4), 285–300.
Xie, L., & Ilić, M. D. (2008). Model predictive dispatch in electric energy systems with intermittent resources. In Conference Proceedings—IEEE International Conference on Systems, Man and Cybernetics.
Xie, L., & Ilić, M. D. (2009). Model predictive economic/environmental dispatch of power systems with intermittent resources. In 2009 IEEE Power and Energy Society General Meeting, PES ‘09.
Yang, R., et al. (2015). An enhanced preventive maintenance optimization model based on a three-stage failure process. In Science and Technology of Nuclear Installations 2015.
Yang, W., et al. (2014). Wind turbine condition monitoring: Technical and commercial challenges. Wind Energy, 17(5), 673–693.CrossRef
Yeomans, H., & Grossmann, I. E. (1999). A systematic modeling framework of superstructure optimization in process synthesis. Computers & Chemical Engineering, 23(6), 709–731.CrossRef
Yokoyama, R., Nakamura, R., & Wakui, T. (2017). Performance comparison of energy supply systems under uncertain energy demands based on a mixed-integer linear model. In Energy, 137, 878–887.CrossRef
Zahraee, S. M., Assadi, M. K., & Saidur, R. (2016). Application of artificial intelligence methods for hybrid energy system optimization. Renewable and Sustainable Energy Reviews, 66, 617–630.CrossRef
Zéphyr, L., Lang, P., Lamond, B. F., & Côté, P. (2017). Approximate stochastic dynamic programming for hydroelectric production planning. European Journal of Operational Research, 262(2), 586–601.MathSciNetCrossRefMATH
Zhang, C., et al. (2017). A spare parts demand prediction method for wind farm based on periodic maintenance strategy. In American Society of Mechanical Engineers, Power Division (Publication) POWER.
Zhang, H., Liang, Y., Liao, Q., Wu, M., & Yan, X. (2017). A hybrid computational approach for detailed scheduling of products in a pipeline with multiple pump stations. Energy, 119, 612–628.CrossRef
Zhou, W., Xia, X., & Wang, B. (2015). Improving building energy efficiency by multiobjective neighborhood field optimization. Energy and Buildings, 87, 45–56.
Zhu, J., et al. (2014). Survey of condition indicators for condition monitoring systems. In PHM 2014—Proceedings of the Annual Conference of the Prognostics and Health Management Society 2014.
Zorić, J., & Hrovatin, N. (2012). Household willingness to pay for green electricity in Slovenia. Energy Policy, 47, 180–187.CrossRef
Metadata
Title
Operational Planning in Energy Systems: A Literature Review
Authors
Cengiz Kahraman
Sezi Çevik Onar
Başar Öztayşi
Ali Karaşan
Copyright Year
2018
Book
Energy Management—Collective and Computational Intelligence with Theory and Applications

Print ISBN: 978-3-319-75689-9

Electronic ISBN: 978-3-319-75690-5

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-75690-5_15

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