The Experts below are selected from a list of 10296 Experts worldwide ranked by ideXlab platform
Catherine D Wolfram - One of the best experts on this subject based on the ideXlab platform.
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Appliance ownership and aspirations among electric grid and home solar households in rural kenya
The American Economic Review, 2016Co-Authors: Edward Miguel, Catherine D WolframAbstract:In Sub-Saharan Africa, there are active debates about whether increases in energy access should be driven by investments in electric grid infrastructure or small-scale “home solar” systems (e.g., solar lanterns and solar home systems). We summarize the results of a household Electrical Appliance survey and describe how households in rural Kenya differ in terms of Appliance ownership and aspirations. Our data suggest that home solar is not a substitute for grid power. Furthermore, the environmental advantages of home solar are likely to be relatively small in countries like Kenya, where grid power is primarily derived from non-fossil fuel sources
Venkata Dinavahi - One of the best experts on this subject based on the ideXlab platform.
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Parallel stochastic programming for energy storage management in smart grid with probabilistic renewable generation and load models
Iet Renewable Power Generation, 2019Co-Authors: Yue Wang, Hao Liang, Venkata DinavahiAbstract:Renewable power generation combined with energy storage (ES) is expected to bring enormous economical and environmental benefits to the future smart grid. However, the ES management in smart grid is facing significant technical challenges due to the volatile nature of renewable energy sources and the buffering effect of ES units. The challenges are further complicated by the increasing size and complexity of the system, as well as the consideration of random usage patterns of Electrical Appliances by customers. To address these challenges, this study proposes a parallel decomposition method for large-scale stochastic programming in a distribution system with renewable energy sources and ES units. By leveraging nested decomposition, the problem can be converted into independent sub-problems with a series of time periods. In addition, the reformulated problem is fully parallel for speed up in execution. The performance of the proposed method is evaluated based on the IEEE 4-bus and 33-bus test distribution systems with real photovoltaic generation and Electrical Appliance usage data. The case study demonstrates that the proposed scheme can substantially reduce the system operation cost, with low computational complexity.
Ridha Bouallegue - One of the best experts on this subject based on the ideXlab platform.
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Dynamic IFFSM Modeling Using IFHMM-Based Bayesian Non-parametric Learning for Energy Disaggregation in Smart Solar Home System
Broadband Communications Networks and Systems, 2019Co-Authors: Kalthoum Zaouali, Mohamed Lassaad Ammari, Amine Chouaieb, Ridha BouallegueAbstract:Recently, the analysis and recognition of each Appliance’s energy consumption are fundamental in smart homes and smart buildings systems. Our paper presents a novel Non-Intrusive Load Monitoring (NILM) recognition method based on Bayesian Non-Parametric (BNP) learning approach to solve the problem of energy disaggregation for smart Solar Home System (SHS). Several researches assumed that there is prior information about the household Appliances in order to restrict those that do not hold the maximum expectation for inference. Therefore, to deal with the unknown number of Electrical Appliances in a SHS, we have adapted a dynamic Infinite Factorial Hidden Markov Model (IFHMM) -based Infinite Factorial Finite State Machine (IFFSM) to our NILM times-series modeling as an unsupervised BNP learning method. Our suggested method can grip with few or nappropriate learning data as well as to standardize Electrical Appliance modeling. Our proposed method outperforms FHMM-based FSM modeling results illustrated in literature.
Edward Miguel - One of the best experts on this subject based on the ideXlab platform.
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Appliance ownership and aspirations among electric grid and home solar households in rural kenya
The American Economic Review, 2016Co-Authors: Edward Miguel, Catherine D WolframAbstract:In Sub-Saharan Africa, there are active debates about whether increases in energy access should be driven by investments in electric grid infrastructure or small-scale “home solar” systems (e.g., solar lanterns and solar home systems). We summarize the results of a household Electrical Appliance survey and describe how households in rural Kenya differ in terms of Appliance ownership and aspirations. Our data suggest that home solar is not a substitute for grid power. Furthermore, the environmental advantages of home solar are likely to be relatively small in countries like Kenya, where grid power is primarily derived from non-fossil fuel sources
Tomohiro Sato - One of the best experts on this subject based on the ideXlab platform.
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Decision-making in Electrical Appliance use in the home
Energy Policy, 2008Co-Authors: Yoshihiro Yamamoto, Akihiko Suzuki, Yasuhiro Fuwa, Tomohiro SatoAbstract:This paper presents the results of a survey as well as an argument from the viewpoint of behavioral economics with the aim of clarifying how consumers make decisions about Electrical Appliance use in the home. A survey of consumers showed that most have little awareness of the energy efficiency of Appliances, the price of the services produced by Electrical Appliances, or electricity rates. These findings indicate that price does not function as a signal in electricity consumption through Electrical Appliance use. Rather, we found that consumer decision-making in electricity consumption is dependent on the characteristics of the particular Electrical Appliances they use. Additionally, we argue that the payment system for home electricity consumption plays an important role in decision-making, causing biases due to aspects of human psychology discussed here in terms of satisficing and heuristics, payment decoupling, and budgeting. We conclude that decision-making about Electrical Appliance use and electricity consumption in the home is not always rational and is affected both by the particular characteristics of Appliances and the payment system for electricity consumption along with human psychology.