Topic
Energy planning
About: Energy planning is a research topic. Over the lifetime, 2732 publications have been published within this topic receiving 51619 citations.
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TL;DR: A review of the studies that developed data-driven building energy consumption prediction models, with a particular focus on reviewing the scopes of prediction, the data properties and the data preprocessing methods used, the machine learning algorithms utilized for prediction, and the performance measures used for evaluation is provided in this paper.
Abstract: Energy is the lifeblood of modern societies. In the past decades, the world's energy consumption and associated CO 2 emissions increased rapidly due to the increases in population and comfort demands of people. Building energy consumption prediction is essential for energy planning, management, and conservation. Data-driven models provide a practical approach to energy consumption prediction. This paper offers a review of the studies that developed data-driven building energy consumption prediction models, with a particular focus on reviewing the scopes of prediction, the data properties and the data preprocessing methods used, the machine learning algorithms utilized for prediction, and the performance measures used for evaluation. Based on this review, existing research gaps are identified and future research directions in the area of data-driven building energy consumption prediction are highlighted.
1,015 citations
TL;DR: In this article, the authors review thermal comfort research work and discuss the implications for building energy efficiency, and propose to increase the summer set point temperature in order to save energy in buildings.
992 citations
TL;DR: In this paper, an extensive review in the sphere of sustainable energy has been performed by utilizing multiple criteria decision making (MCDM) technique and future prospects in this area are discussed.
Abstract: In the current era of sustainable development, energy planning has become complex due to the involvement of multiple benchmarks like technical, social, economic and environmental. This in turn puts major constraints for decision makers to optimize energy alternatives independently and discretely especially in case of rural communities. In addition, topographical limitations concerning renewable energy systems which are mostly distributed in nature, the energy planning becomes more complicated. In such cases, decision analysis plays a vital role for designing such systems by considering various criteria and objectives even at disintegrated levels of electrification. Multiple criteria decision making (MCDM) is a branch of operational research dealing with finding optimal results in complex scenarios including various indicators, conflicting objectives and criteria. This tool is becoming popular in the field of energy planning due to the flexibility it provides to the decision makers to take decisions while considering all the criteria and objectives simultaneously. This article develops an insight into various MCDM techniques, progress made by considering renewable energy applications over MCDM methods and future prospects in this area. An extensive review in the sphere of sustainable energy has been performed by utilizing MCDM technique.
983 citations
01 May 2016
TL;DR: The U.S. Energy Information Administration (EIA) as discussed by the authors is a statistical and analytical agency within the United States Department of Energy that produces data, analyses, and forecasts independent of approval by any other officer or employee.
Abstract: This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other federal agencies.
718 citations
TL;DR: In this paper, a review paper on energy modeling will help the energy planners, researchers and policy makers widely, and an attempt has been made to understand and review the various emerging issues related to the energy modeling.
Abstract: Energy is a vital input for social and economic development of any nation. With increasing agricultural and industrial activities in the country, the demand for energy is also increasing. Formulation of an energy model will help in the proper allocation of widely available renewable energy sources such as solar, wind, bioenergy and small hydropower in meeting the future energy demand in India. During the last decade several new concepts of energy planning and management such as decentralized planning, energy conservation through improved technologies, waste recycling, integrated energy planning, introduction of renewable energy sources and energy forecasting have emerged. In this paper an attempt has been made to understand and review the various emerging issues related to the energy modeling. The different types of models such as energy planning models, energy supply–demand models, forecasting models, renewable energy models, emission reduction models, optimization models have been reviewed and presented. Also, models based on neural network and fuzzy theory have been reviewed and discussed. The review paper on energy modeling will help the energy planners, researchers and policy makers widely.
670 citations