Generation Integrated Energy Storage - A Paradigm Shift

Lead Research Organisation: University of Leeds
Department Name: Civil Engineering

Abstract

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Description This project has examined the marginal economic value of GIES systems when these co-exist with conventional energy storage systems. Novel methodologies to conduct the economic and financial analysis were developed and the corresponding results were published in prestigious journals, including Applied Energy, Journal of Cleaner Production, and Energy. The award has also facilitated international multi-disciplinary collaboration with the Department of Electrical Engineering at Guangdong University of Technology. The addition output to the award includes the establishment of an IEEE Working Group to develop Recommended Practices in energy system techno-economic appraisals.

This project has completed the cost and revenue analysis (economic perspective) for GIES and non-GIES systems

As Li-ion batteries are becoming a more popular form of large-scale energy storage, a state-of-the-art financial model was developed to obtain novel and significative financial and economics results when applied to Li-ion EES. Consider Li-ion cell degradation, the frequent use of Li-ion (thus reducing lifetime) can be financially attractive. In addition, we compared the economics and financial merits for GIES (with pumped-heat energy storage) and non-GIES (with a Lithium-ion battery) systems coupled with wind generation in the United Kingdom. Wind farms without energy storage have better economic and financial performance.

Specifically, the studies were published as follows:
1. Lai, C.S., Locatelli, G., Pimm, A., Tao, Y., Li, X. and Lai, L.L., 2019. A financial model for lithium-ion storage in a photovoltaic and biogas energy system. Applied Energy, 251, p.113179.
2. Lai, C.S. and Locatelli, G., 2021. Economic and financial appraisal of novel large-scale energy storage technologies. Energy, 214, p.118954.

This project has completed the analysis of optimal financing and cash flow management (financial perspective) for GIES and non-GIES systems:

GIES systems are risky investments due to their relevant technical and economic uncertainties. Prototyping can hedge these risks by spending a fraction of the cost of a full-scale system and in return receiving economic and technical information regarding the system. In economic terms, prototyping is an option to hedge risk coming at a cost that needs to be properly assessed. Real options analysis is the project appraisal approach for these assessments. We introduced and test an algorithm based on real options analysis to quantitatively assess the "option to prototype" in the energy sector. Results show that the cost of the prototype and the market size (number of identical systems to build) are key parameters.

We conducted a scenario analysis considering different levels of support from the UK government for GIES systems. According to the state-of-the-art financial model, the case study of energy storage systems coupled with a Small Modular nuclear Reactor (SMR) is quantitatively investigated in three scenarios. As the net present value reduces with increased energy storage capacity (when coupled with generation), this work shows that low-carbon incentives are, unintentionally, barriers to the development of energy storage due to: (A) current generator incentives give a favourable return on investment and energy storage would diminish it; (B) energy storage cannot participate in generator only incentives.

Specifically, the studies were published as follows:
1. Lai, C.S. and Locatelli, G., 2021. Valuing the option to prototype: A case study with Generation Integrated Energy Storage. Energy, 217, p.119290.
2. Lai, C.S. and Locatelli, G., 2021. Are energy policies for supporting low-carbon power generation killing energy storage?. Journal of Cleaner Production, 280, p.124626.

The ongoing work includes the study and development of contractual frameworks to link project stakeholders (management and legal perspective) of GIES systems:

We have examined the typical contractual frameworks for energy storage and generation systems. The ongoing research includes contractual analysis to identify the key actors and feasible development paths for several GIES systems.

In this regard, we started identifying the typical risks associable with various stakeholders involved in the construction and operation of GIES. Lai, C.S., Sainati, T., Locatelli, G. and Lai, L.L., 2019. "Project financing for generation integrated energy storage: A UK context," Applied Energy Symposium 2019, Xiamen, China http://www.energy-proceedings.org/wp-content/uploads/2020/02/CUE2019_paper_24.pdf

We then developed a framework for the available financial and commercial models for GIES, looking at the comparable energy technologies. We started carrying out an extensive literature review on financial and commercial models for energy facilities. Then we carried out a multiple case study looking at the evolution of the financial and commercial models for selected energy technologies, including wind farms, concentrated thermal-solar plants, and nuclear fusion. It was not possible to consider existing cases of GIES directly because they are at the early stage of technology development (i.e. low technology readiness level - TRL), and the start-ups we contacted were not willing to share commercially-sensitive information. Our preliminary results have been sent to an academic conference: Mignacca, B., Sainati, T., Locatelli, G., "Financing energy innovation projects for net-zero: A novel diagrammatic model", Submitted to European Academy of Management- EURAM 2022 - Annual Conference. We intend to improve the manuscript and then submit it to a relevant academic journal, such as the Journal of Cleaner Production, Energy Economics or similar journals.
We showed that all energy technologies revise the financial and commercial model depending on the stage of technological development. Given the current stage of technology development (i.e. early prototyping/ demonstration plants), GIES is likely to require relevant public financial support before its full commercialisation. To deepen this concluding analysis, we are planning to involve additional quali-quantitative analysis, looking at the type of public subsidies required to make GIES commercially viable.
Exploitation Route As also described in our review paper on long-term electrical power system modeling with energy storage, GIES systems are not well recognised in power systems and smart grid development. To further decarbonise the society, GIES technologies will need to be included for large-scale energy storage. Academic research is still needed to examine the technical and economic performance of GIES systems.

Government authorities need to consider GIES systems in developing low-carbon energy roadmaps. In particular, generous incentives are provided for low-carbon generation. The impact on energy storage and GIES systems development needs to be examined further.

