The management of distributed energy resources for national security

• Authors: Krzysztof Waśniewski

Abstracts

EN

This article investigates the possibilities of using distributed energy resources (DER) to increase the resilience of national energy systems and national security, including the case of war. A review of literature is conducted, regarding the management of DER systems. Conclusions focus on the specificities of managing such systems for national security, namely: a) the importance of complexity theory as basic framework for strategic planning in DER systems b) the management of risks relative to disruptions in supply chains and c) the role to be played by financial instruments and markets.

Keywords

EN

energy security; distributed energy resources (DER); national security; Energy resilience

• Publisher: Krakowska Akademia im. Andrzeja Frycza Modrzewskiego
• Journal: Bezpieczeństwo. Teoria i Praktyka
• Year: 2022
• Volume: XLVII
• Issue: 2
• Pages: 39-48

Dates

published

2022

Contributors

author

Krzysztof Waśniewski

• Andrzej Frycz Modrzewski Krakow University

References

• Anderson P.C., Meyer A., Complexity theory and process organization studies, [in:] SAGE Handbook of Process Organization Studies, eds. A. Langley, H. Tsoukas, Thousand Oaks, CA: SAGE Publications Ltd, 2016, pp. 127–143.
• Anderson P.W., “More is different: Broken symmetry and the nature of the hierarchical structure of science”, Science, vol. 177, no. 4047, 1972, pp. 393–396.
• Bompard E., Carpignano A., Erriquez M. et al., “National energy security assessment in a geopolitical perspective”, Energy, vol. 130, 2017, pp. 144–154, https://doi.org/10.1016/j.energy.2017.04.108.
• Colby E.A., The Strategy of Denial: American Defense in An Age of Great Power Conflict, New Haven: Yale University Press, 2021.
• Dannreuther R., Energy security, Hoboken, NJ: John Wiley & Sons, 2017.
• Di Caprio D., Ebrahimnejad A., Alrezaamiri H., Santos-Arteaga F.J., “A novel ant colony algorithm for solving shortest path problems with fuzzy arc weights”, Alexandria Engineering Journal, vol. 61, no. 5, 2021, pp. 3403–3415, https://doi.org/10.1016/j.aej.2021.08.058.
• Feng Y., Ryan S.M., “Scenario construction and reduction applied to stochastic power generation expansion planning”, Computers & Operations Research, vol. 40, no. 1, 2013, pp. 9–23, http://dx.doi.org/10.1016/j.cor.2012.05.005.
• Feng L., Zhang X., Li X. et al., “Performance analysis of hybrid energy storage integrated with distributed renewable energy”, Energy Reports, vol. 8, 2022, pp. 1829–1838, https://doi.org/10.1016/j.egyr.2021.12.078.
• Flores-Quiroz A., Strunz K., “A distributed computing framework for multi-stage stochastic planning of renewable power systems with energy storage as flexibility option”, Applied Energy, vol. 291, 2021, 116736, https://doi.org/10.1016/j.apenergy.2021.116736.
• Gupta A., Srivastava S., “Comparative analysis of ant colony and particle swarm optimization algorithms for distance optimization”, Procedia Computer Science, vol. 173, 2020, pp. 245–253, https://doi.org/10.1016/j.procs.2020.06.029.
• Haider R., D’Achiardi D., Venkataramanan V., “Reinventing the utility for distributed energy resources: A proposal for retail electricity markets”, Advances in Applied Energy, vol. 2, 2021,100026, https://doi.org/10.1016/j.adapen.2021.100026.
• Hou P., Yang G., Hu J. et al., “A distributed transactive energy mechanism for integrating PV and storage prosumers in market operation”, Engineering, vol. 12, 2022, pp. 171–182, https://doi.org/10.1016/j.eng.2022.03.001.
• Howell S., Rezgui Y., Hippolyte J.-L. et al., “Towards the next generation of smart grids: Semantic and holonic multi-agent management of distributed energy resources”, Renewable and Sustainable Energy Reviews, vol. 77, 2017, pp. 193–214, http://dx.doi.org/10.1016/j.rser.2017.03.107.
• Jin S., Ryan S.M., Watson J.-P., Woodruff D.L., “Modeling and solving a large-scale generation expansion planning problem under uncertainty”, Energy Systems, vol. 2, no. 3, 2011, pp. 209–242, http://dx.doi.org/10.1007/s12667- 011-0042-9.
• Kivimaa P., Sivonen M.H., “Interplay between low-carbon energy transitions and national security: An analysis of policy integration and coherence in Estonia, Finland and Scotland”, Energy
• Research & Social Science, vol. 75, 2021, 102024, https://doi.org/10.1016/j.erss.2021.102024.
• Ladyman J., Wiesner K., What Is a Complex System?, New Haven, CT: Yale University Press, 2020,Kindle Edition.
• Levchenko V., Boiko A., Savchenko T. et al., “State regulation of the economic security by applying the innovative approach to its assessment”, Marketing and Management of Innovations, vol. 10,no. 4, 2019, pp. 364–372, http://doi.org/10.21272/mmi.2019.4-28.
• López González D.M., Garcia Rendon J., “Opportunities and challenges of mainstreaming distributed energy resources towards the transition to more efficient and resilient energy markets”, Renewable and Sustainable Energy Reviews, vol. 157, 2022, 112018, https://doi.org/10.1016/j.rser.2021.112018.
