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Given the historically static nature of low-voltage networks, distributionnetwork companies do not possess tools for dealing with an increasinglyvariable demand due to the high penetration of distributed energy resources(DER). Within this context, this paper proposes a probabilistic framework fortariff design that minimises the impact of DER on network performance,stabilise network company revenue, and improves the equity of network costsallocation. To address the issue of the lack of customers' response, we alsoshow how DER-specific tariffs can be complemented with an automated home energymanagement system (HEMS) that reduces peak demand while retaining the desiredcomfort level. The proposed framework comprises a nonparametric Bayesian modelwhich statistically generates synthetic load and PV traces, a hot-water-usestatistical model, a novel HEMS to schedule customers' controllable devices,and a probabilistic power-flow model. Test cases using both energy- anddemand-based network tariffs show that flat tariffs with a peak demandcomponent reduce the customers' cost, and alleviate network constraints. Thisdemonstrates, first, the efficacy of the proposed tool for the development oftariffs that are beneficial for networks with a high DER penetration, andsecond, how customers' HEM systems can be part of the solution.

Probabilistic assessment of the impact of flexible loads under network tariffs in low voltage distribution networks