Time-of-use and time-of-export tariffs for home batteries: Effects on low voltage distribution networks

Pimm, Andrew J.; Cockerill, Tim; Taylor, Peter

doi:10.1016/j.est.2018.06.008

Cited by 51 publications

(36 citation statements)

References 22 publications

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“…The impact of ToU tariffs is investigated in [7] emphasizing their influence on load curves of residential consumers in grid areas with RES, heat pumps and storage facilities. The response of energy storage facilities to tariff system and their effect of peak shaving on the distribution grid is analysed using Monte Carlo method in the context of higher EV and heat pumps penetration.…”

Section: I Initial Consumption C Modmentioning

confidence: 99%

“…The operation of storage facilities showed that ToU tariffs have little effect on the consumption peak, requiring other measures to reward flexibility. There is a similarity between [7] and our approach in the sense that we both investigate the effect of the ToU tariffs on the consumption peak, but our methodology is aiming to set a tariff to respond to the consumers' actual contribution to the consumption peak/off-peak.…”

Section: I Initial Consumption C Modmentioning

confidence: 99%

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Setting the Time-of-Use Tariff Rates With NoSQL and Machine Learning to a Sustainable Environment

Oprea

Bârã

2020

IEEE Access

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The electricity consumption will continue to increase despite the overall efforts and tendencies of changing the old appliances to less energy intensive ones. The advancements of Electric Vehicles (EV) and public mobility, electric heating, and the abundance of smart appliances that enhance the comfort of modern life lead to an increasing consumption trend. On the other hand, prosumers raising the quota of distributed generation and storage capacity will balance the electricity consumption trend. These changes at the consumption and generation level lead to the necessity to increase the awareness and incentive the consumers' behavior to flatten the consumption curve and improve the savings. Such objectives could be reached by properly setting the Time-of-Use (ToU) tariff rates to encourage the consumption at off-peak hours when the rates are lower and unstress the grid loading. In this paper, we propose a methodology for setting the Time-of-Use (ToU) tariff rates and peak/off-peak intervals using big data technologies and machine learning, and verify the assumptions considering the large volume of consumption data of over 4200 residential consumers recorded in a smart metering implementation trail period that took place in Ireland from January to December 2010. We calculate the contribution to the peak/off-peak of the total consumption and use it in setting the ToU tariff rates starting from the flat tariff. Then, the consumers' sensitivity to tariff change from flat to ToU is considered to identify the consumption change. The results show that using ToU instead of flat tariff, the peak is reduced in average by 5 to 7.5% and annual savings are around 4%. Also, by clustering the consumers a better allocation of the tariffs is possible. Thus, clustering is proposed considering the importance of the tariff allocation in Demand Side Management (DSM). INDEX TERMS Time-of-use tariff rates, contribution to consumption peak/off-peak, big data, machine learning, tariff elasticity. NOMENCLATURE Symbol Description C off cluster Consumption at off-peak hour for a cluster of consumers C peak cluster Consumption at peak hour for a cluster of consumers C% Consumption variation in percentage c off Contribution to consumption off-peak coefficient c peak Contribution to consumption peak coefficient C h Hourly consumption The associate editor coordinating the review of this manuscript and approving it for publication was Zhiwei Gao .

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Section: I Initial Consumption C Modmentioning

confidence: 99%

Section: I Initial Consumption C Modmentioning

confidence: 99%

Setting the Time-of-Use Tariff Rates With NoSQL and Machine Learning to a Sustainable Environment

Oprea

Bârã

2020

IEEE Access

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“…Economy 10 provides ten hours of off-peak electricity split between night, afternoon and evening; which makes it particularly useful for storage purposes), considerable opportunities to provide services to system operators and network operators will be missed, and the storage asset may not be profitable. Recent modelling has shown that home batteries operating according to time-of-use tariffs significantly miss out on the potential for peak shaving, and can even cause a "rebound peak" as large numbers of storage systems commence charging at the start of low tariff price periods [20]. This shows the need for smarter storage control, ideally with greater input from network operators.…”

Section: Des Technologies and Urban Energy Systemsmentioning

confidence: 99%

“…The prompt materials for the workshop were generated by the paper authors and other researchers in a wider research project (see http://sure-infrastructure.leeds.ac.uk/c-madens/ for further information) Most of the work that informed the prompt materials has been published separately [17,20,21,24,28] and the prompt material themselves are presented in full in the Supplementary Material File.…”

Section: Background Materials and Participantsmentioning

confidence: 99%

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What Makes Decentralised Energy Storage Schemes Successful? An Assessment Incorporating Stakeholder Perspectives

et al. 2020

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Decentralised energy storage is increasingly seen as being important for decarbonising local energy systems and the global market for such systems is expected to grow significantly. Several studies have looked into the technical development of decentralised energy storage systems, as well as examining how different business models can enable them to capture a variety of value streams. Recent work has also explored public perceptions of energy storage, yet so far there has been little focus on how the different dimensions affecting deployment interact together. Here, we present the result of a deliberative workshop which gathers stakeholders’ views and addresses how the interplay between these three dimensions affects successful deployment. Our approach is holistic and integrative and utilises a participatory decision-making methodology. The findings of the research add substantially to the understanding of how decentralised energy storage schemes should be implemented. The research reveals that there are many aspects that can help to either facilitate or impede a storage scheme, and stakeholders perceive multiple ways to engage with the deployment of the technology. We show that the following four principles could contribute to achieving success: maximizing simplicity and clarity; managing expectations, uncertainty and risk; generating benefits for the community; and the involvement of trusted actors.

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Integrating PV+Battery Residential Microgrids in Distribution Networks: How Is the Point of Common Coupling Agreed Upon?

Saviuc

Passel

Peremans

2020

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Time-of-use and time-of-export tariffs for home batteries: Effects on low voltage distribution networks

Cited by 51 publications

References 22 publications

Setting the Time-of-Use Tariff Rates With NoSQL and Machine Learning to a Sustainable Environment

Setting the Time-of-Use Tariff Rates With NoSQL and Machine Learning to a Sustainable Environment

What Makes Decentralised Energy Storage Schemes Successful? An Assessment Incorporating Stakeholder Perspectives

Integrating PV+Battery Residential Microgrids in Distribution Networks: How Is the Point of Common Coupling Agreed Upon?

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