How to cite this WIREs title:
WIREs Energy Environ.

Impact Factor: 3.803

Power system transition in China under the coordinated development of power sources, network, demand response, and energy storage

Opinion

Ning Zhang, Hongcai Dai, Yaohua Wang, Yunzhou Zhang, Yuqing Yang

Published Online: Dec 09 2020

DOI: 10.1002/wene.392

Full article on Wiley Online Library: HTML PDF

Can't access this content? Tell your librarian.

Abstract China is transiting its power system towards a more flexible status with a higher capability of integrating renewable energy generation. Demand response (DR) and energy storage increasingly play important roles to improve power system flexibility. The coordinated development of power sources, network, DR, and energy storage will become a trend. This paper examines the significance of source‐network‐demand‐storage coordinated development. Furthermore, an outlook of the power system transition in China is provided by virtue of source‐network‐demand‐storage coordinated planning. The paper also assesses the integration of multiple urban infrastructures in China and its impacts on source‐network‐demand‐storage coordination. Lastly, challenges for achieving the source‐network‐demand‐storage coordination and suggested measures are discussed. This article is categorized under: Energy Research & Innovation > Systems and Infrastructure Energy and Urban Design > Systems and Infrastructure

Schematic diagram of source‐network‐demand‐storage coordinated planning

[ Normal View | Magnified View ]

Development of energy storage from now to 2050. (a) Total capacity of energy storage and (b) energy storage capacity in various regions

[ Normal View | Magnified View ]

Development of DR from now to 2050. (a) Total capacity of DR and (b) DR capacity in various regions

[ Normal View | Magnified View ]

Power flow among various regions in 2050

[ Normal View | Magnified View ]

Installed capacity of various power sources from now to 2050 in China

[ Normal View | Magnified View ]

Schematic diagram of the optimization model of source‐network‐demand‐storage coordinated planning

[ Normal View | Magnified View ]

