A new technique for short-term residential electric load forecasting including weather and lifestyle influences

Noureddine, A.H.; Alouani, A.T.; Chandrasekaran, Aravind

doi:10.1109/mwscas.1992.271029

Cited by 6 publications

(4 citation statements)

References 14 publications

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“…While focused on methods to produce short-term residential forecasts, elements of Noureddine et al (1992) 8 apply to longer-term modeling. Loads are split between weather-and non-weather-dependent categories.…”

Section: Residential Load Modelingmentioning

confidence: 99%

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Enhanced Reliability of Photovoltaic Systems with Energy Storage and Controls

Manz¹,

Schelenz²,

Chandra³

et al. 2008

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PrefaceNow is the time to plan for the integration of significant quantities of distributed renewable energy into the electricity grid. Concerns about climate change, the adoption of state-level renewable portfolio standards and incentives, and accelerated cost reductions are driving steep growth in U.S. renewable energy technologies. The number of distributed solar photovoltaic (PV) installations, in particular, is growing rapidly. As distributed PV and other renewable energy technologies mature, they can provide a significant share of our nation's electricity demand. However, as their market share grows, concerns about potential impacts on the stability and operation of the electricity grid may create barriers to their future expansion.To facilitate more extensive adoption of renewable distributed electric generation, the U.S. Department of Energy launched the Renewable Systems Interconnection (RSI) study during the spring of 2007. This study addresses the technical and analytical challenges that must be addressed to enable high penetration levels of distributed renewable energy technologies. Because integration-related issues at the distribution system are likely to emerge first for PV technology, the RSI study focuses on this area. A key goal of the RSI study is to identify the research and development needed to build the foundation for a high-penetration renewable energy future while enhancing the operation of the electricity grid.The RSI study consists of 15 reports that address a variety of issues related to distributed systems technology development; advanced distribution systems integration; system-level tests and demonstrations; technical and market analysis; resource assessment; and codes, standards, and regulatory implementation. The RSI reports are: Addressing grid-integration issues is a necessary prerequisite for the long-term viability of the distributed renewable energy industry, in general, and the distributed PV industry, in particular. The RSI study is one step on this path. The Department of Energy is also working with stakeholders to develop a research and development plan aimed at making this vision a reality. iv AcknowledgmentsThe authors would like to acknowledge Ray George from NREL for providing insolation and temperature data for regions of the United States. The authors would also like to acknowledge the contribution of Tom Short from EPRI. Tom provided the GE team with detailed reliability data for two utilities in the United States. The project team would also like to thank the following individuals for their contributions to this study:1. Jim McMahon of LBL for appliance data models, start/end time estimation.2. Craig Cornelius for the interaction needed to obtain load modeling data and information.3. Robert Delmerico of GE Global Research for providing data from studies on load modeling in residential communities.4. Lawrence Berkley Labs for providing load shapes for several appliances, distinguishing week and weekend days.5. Patrick G. McElhaney (GE C&I) for providing data on av...

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Section: Residential Load Modelingmentioning

confidence: 99%

“…For example, a dishwasher is reported to be in operation 8 Where the first factor is the average dishwasher power consumption, the second factor is the average use in hours per month. Lastly, these factors are multiplied by months in a year to obtain the yearly kWh usage.…”

Section: Generate Appliance Runtime Valuesmentioning

confidence: 99%

Enhanced Reliability of Photovoltaic Systems with Energy Storage and Controls

Manz¹,

Schelenz²,

Chandra³

et al. 2008

View full text Add to dashboard Cite

show abstract

“…The use of measured electricity consumption data in combination with a physical model has previously been discussed [13]. It has been proposed to include both a weatherbased component and a lifestyle component in the modeling tool.…”

Section: Bottom-up Approachmentioning

confidence: 99%

“…Each residential customer could, according to previous work [13], be represented by two components. In regards to an individual electricity consumption series, a three-component model seems appropriate, where the base load constitutes the third component.…”

Section: Bottom-up Approachmentioning

confidence: 99%

Automatic Meter Reading Provides Opportunities for New Prognosis and Simulation Methods

Wallin

Dotzauer

Thorin

et al. 2007

2007 IEEE Lausanne Power Tech

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The use of top-down models for load forecasting purposes has been a dominating method over the last few decades. However, there is now concern regarding the performance of topdown models, e.g. in situations with unusual weather conditions, due to the lack of historical data. This paper considers an alternative bottom-up approach with a stronger relation to the laws of physics. Electrical companies in Sweden are installing automatic meter reading systems for their customers, and using consumption data gives new possibilities for adapting the modeling parameters in a bottom-up model for each customer. A method for analyzing individual consumption series is suggested, where different periods in time are used to divide and identify different parts of the electricity load: base load, heat load and household loads. A review of previous work is presented, and suggestions on how to link load analysis to construction parameters for an individual building are proposed.

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Decomposition of Aggregate Electricity Demand into the Seasonal-Thermal Components for Demand-Side Management Applications in “Smart Grids”

Paisios

Djokić

2017

Data Analytics for Renewable Energy Integration

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A new technique for short-term residential electric load forecasting including weather and lifestyle influences

Cited by 6 publications

References 14 publications

Enhanced Reliability of Photovoltaic Systems with Energy Storage and Controls

Enhanced Reliability of Photovoltaic Systems with Energy Storage and Controls

Automatic Meter Reading Provides Opportunities for New Prognosis and Simulation Methods

Decomposition of Aggregate Electricity Demand into the Seasonal-Thermal Components for Demand-Side Management Applications in “Smart Grids”

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