• Maschio D.M., Duarte B., Lazzaretti A.E. et al., “An event-driven approach for resources planning in distributed power generation systems”, International Journal of Electrical Power & Energy Systems, vol. 137, 2022, 107768, https://doi.org/10.1016/j.ijepes.2021.107768.
• Mazzucchi N., Énergie: Ressources, Technologies et Enjeux de Pouvoir, Paris: Armand Colin, 2017.
• McIlwaine N., Foley A.M., Morrow D.J. et al., “A state-of-the-art techno-economic review of distributed and embedded energy storage for energy systems”, Energy, vol. 229, 2021, 120461, https://doi.org/10.1016/j.energy.2021.120461.
• Pazouki S., Naderi E., Asrari A., “A remedial action framework against cyberattacks targeting energy hubs integrated with distributed energy resources”, Applied Energy, vol. 304, 2021, 117895,https://doi.org/10.1016/j.apenergy.2021.117895.
• Pu X., Wang Z.L., “Self-charging power system for distributed energy: Beyond the energy storage unit”, Chemical Science, vol. 12, no. 1, 2021, pp. 34–49, https://doi.org/10.1039/D0SC05145D.
• Sidnell T., Clarke F., Dorneanu B. et al., “Optimal design and operation of distributed energy resources systems for residential neighbourhoods”, Smart Energy, vol. 4, 2021, 100049, https://doi.org/10.1016/j.segy.2021.100049.
• Sikorski T., Jasiński M., Ropuszyńska-Surma E., “A case study on distributed energy resources and energy-storage systems in a virtual power plant concept: Technical aspects”, Energies, vol. 13, no. 12, 2020, 3086, https://doi.org/10.3390/en13123086.
• Silva C., Faria P., Fernandes A., Vale Z., “Clustering distributed Energy Storage units for the aggregation of optimized local solar energy”, Energy Reports, vol. 8, suppl. 3, 2022, pp. 405–410, https://doi.org/10.1016/j.egyr.2022.01.043.
• Simon H.A., “The architecture of complexity”, Proceedings of the American Philosophical Society, vol. 106, no. 6, 1962, pp. 467–482.
• Sofyalıoğlu Ç., Kartal B., “The Selection of Global Supply Chain Risk Management Strategies by Using Fuzzy Analytical Hierarchy Process – A Case from Turkey”, Procedia – Social and Behavioral Sciences, vol. 58, 2012, pp. 1448–1457, https://doi.org/10.1016/j.sbspro.2012.09.1131.
• Tikka V., Mashlakov A., Kulmala A. et al., “Integrated business platform of distributed energy resources – Case Finland”, Energy Procedia, vol. 158, 2019, pp. 6637–6644, https://doi.org/10.1016/j.egypro.2019.01.041.
• Touzani S., Prakash A.K., Wang Z. et al., “Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency”, Applied Energy, vol. 304, 2021, 117733, https://doi.org/10.1016/j.apenergy.2021.117733.
• The Virtual Utility: Accounting, technology & competitive aspects of the emerging industry, eds. S. Awerbuch, A. Preston, Boston, MA Springer, 1997.
• Wang Q., Zhou K., “A framework for evaluating global national energy security”, Applied Energy, vol. 188, 2017, pp. 19–31, https://doi.org/10.1016/j.apenergy.2016.11.116.
• Wasiak I., Szypowski M., Kelm P. et al., “Innovative energy management system for low-voltage networks with distributed generation based on prosumers’ active participation”, Applied Energy, vol. 312, 2022, 118705, https://doi.org/10.1016/j.apenergy.2022.118705.
• White S., Youssefi S., Energy Storage Basics: A Study Guide for Energy Practitioners, independently published, 2020, Kindle Edition.
• Wu R., Sansavini G., “Energy trilemma in active distribution network design: Balancing affordability, sustainability and security in optimization-based decision-making”, Applied Energy, vol. 304, 2021, 117891, https://doi.org/10.1016/j.apenergy.2021.117891.
• Xia Y., Xu Q., Qian H., Cai L., “Peer-to-Peer energy trading considering the output uncertainty of distributed energy resources”, Energy Reports, vol. 8, suppl. 1, 2022, pp. 567–574, https://doi.org/10.1016/j.egyr.2021.11.001.
• Yan T., Liu J., Niu Q. et al., “Distributed energy storage node controller and control strategy based on energy storage cloud platform architecture”, Global Energy Interconnection, vol. 3, no. 2, 2020, pp. 166–174, https://doi.org/10.1016/j.gloei.2020.05.008.
• Zakeri B., Gissey G.C., Dodds P.E., Subkhankulova D., “Centralized vs. distributed energy storage: Benefits for residential users”, Energy, vol. 236, 2021, 121443, https://doi.org/10.1016/j.energy.2021.121443.
• Zhang S., May D., Gül M., Musilek P., “Reinforcement learning-driven local transactive energy market for distributed energy resources”, Energy and AI, vol. 8, 2022, 100150, https://doi.org/10.1016/j.egyai.2022.100150.
• Zheng W., Zou B., “Evaluation of intermittent-distributed-generation hosting capability of a distribution system with integrated energy-storage systems”, Global Energy Interconnection, vol. 4, no. 4, 2021, pp. 415–424, https://doi.org/10.1016/j.gloei.2021.09.003.

Identifiers

DOI

10.48269/2451-0718-btip-2022-2-002

Biblioteka Nauki

2170028