A multi-dimension clustering-based method for renewable energy investment planning

Liu, Aaron; Miller, Wendy; Cholette, Michael E.; Ledwich, Gerard; Crompton, Glenn; Li, Yong

doi:10.1016/j.renene.2021.03.056

Cited by 19 publications

(9 citation statements)

References 26 publications

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“…Sun et al [78] stated that investment decisions considering every operating period are unrealistic. Liu et al [79] and Härtel et al [80] applied clustering to representative data for determining investment decisions. Palupi et al [81] compared clustering algorithms to choose preferred market assets.…”

Section: State Of Researchmentioning

confidence: 99%

Business models for local energy market and circular economy establishment in municipalities: A case study in an Austrian municipality

Maldet,

Loschan,

Schwabeneder

et al. 2023

Heliyon

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Section: State Of Researchmentioning

confidence: 99%

Business models for local energy market and circular economy establishment in municipalities: A case study in an Austrian municipality

Maldet,

Loschan,

Schwabeneder

et al. 2023

Heliyon

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“…The initial investment would rapidly increase within a certain range. Liu et al [159] proposed the multi-dimensional objective-oriented clustering (MOC) method for planning sustainable energy investment with various options for new forms of energy investment. The data of an actual residential community load profile were analyzed under both energy-consumption-only tariffs and coupled-energy-demand tariffs.…”

Section: Economic Assessment Of Sustainable Energymentioning

confidence: 99%

Recent Advances in Low-Carbon and Sustainable, Efficient Technology: Strategies and Applications

et al. 2022

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The COVID-19 pandemic has had a significant impact on the supply chains of traditional fossil fuels. According to a report by the International Energy Agency (IEA) from 2020, oil-refining activity fell by more than the IEA had anticipated. It was also assumed that the demand in 2021 would likely be 2.6 million bpd below the 2019 levels. However, renewable markets have shown strong resilience during the crisis. It was determined that renewables are on track to meet 80% of the growth in electricity demand over the next 10 years and that sustainable energy will act as the primary source of electricity production instead of coal. On the other hand, the report also emphasized that measures for reducing environmental pollution and CO2 emissions are still insufficient and that significant current investments should be further expanded. The Sustainable Development of Energy, Water and Environment Systems (SDEWES) conference series is dedicated to the advancement and dissemination of knowledge on methods, policies and technologies for improving the sustainability of development by decoupling growth from the use of natural resources. The 15th SDEWES conference was held online from 1–5 September 2020; more than 300 reports with 7 special sections were organized on the virtual conference platform. This paper presents the major achievements of the recommended papers in the Special Issue of Energies. Additionally, related studies connected to the above papers published in the SDEWES series are also introduced, including the four main research fields of energy saving and emission reduction, renewable energy applications, the development of district heating systems, and the economic assessment of sustainable energy.

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“…To identify typical demand profiles, Gaussian Mixture Model clustering method (GMM) is used [36,37]. Critical evaluation can be then conducted to examine changes to typical demand profiles, magnitudes of demands and peak demand timing.…”

Section: Typical Demand Profilesmentioning

confidence: 99%

“…Another way to examine change of energy use pattern is by studying how typical demand profiles look like [22]. Clustering algorithms can be quite helpful in identifying typical profiles, such as k-means clustering [23], SPSS 2-step technique (Statistical Package for Social Science software) [24] and Gaussian Mixture Model clustering [25]. Once typical profiles are identified, visualizations can show how energy is typically used across an interval, such as a day.…”

Section: Introductionmentioning

confidence: 99%

Aged Care Energy Use and Peak Demand Change in the COVID-19 Year: Empirical Evidence from Australia

Liu

Miller

Chiou³

et al. 2021

Buildings

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Aged care communities have been under the spotlight since the beginning of 2020. Energy is essential to ensure reliable operation and quality care provision in residential aged care communities (RAC). The aim of this study is to determine how RAC’s yearly energy use and peak demand changed in Australia and what this might mean for RAC design, operation and energy asset investment and ultimately in the healthcare plan for elderly residents. Five years of electricity demand data from four case study RACs in the same climate zone are analyzed. Statistical tools are used to analyze the data, and a clustering algorithm is used to identify typical demand profiles. A number of energy key performance indicators (KPIs) are evaluated, highlighting their respective benefits and limitations. The results show an average 8% reduction for yearly energy use and 7% reduction for yearly peak demands in the COVID-19 year compared with the average of the previous four years. Typical demand profiles for the four communities were mostly lower in the pandemic year. Despite these results, the KPI analysis shows that, for these four communities, outdoor ambient temperature remains a very significant correlation factor for energy use.

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A multi-dimension clustering-based method for renewable energy investment planning

Cited by 19 publications

References 26 publications

Business models for local energy market and circular economy establishment in municipalities: A case study in an Austrian municipality

Business models for local energy market and circular economy establishment in municipalities: A case study in an Austrian municipality

Recent Advances in Low-Carbon and Sustainable, Efficient Technology: Strategies and Applications

Aged Care Energy Use and Peak Demand Change in the COVID-19 Year: Empirical Evidence from Australia

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