Load modelling and non-intrusive load monitoring to integrate distributed energy resources in low and medium voltage networks. (December 2021)

• Record Type: Journal Article
• Authors: Moreno Jaramillo, Andres F.; Laverty, David M.; Morrow, D. John; Martinez del Rincon, Jesús; Foley, Aoife M.
• Is Part Of: Renewable energy. Volume 179(2021)
• Page Start: 445
• Page End: 466
• Publication Date: 2021-12
• Subjects: Distributed energy resources -- Load modelling -- Load identification -- Low voltage distribution network -- Non-intrusive load monitoring -- Smart grids; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2021.07.056
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: In many countries distributed energy resources (DER) (e.g. photovoltaics, batteries, wind turbines, electric vehicles, electric heat pumps, air-conditioning units and smart domestic appliances) are part of the 'Green Deal' to deliver a climate neutral society. Policy roadmaps, despite providing a framework and penetration targets for DER, often lack the network planning strategies needed to transition from passive to active distribution networks. Currently, DER's dynamic performance parameters and location identification techniques are not fully standardised. In fact, it can be very ad hoc . Standardised distributed load modelling and non-intrusive load monitoring (NILM) for equipment manufacturers, installers and network operators is critical to low and medium voltage network management in order to facilitate better balancing, flexibility and electricity trading across and within the power system for mass DER deployment. The aim of this paper is to fill this load modelling and NILM knowledge gap for DERto inform the 'Green Deal' transition and support standardisation. In the paper, existing load modelling techniques and NILM methodologies are critically examined to inform and guide research activity, equipment development and regulator thinking, as well as network operators. Seven key findings that need urgent attention are identified to support a smooth power system reconfiguration. Graphical abstract: Image 1 Highlights: A thorough review of existing monitoring and modelling methods for DER on distribution networks is provided. Efficacies between 65% and 95% for conventional load identification exist. Increasing DER penetrations are creating technological challenges in distribution networks. Optimum DER integration in low voltage networks is vital for electric networks reliability. Seven aspects to enable massification of DER on distribution networks are established.