References

Barbour,, E., Parra,, D., Awwad,, Z., & González,, M. C. (2018). Community energy storage: A smart choice for the smart grid. Applied Energy, 212, 489–497.
Barton,, J. P., & Infield,, D. G. (2004). Energy storage and its use with intermittent renewable energy. IEEE Transactions on Energy Conversion, 19(2), 441–448.
Bjelić,, I. B., & Rajaković,, N. (2015). Simulation‐based optimization of sustainable national energy systems. Energy, 91, 1087–1098.
BNEF. (2019). New Energy Outlook. Retrieved from https://www.newenergyfinance.com/flagships/new-energy-outlook
CGTN. (2020). Getting to know China`s new infrastructure projects. Retrieved from https://news.cgtn.com/news/2020-05-06/Getting-to-know-China-s-new-infrastructure-projects-QfIOLy9khq/index.html
Chen,, X., Mcelroy,, M. B., & Kang,, C. (2018). Integrated energy systems for higher wind penetration in China: Formulation, implementation and impacts. IEEE Transactions on Power Systems, 33(2), 1309–1319.
Dong,, G. C., & Thomas,, V. M. (2012). An electricity generation planning model incorporating demand response. Energy Policy, 42(2), 429–441.
Dong,, J., Xue,, G., & Li,, R. (2016). Demand response in China: Regulations, pilot projects and recommendations – A review. Renewable %26 Sustainable Energy Reviews, 59, 13–27.
Go,, R. S., Munoz,, F. D., & Watson,, J. P. (2016). Assessing the economic value of co‐optimized grid‐scale energy storage investments in supporting high renewable portfolio standards. Applied Energy, 183, 902–913.
Graabak,, I., Wu,, Q., Warland,, L., & Liu,, Z. (2016). Optimal planning of the Nordic transmission system with 100% electric vehicle penetration of passenger cars by 2050. Energy, 107, 648–660.
Heuberger,, C. F., Rubin,, E. S., Staffell,, I., Shah,, N., & Dowell,, N. M. (2017). Power capacity expansion planning considering endogenous technology cost learning. Applied Energy, 204, 831–845.
Hu,, Z., Wen,, Q., Wang,, J., Tan,, X., Nezhad,, H., Shan,, B., & Han,, X. (2010). Integrated resource strategic planning in China. Energy Policy, 38(8), 4635–4642.
Huo,, M. (2015) What`s the experience of demand response pilots in China? China Electric Power News. Retrieved from http://hvdc.chinapower.com.cn/news/1039/10393862.asp. (in Chinese)
IEA. (2017). Digitalization and energy. Retrieved from https://www.iea.org/events/digitalization-and-energy
IRENA. (2018). Power system flexibility for the energy transition. Retrieved from https://www.irena.org/publications/2018/Nov/Power-system-flexibility-for-the-energy-transition
Koltsaklis,, N. E., Liu,, P., & Georgiadis,, M. C. (2015). An integrated stochastic multi‐regional long‐term energy planning model incorporating autonomous power systems and demand response. Energy, 82, 865–888.
Li,, S., Ni,, Q., Sun,, Y. J., Min,, J. Y., Min,, G. Y., & Rubaye,, S. (2018). Energy‐efficient resource allocation for industrial cyber‐physical IoT systems in 5G era. IEEE Transactions on Industrial Informatics, 14(6), 2618–2628.
Li,, Y., Wang,, C. L., Li,, G. Q., Wang,, J. L., Zhao,, D. B., & Chen,, C. (2020). Improving operational flexibility of integrated energy system with uncertain renewable generations considering thermal inertia of buildings. Energy Conversion and Management, 207, 1125–1126.
Liu,, Y., Li,, H., Peng,, K., Zhang,, C., Huang,, S. H., & Li,, W. (2018). Demonstration projects of integrated energy system in China. Energy Procedia, 145, 88–96.
Moghaddam,, M. M., Javidi,, M. H., Moghaddam,, M. P., & Buygi,, M. O. (2013). Coordinated decisions for transmission and generation expansion planning in electricity markets. International Transactions on Electrical Energy Systems, 23, 1452–1467.
Munshi,, A. A., & Mohamed,, Y. A. (2018). Extracting and defining flexibility of residential electrical vehicle charging loads. IEEE Transactions on Industrial Informatics, 14(2), 448–461.
NBN. (2019). 2018–2020 action plan of clean energy consumption. Retrieved from https://nbn.media/2018-2020-action-plan-of-clean-energy-consumption/
Niina,, H., Juha,, K., Hannele,, H., Daniel,, L. J., & Bri,, H. (2019). Including operational aspects in the planning of power systems with large amounts of variable generation: A review of modeling approaches. WIREs: Energy Environment, 8(5), e341.1–e341.34.
Perera,, P., Hewage,, K., & Sadiq,, R. (2020). Electric vehicle recharging infrastructure planning and management in urban communities. Journal of Cleaner Production, 250, 119559.
Pham,, H. Q., Lee,, H. Y., Hwang,, E. H., Kwon,, Y. G., & Song,, S. W. (2018). Non‐flammable organic liquid electrolyte for high‐safety and high‐energy density Li‐ion batteries. Journal of Power Sources, 404(15), 13–19.