The results of our research will inform technology developers and public entities on the most suitable financial schemes for GIES technologies.
Sectors Energy
 
Description IEEE P2814 - Techno-economics terminology working group
Geographic Reach Multiple continents/international 
Policy Influence Type Membership of a guideline committee
 
Description Collaboration with Professor Loi Lei Lai - 
Organisation Guangdong University of Technology
Country China 
Sector Academic/University 
PI Contribution This research project generated a collaboration with Professor Loi Lei Lai and his team at the Department of Electrical Engineering, Guangdong University of Technology. Professor L. L. Lai is a leading authority in power systems research having awarded FIEEE for contributions to the development of computational intelligence techniques to power system applications. The collaboration with has proved to be very fruitful and generated 5 papers, 4 of which directly related to this grant/project. This research collaboration aims to bridge the gap between energy storage techno-economics and power system/smart grid research. In particular, a paper was produced for a state-of-the-art review of long-term electrical power system models and shows that (a) existing models are inadequate to address grids with a high percentage of renewables and energy storage; and (b) there is a challenge in integrating short-term temporal changes in long-term electrical power system models due to model complexity and computational cost. Lai, C.S., Locatelli, G., Pimm, A., Wu, X. and Lai, L.L., 2020. A review on long-term electrical power system modeling with energy storage. Journal of Cleaner Production, p.124298. The collaboration also led to an establishment of a Special Session: "Smart grid under high penetration of renewables and generation integrated energy storages" at IEEE International Conference on Systems, Man, and Cybernetics, Bari, Italy http://smc2019.org/approved_special_sessions.html
Collaborator Contribution He supported the technical analysis of our research particularly focusing on the Electrical / power Systems elements
Impact Lai, C.S., Locatelli, G., Pimm, A., Wu, X., Lai, L.L. A review on long-term electrical power system modeling with energy storage (2021) Journal of Cleaner Production, 280, art. no. 124298, .(multidisciplinary: energy, power systems, economics) Lai, C.S., Locatelli, G., Pimm, A., Tao, Y., Li, X., Lai, L.L. A financial model for lithium-ion storage in a photovoltaic and biogas energy system (2019) Applied Energy, 251, art. no. 113179, . https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065927499&doi=10.1016%2fj.apenergy.2019.04.175?nerID=40&md5=3388707b72e707b4b4c20d81a9464e7a (multidisciplinary: energy, power systems, economics) Lai, C.S., Locatelli, G., Pimm, A., Li, X., Lai, L.L. Levelized cost of electricity considering electrochemical energy storage cycle-life degradations (2019) Energy Procedia, 158, pp. 3308-3313. (multidisciplinary: energy, power systems, economics) Lai, C.S., Tao, Y., Xu, F., Ng, W.W.Y., Jia, Y., Yuan, H., Huang, C., Lai, L.L., Xu, Z., Locatelli, G. A robust correlation analysis framework for imbalanced and dichotomous data with uncertainty (2019) Information Sciences, 470, pp. 58-77. (multidisciplinary: energy, informatics, mathematics) Lai, C.S., Li, X., Locatelli, G., Lai, L.L. Cost benefit analysis and data analytics for renewable energy and electrical energy storage (2018) IET Conference Publications, 2018 (CP757), . (multidisciplinary: energy, power systems, economics) Lai, C.S., Locatelli, G., Pimm, A., Li, X. and Lai, L.L., 2018, May. Levelized cost of electricity with storage degradation. In Proceedings of Offshore Energy and Storage 2018. Leeds. (multidisciplinary: energy, power systems, economics) Lai, C.S., Sainati, T., Locatelli, G. and Lai, L.L., 2019. "Project financing for generation integrated energy storage: A UK context," Applied Energy Symposium 2019, Xiamen, China http://www.energy-proceedings.org/wp-content/uploads/2020/02/CUE2019_paper_24.pdf
Start Year 2018
 
Title Excel files 
Description The project has produced three new computational models: 1. A discounted cash flow model for the Li-ion battery with detailed technical, economic, and finance inputs is developed in Microsoft Excel. The cash flow model obtains the technical input according to three energy storage operating scenarios. The energy storage is installed with biogas power generator and photovoltaic power plant. The operating regime is developed in MATLAB. Lai, C.S., Locatelli, G., Pimm, A., Tao, Y., Li, X. and Lai, L.L., 2019. A financial model for lithium-ion storage in a photovoltaic and biogas energy system. Applied Energy, 251, p.113179. 2. A state-of-the-art cash flow model for generation integrated energy storage (GIES) is developed and accounts for the technical, economic, and financial inputs with uncertainties. The model allows financial and economic comparison of GIES and non-GIES systems. The cash flow model was developed in Microsoft Excel with Palisade @Risk for Monte Carlo analysis. Lai, C.S. and Locatelli, G., 2021. Economic and financial appraisal of novel large-scale energy storage technologies. Energy, 214, p.118954. 3. A real option to prototype algorithm is developed to quantitatively assess the "option to prototype" in the energy sector and GIES systems. Prototyping can hedge these risks by spending a fraction of the cost of a full-scale system and in return receiving economic and technical information regarding the system. In economic terms, prototyping is an option to hedge risk coming at a cost that needs to be properly assessed. The option model was developed in Microsoft Excel with Palisade @Risk for Monte Carlo analysis. Lai, C.S. and Locatelli, G., 2021. Valuing the option to prototype: A case study with Generation Integrated Energy Storage. Energy, 217, p.119290. 
Type Of Technology Webtool/Application 
Year Produced 2019 
Impact We published the papers listed in the previous sections