Network impacts of distribution power tariff schemes with active customers

Supponen, Antti; Rautiainen, Antti; Lummi, Kimmo; Järventausta, Pertti; Repo, Sami

doi:10.1109/eem.2016.7521237

Cited by 4 publications

(4 citation statements)

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“…For customers facing an energy-based tariff (Flat or ToU, which will be explained in Section VII-B), the monthly optimisation model is given in ( 12) for all h Î H, subject to (2)- (11), and ( 13)- (18).…”

Section: A Optimisation Model For Energy-based Tariffsmentioning

confidence: 99%

“…Different tariffs including Flat, ToU, FlatD, and ToUD will be discussed in detail in Section VII-B. The monthly optimisation model is given in (19) for all h Î H, subject to (3)-( 11), ( 13)- (18), and (20).…”

Section: B Optimisation Model For Demand-based Tariffsmentioning

confidence: 99%

“…In [17], the timeof-use (ToU) tariffs alone can increase peak loading on networks with high penetration levels of DERs, where customers seek to maximise their cost savings. In view of this, [18] shows that demand-based tariffs could be used to mitigate transformer loading at medium-voltage (MV) substations. Similarly, the results in [19] demonstrates the effectiveness of demand-based tariffs in alleviating peak demand considering demand response from controllable appliances of customers.…”

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confidence: 99%

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Probabilistic Assessment of Impact of Flexible Loads Under Network Tariffs in Low-voltage Distribution Networks

Azuatalam

Chapman

2021

Journal of Modern Power Systems and Clean Energy

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Given the historically static nature of low-voltage networks, distribution network companies do not possess the tools for dealing with an increasingly variable demand due to the high penetration of distributed energy resources (DERs). Within this context, this paper proposes a probabilistic framework for tariff design that minimises the impact of DER on network performance, stabilises the revenue of network company, and improves the equity of network cost allocation. To deal with the lack of customers' ' response, we also show how DERspecific 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, firstly, the efficacy of the proposed tool for the development of tariffs that are beneficial for the networks with a high penetration of DERs, and secondly, how customers' ' HEM systems can be part of the solution.

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Section: A Optimisation Model For Energy-based Tariffsmentioning

confidence: 99%

Section: B Optimisation Model For Demand-based Tariffsmentioning

confidence: 99%

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confidence: 99%

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Probabilistic Assessment of Impact of Flexible Loads Under Network Tariffs in Low-voltage Distribution Networks

Azuatalam

Chapman

2021

Journal of Modern Power Systems and Clean Energy

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“…It was shown in [17] that time-of-use (ToU) tariffs alone can increase peak loading on networks with deep DER penetration levels, where customers seek to maximise their cost savings. In view of this, authors in [18] showed that demand-based tariffs could be used to mitigate transformer loading at medium voltage (MV) substations. Similarly, the results in [19] demonstrated the effectiveness of demand-based tariffs in alleviating peak demand whilst considering demand response from customers' controllable appliances.…”

Section: Introductionmentioning

confidence: 99%

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

Azuatalam¹,

Chapman²,

Verbič³

2018

Preprint

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In many jurisdictions, the recent wave of rooftop PV investment compromised the equity of network cost allocations across retail electricity customer classes, in part due to poorly designed network, retail and feed-in tariffs. Currently, a new wave of investment in distributed energy resource (DER), such as residential batteries and home energy management systems, is unfurling and with it so does the risk of repeating the same tariff design mistakes. As such, distribution network service providers need improved tools for crafting DER-specific tariffs. These tools will guide the design of tariffs that minimise DER impacts on network performance, stabilise network company revenue, and improve the equity of network costs across the customer base. Within this context, this paper proposes a probabilistic framework to assess the impacts of different network tariffs on the consumption pattern of electricity consumers with flexible DER, such as thermostatically controlled loads and battery storage. The assessment tool comprises randomly-generated synthetic load and rooftop generation traces, which are fed into a mixed integer linear programming-based home energy management system to schedule residential customers' controllable devices connected to a low voltage network. Customer net loads are then used in low voltage power flow studies to assess the network effects of various tariff designs. In this work, assessments are made of energy-and demand-based tariffs. Simulation results show that flat tariffs with a peak demand component perform best in terms of electricity cost reduction for the customer, as well as in mitigating the level of binding network constraints. This demonstrates how the assessment tool can be used by distribution network service providers and regulators to develop tariffs that are beneficial for networks that play host to growing numbers of PV-battery systems and other DER.

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