The Experts below are selected from a list of 51408 Experts worldwide ranked by ideXlab platform
Ryan Hledik - One of the best experts on this subject based on the ideXlab platform.
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unlocking the 53 billion savings from Smart Meters in the eu how increasing the adoption of dynamic tariffs could make or break the eu s Smart grid investment
Energy Policy, 2010Co-Authors: Ahmad Faruqui, Dan Harris, Ryan HledikAbstract:We estimate the cost of installing Smart Meters in the EU to be [euro]51 billion, and that operational savings will be worth between [euro]26 and 41 billion, leaving a gap of [euro]10-25 billion between benefits and costs. Smart Meters can fill this gap because they enable the provision of dynamic pricing, which reduces peak demand and lowers the need for building and running expensive peaking power plants. The present value of savings in peaking infrastructure could be as high as [euro]67 billion for the EU if policy-makers can overcome barriers to consumers adopting dynamic tariffs, but only [euro]14 billion otherwise. We outline a number of ways to increase the adoption of dynamic tariffs.
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unlocking the 53 billion savings from Smart Meters in the eu how increasing the adoption of dynamic tariffs could make or break the eu s Smart grid investment
Energy Policy, 2010Co-Authors: Ahmad Faruqui, Dan Harris, Ryan HledikAbstract:We estimate the cost of installing Smart Meters in the EU to be [euro]51 billion, and that operational savings will be worth between [euro]26 and 41 billion, leaving a gap of [euro]10-25 billion between benefits and costs. Smart Meters can fill this gap because they enable the provision of dynamic pricing, which reduces peak demand and lowers the need for building and running expensive peaking power plants. The present value of savings in peaking infrastructure could be as high as [euro]67 billion for the EU if policy-makers can overcome barriers to consumers adopting dynamic tariffs, but only [euro]14 billion otherwise. We outline a number of ways to increase the adoption of dynamic tariffs.
Dima Alberg - One of the best experts on this subject based on the ideXlab platform.
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short term load forecasting in Smart Meters with sliding window based arima algorithms
Vietnam Journal of Computer Science, 2018Co-Authors: Dima AlbergAbstract:Forecasting of electricity consumption for residential and industrial customers is an important task providing intelligence to the Smart grid. Accurate forecasting should allow a utility provider to plan the resources as well as to take control actions to balance the supply and the demand of electricity. This paper presents two non-seasonal and two seasonal sliding window-based ARIMA (auto regressive integrated moving average) algorithms. These algorithms are developed for short-term forecasting of hourly electricity load at the district meter level. The algorithms integrate non-seasonal and seasonal ARIMA models with the OLIN (online information network) methodology. To evaluate our approach, we use a real hourly consumption data stream recorded by six Smart Meters during a 16-month period.
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short term load forecasting in Smart Meters with sliding window based arima algorithms
Asian Conference on Intelligent Information and Database Systems, 2017Co-Authors: Dima AlbergAbstract:Forecasting of electricity consumption for residential and industrial customers is an important task providing intelligence to the Smart grid. Accurate forecasting should allow a utility provider to plan the resources as well as to take control actions to balance the supply and the demand of electricity. This paper presents two non - seasonal and two seasonal sliding window-based ARIMA (Auto Regressive Integrated Moving Average) algorithms. These algorithms are developed for short-term forecasting of hourly electricity load. The algorithms integrate non - seasonal and seasonal ARIMA models with the OLIN (Online Information Network) methodology. To evaluate our approach, we use a real hourly consumption data stream recorded by six Smart Meters during a 16-month period.
Sookchi Yip - One of the best experts on this subject based on the ideXlab platform.
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an anomaly detection framework for identifying energy theft and defective Meters in Smart grids
International Journal of Electrical Power & Energy Systems, 2018Co-Authors: Sookchi Yip, Koksheik WongAbstract:Abstract Smart Meters are progressively deployed to replace its antiquated predecessor to measure and monitor consumers’ consumption in Smart grids. Although Smart Meters are equipped with encrypted communication and tamper-detection features, they are likely to be exposed to multiple cyber attacks. These Meters may be easily compromised to falsify meter readings, which increases the chances and diversifies the types of energy theft. To thwart energy fraud from Smart Meters, utility providers are identifying anomalous consumption patterns reported to operation centers by leveraging on consumers’ consumption data collected from advanced metering infrastructure. In this paper, we put forward a new anomaly detection framework to evaluate consumers’ energy utilization behavior for identifying the localities of potential energy frauds and faulty Meters. Metrics known as the loss factor and error term are introduced to estimate the amount of technical losses and capture the measurement noise, respectively in the distribution lines and transformers. The anomaly detection framework is then enhanced to detect consumers’ malfeasance and faulty Meters even when there are intermittent cheating and faulty equipment, improving its robustness. Results from both simulations and test rig show that the proposed framework can successfully locate fraudulent consumers and discover faulty Smart Meters.
