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

TL;DR

This paper introduces a probabilistic framework combining statistical models, a novel home energy management system, and power-flow analysis to optimize tariff design and manage the impact of distributed energy resources in low-voltage networks.

Contribution

It presents a new probabilistic approach integrating Bayesian models, HEMS, and power-flow analysis for designing tariffs that mitigate DER impacts and enhance network performance.

Findings

Flat tariffs with peak demand components reduce customer costs.

The framework effectively alleviates network constraints.

Customer HEM systems complement tariff strategies.

Abstract

Given the historically static nature of low-voltage networks, distribution network companies do not possess tools for dealing with an increasingly variable demand due to the high penetration of distributed energy resources (DER). Within this context, this paper proposes a probabilistic framework for tariff design that minimises the impact of DER on network performance, stabilise network company revenue, and improves the equity of network costs allocation. To address the issue of the lack of customers' response, we also show how DER-specific tariffs can be complemented with an automated home energy management system (HEMS) that reduces peak demand while retaining the desired comfort level. The proposed framework comprises a nonparametric Bayesian model which statistically generates synthetic load and PV traces, a hot-water-use statistical model, a novel HEMS to schedule customers' controllable devices, and a probabilistic power-flow model. Test cases using both energy- and demand-based network tariffs show that flat tariffs with a peak demand component reduce the customers' cost, and alleviate network constraints. This demonstrates, first, the efficacy of the proposed tool for the development of tariffs that are beneficial for networks with a high DER penetration, and second, how customers' HEM systems can be part of the solution.