Pozo,, D., Sauma,, E. E., & Contreras,, J. A. (2013). Three‐level static MILP model for generation and transmission expansion planning. IEEE Transactions on Power Systems, 28(1), 202–210.
Qiu,, J., Zhao,, J., Yang,, H., Wang,, D., & Dong,, Z. (2017). Planning of solar photovoltaics, battery energy storage system and gas micro turbine for coupled micro energy grids. Applied Energy, 219, 361–369.
Revesz,, R. L., & Unel,, B. (2018). Managing the future of the electricity grid: Energy storage and greenhouse gas emissions. The Harvard Environmental Law Review: HELR, 42, 139.
Rouhani,, A., Hosseini,, S. H., & Raoofat,, M. (2014). Composite generation and transmission expansion planning considering distributed generation. International Journal of Electrical Power %26 Energy Systems, 62(60), 792–805.
Schlachtberger,, D. P., Becker,, S., Schramm,, S., & Greiner,, M. (2016). Backup flexibility classes in emerging large‐scale renewable electricity systems. Energy Conversion and Management, 125, 336–346.
Sechilariu,, M., Molines,, N., Richard,, G., & Martell Flores,, H. (2019). Electromobility framework study: Infrastructure and urban planning for EV charging station empowered by PV‐based microgrid. IET Electrical Systems in Transportation, 9(4), 176–185.
Seddighi,, A. H., & Ahmadi‐Javid,, A. (2015). Integrated multi‐period power generation and transmission expansion planning with sustainability aspects in a stochastic environment. Energy, 86, 9–18.
SETIS. (2018). Digitalisation of the energy sector. Retrieved from https://setis.ec.europa.eu/publications/setis-magazine/digitalisation-of-energy-sector
Sikorski,, T., Jasiński,, M., Ropuszyńska‐Surma,, E., & Borgosz‐Koczwara,, M. (2019). A case study on distributed energy resources and energy‐storage systems in a virtual power plant concept: Economic aspects. Energies, 12(23), 44–47.
Sisternes,, F. J. D., Jenkins,, J. D., & Botterud,, A. (2016). The value of energy storage in decarbonizing the electricity sector. Applied Energy, 175, 368–379.
Sun,, H., Guo,, Q., Wu,, W., Wang,, B., Xia,, T., & Zhang,, B. (2019). Integrated energy management system with multi‐energy flow for Energy Internet: Design and application. Automation of Electric Power Systems, 43(12), 122 (in Chinese).
Tang,, Y., Chen,, Q., Ning,, J., Wang,, Q., Feng,, S. H., & Li,, Y. P. (2018). Hierarchical control strategy for residential demand response considering time‐varying aggregated capacity. International Journal of Electrical Power %26 Energy Systems, 97, 165–173.
Wang,, F. (2020). China to boost construction of new infrastructure, advance industrial and consumption upgrade. Retrieved from http://www.ecns.cn/news/economy/2020-04-28/detail-ifzvtuth8163432.shtml
Wang,, F., Ge,, X. X., Li,, K., & Mi,, Z. Q. (2019). Day‐ahead market optimal bidding strategy and quantitative compensation mechanism design for load aggregator engaging demand response. IEEE Transactions on Industry Applications, 55(6), 5564–5573.
Wu,, D., Lian,, J. M., Sun,, Y. N., Yang,, T., & Hansen,, J. (2017). Hierarchical control framework for integrated coordination between distributed energy resources and demand response. Electric Power Systems Research, 150, 45–54.
Yuan,, J., Xu,, Y., Kang,, J., Zhang,, X., & Hu,, Z. (2014). Nonlinear integrated resource strategic planning model and case study in China`s power sector planning. Energy, 67, 27–40.
Zeng,, M., Yang,, Y., Liu,, D., Zeng,, B., Ouyang,, S., Lin,, H., & Han,, X. (2016). “Generation‐grid‐load‐storage” coordinative optimal operation mode of energy internet and key technologies. Power System Technology, 40(1), 124–134 (in Chinese).
Zeng,, M., Yang,, Y., Xiang,, H., Wang,, L., & Zeng,, B. (2016). Optimal dispatch model based on coordination between “generation‐grid‐load‐energy storage” and demand‐side resource. Electric Power Automation Equipment, 036(002), 102–111 (in Chinese).
Zeng,, S., Tang,, S., Cheng,, H., Su,, Z., Xia,, W., & Zeng,, Y. (2018). Framework planning of active distribution network considering coordinated optimization of generation, network, load and storage. Southern Power System Technology, 012(003), 35–43 (in Chinese).
Zhang,, N., Hu,, Z., Shen,, B., He,, G., & Zheng,, Y. (2017). An integrated source‐grid‐load planning model at the macro level: Case study for China`s power sector. Energy, 126, 231–246.
Zhang,, Q., Mclellan,, B., Tezuka,, T., & Ishihara,, K. (2013). An integrated model for long‐term power generation planning toward future smart electricity systems. Applied Energy, 112, 1424–1437.

Further Reading

He,, Y., Xia,, T., Liu,, Z., Zhang,, T., & Dong,, Z. (2013). Evaluation of the capability of accepting large‐scale wind power in China. Renewable %26 Sustainable Energy Reviews, 19, 509–516.

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts