An approach to probabilistic assessment of the influence of penetration of low-carbon technologies on aggregate load models

The paper presents the methodology and its application to study how the increasing adoption of low-carbon technologies (LCTs), e.g., electric vehicles, light-emitting diode (LED) lighting, and heat pumps, affects aggregate load models at bulk supply points. A probabilistic component-based methodology is used to develop aggregate exponential load models across various LCT penetration levels and corresponding probability distribution functions (PDFs) for real and reactive power voltage exponents, accounting for different device types and load mix (composition) at the bus. It enables parameter estimation for modern and future residential, commercial, and industrial load mixes (and their combinations) without the need for any field measurements. To illustrate the outputs of the study, the paper presents the estimated voltage exponents and their trends under increasing LCT penetration. The presented methodology lays a rigorous foundation for future investigations into load modelling, optimisation, steady-state and dynamic power system studies in networks with increasing proliferation of LCTs, either existing or planned, and is hence applicable for both operational and planning level studies.