The Residual Load Duration Curve (rLDC) to model an energy system W.-G. Früh   2019/07/15

Abstract

This paper develops a framework to represent the action of different generation and balancing technologies based on the statistics of the demand and generation using the concept of the
Load Duration Curve (LDC). The aim is to capture the statistics in terms of energy and power provision from a generation type given by its inherent resource, technical and economic constraints.
This paper provides a brief overview of the fundamental types of generation and balancing, and how their action modifies the load duration curve to eventually arrive at a balanced system. Based on
empirical data from the UK National Grid, the statistical properties of renewable energy sources and of the energy and power capacities of energy storage technologies, different basic functional relationships between the residual Load Duration Curves (rLDC) will be derived for these technologies.

Authors and affiliations

W.-G. Früh
Institute of Mechanical, Process and Energy Engineering, School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh (Scotland, UK)

Key words

Energy system, Renewables integration, Load Duration Curve, Equivalent Load Duration Curve.

References

[1] R. Loulou, G. Goldstein, K. Noble, “Documentation for the MARKAL family of models, ETSAP, 2004., see also
https://iea-etsap.org/index.php/etsap-tools/modelgenerators/times, accessed 18 Jan 2019.
[2] H. Lund, J.Z. Thellufsen, “EnergyPLAN: Advanced Energy Systems Analysis Computer Model”, Documentation V.14,
2018, see also https://www.energyplan.eu/ , accessed 18 Jan 2019.
[3] Scottish Power, Whitelee Windfarm website, https://www.scottishpower.co.uk/whitelee/ , accessed 18 Jan 2019.
[4] A. Poulin, M. Dostie, M. Fournier, S. Sansregret, “Load duration curve: A tool for technico-economic analysis of
energy solutions”, Energy and Buildings, Vol. 40, pp. 29–35.
[5] ELEXON, “Historic generation by fuel type”, www.elexonportal.co.uk/historicgenerationbyfueltype, accessed 19 Nov 2017.
[6] A.S. Malik, B.J. Cory, “An application of frequency and duration approach in generation planning”, IEEE Transactions on Power Systems, Vol. 12, pp. 1076 – 1084.
[7] M. Ould Mohamed Mahmoud, M. Jaïdane-Saïdane, J. Souissi, N. Hizaoui, “Modeling of the load duration curve using the asymmetric generalized Gaussian distribution: Case of the Tunisian power system”, in IEEE Power and Energy Society 2008 General Meeting: Conversion and Delivery of Electrical Energy in the 21st Century, PES.
[8] M. Kato, Y. Zhou, C. Kang, R. Yokoyama, ”Novel approach of modeling load duration curve for generation expansion planning based on Hill’s function”, in IEEJ Transactions on Electrical and Electronic Engineering, 2011, Vol. 6, pp. 304–310.
[9] A. Wiskich, “Implementing a load duration curve of electricity demand in a general equilibrium model”, in Energy Economics, 2014, Vol. 45, pp.373–380.
[10] W.-G. Früh, “From local wind energy resource to national wind power production”, in AIMS Energy, 2015, Vol. 3,
pp.101–120.
[11] Ofgem, “Wholesale Energy Markets in 2016”, 2016, https://www.ofgem.gov.uk/system/files/docs/2016/08/wh
olesale_energy_markets_in_2016.pdf , accessed 18 Jan 2019.
[12] Nuclear Energy Agency, “Technical and economic aspects of load following with Nuclear power plants, OECD, 2011,
https://www.oecd-nea.org/ndd/reports/2011/loadfollowing-npp.pdf , accessed 18 Jan 2019.
[13] S.R. Greene, “Enhancing Electric Grid, Critical Infrastructure, and Societal Resilience with Resilient Nuclear Power Plants (rNPPs)”, in Nuclear Technology, 2018, Vol. 204, pp.1–18.