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detection of energy theft and defective Smart Meters in Smart grids using linear regression
International Journal of Electrical Power & Energy Systems, 2017Co-Authors: Sookchi Yip, Koksheik Wong, W P Hew, Raphael C W PhaAbstract:The utility providers are estimated to lose billions of dollars annually due to energy theft. Although the implementation of Smart grids offers technical and social advantages, the Smart Meters deployed in Smart grids are susceptible to more attacks and network intrusions by energy thieves as compared to conventional mechanical Meters. To mitigate non-technical losses due to electricity thefts and inaccurate Smart Meters readings, utility providers are leveraging on the energy consumption data collected from the advanced metering infrastructure implemented in Smart grids to identify possible defective Smart Meters and abnormal consumers’ consumption patterns. In this paper, we design two linear regression-based algorithms to study consumers’ energy utilization behavior and evaluate their anomaly coefficients so as to combat energy theft caused by meter tampering and detect defective Smart Meters. Categorical variables and detection coefficients are also introduced in the model to identify the periods and locations of energy frauds as well as faulty Smart Meters. Simulations are conducted and the results show that the proposed algorithms can successfully detect all the fraudulent consumers and discover faulty Smart Meters in a neighborhood area network.
Walmi Freitas - One of the best experts on this subject based on the ideXlab platform.
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low voltage zones to support fault location in distribution systems with Smart Meters
IEEE Transactions on Smart Grid, 2017Co-Authors: Fernanda C L Trindade, Walmi FreitasAbstract:This paper proposes to combine the voltage monitoring capability of Smart Meters with impedance-based fault location methods to provide an efficient fault location approach improving service restoration. The first step of the proposed methodology is to apply an impedance-based method to obtain a rough estimation of fault location. Since the result is an estimated distance to the fault, multiple branches can be indicated due to the typical distribution systems topologies. Therefore, the challenge is: how to recognize the actual fault location? To solve this problem, voltage measurements from Smart Meters are used to build the low voltage zones (LVZs). The main contributions of the proposed fault location technique are to decrease the multiple estimations associated with impedance-based methods, to propose a systematic approach to build the LVZs, and to explore the presence of Smart Meters for fault location. The proposed method was tested through intensive and extensive simulations in a real distribution system, proving its efficiency.
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an event window based load monitoring technique for Smart Meters
Web Science, 2012Co-Authors: Ming Dong, Paulo Cesar Magalhaes Meira, Walmi FreitasAbstract:The data collected by Smart Meters contain a lot of useful information. One potential use of the data is to track the energy consumptions and operating statuses of major home appliances. The results will enable homeowners to make sound decisions on how to save energy and how to participate in demand response programs. This paper presents a new method to breakdown the total power demand measured by a Smart meter to those used by individual appliances. A unique feature of the proposed method is that it utilizes diverse signatures associated with the entire operating window of an appliance for identification. As a result, appliances with complicated middle process can be tracked. A novel appliance registration device and scheme is also proposed to automate the creation of appliance signature database and to eliminate the need of massive training before identification. The software and system have been developed and deployed to real houses in order to verify the proposed method.
Ahmad Faruqui - One of the best experts on this subject based on the ideXlab platform.
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unlocking the 53 billion savings from Smart Meters in the eu how increasing the adoption of dynamic tariffs could make or break the eu s Smart grid investment
Energy Policy, 2010Co-Authors: Ahmad Faruqui, Dan Harris, Ryan HledikAbstract:We estimate the cost of installing Smart Meters in the EU to be [euro]51 billion, and that operational savings will be worth between [euro]26 and 41 billion, leaving a gap of [euro]10-25 billion between benefits and costs. Smart Meters can fill this gap because they enable the provision of dynamic pricing, which reduces peak demand and lowers the need for building and running expensive peaking power plants. The present value of savings in peaking infrastructure could be as high as [euro]67 billion for the EU if policy-makers can overcome barriers to consumers adopting dynamic tariffs, but only [euro]14 billion otherwise. We outline a number of ways to increase the adoption of dynamic tariffs.
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unlocking the 53 billion savings from Smart Meters in the eu how increasing the adoption of dynamic tariffs could make or break the eu s Smart grid investment
Energy Policy, 2010Co-Authors: Ahmad Faruqui, Dan Harris, Ryan HledikAbstract:We estimate the cost of installing Smart Meters in the EU to be [euro]51 billion, and that operational savings will be worth between [euro]26 and 41 billion, leaving a gap of [euro]10-25 billion between benefits and costs. Smart Meters can fill this gap because they enable the provision of dynamic pricing, which reduces peak demand and lowers the need for building and running expensive peaking power plants. The present value of savings in peaking infrastructure could be as high as [euro]67 billion for the EU if policy-makers can overcome barriers to consumers adopting dynamic tariffs, but only [euro]14 billion otherwise. We outline a number of ways to increase the adoption of dynamic tariffs.
