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Smart grid

About: Smart grid is a research topic. Over the lifetime, 37536 publications have been published within this topic receiving 627844 citations. The topic is also known as: intelligent grid.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors investigated the impact of DERs and effect of wind, price and demand uncertainties on total hub operation costs and hub reliability and also on which technology most be operated.

218 citations

Journal ArticleDOI
TL;DR: A hybrid ensemble deep learning framework is proposed to forecast short-term photovoltaic power generation in a time series manner and adopted the attention mechanism for the two LSTM neural networks to adaptively focus on input features that are more significant in forecasting.
Abstract: Photovoltaic power generation forecasting is an important topic in the field of sustainable power system design, energy conversion management, and smart grid construction. Difficulties arise while the generated PV power is usually unstable due to the variability of solar irradiance, temperature, and other meteorological factors. In this paper, a hybrid ensemble deep learning framework is proposed to forecast short-term photovoltaic power generation in a time series manner. Two LSTM neural networks are employed working on temperature and power outputs forecasting, respectively. The forecasting results are flattened and combined with a fully connected layer to enhance forecasting accuracy. Moreover, we adopted the attention mechanism for the two LSTM neural networks to adaptively focus on input features that are more significant in forecasting. Comprehensive experiments are conducted with recently collected real-world photovoltaic power generation datasets. Three error metrics were adopted to compare the forecasting results produced by attention LSTM model with state-of-art methods, including the persistent model, the auto-regressive integrated moving average model with exogenous variable (ARIMAX), multi-layer perceptron (MLP), and the traditional LSTM model in all four seasons and various forecasting horizons to show the effectiveness and robustness of the proposed method.

218 citations

Journal ArticleDOI
TL;DR: Narrowband IoT (NB-IoT), as a licensed LPWAN technology, is developed based on the existing long-term evolution specifications and facilities, and henceforth can be viewed as a promising candidate for smart grid communications.
Abstract: The low power wide area network (LPWAN) technologies, which is now embracing a booming era with the development in the Internet of Things (IoT), may offer a brand new solution for current smart grid communications due to their excellent features of low power, long range, and high capacity. The mission-critical smart grid communications require secure and reliable connections between the utilities and the devices with high quality of service (QoS). This is difficult to achieve for unlicensed LPWAN technologies due to the crowded license-free band. Narrowband IoT (NB-IoT), as a licensed LPWAN technology, is developed based on the existing long-term evolution specifications and facilities. Thus, it is able to provide cellular-level QoS, and henceforth can be viewed as a promising candidate for smart grid communications. In this paper, we introduce NB-IoT to the smart grid and compare it with the existing representative communication technologies in the context of smart grid communications in terms of data rate, latency, range, etc. The overall requirements of communications in the smart grid from both quantitative and qualitative perspectives are comprehensively investigated and each of them is carefully examined for NB-IoT. We further explore the representative applications in the smart grid and analyze the corresponding feasibility of NB-IoT. Moreover, the performance of NB-IoT in typical scenarios of the smart grid communication environments, such as urban and rural areas, is carefully evaluated via Monte Carlo simulations.

218 citations

01 Jan 2011
TL;DR: In this paper, the authors provide a description of the current conventional electric energy system and identify the key areas that must change in order to provide the intelligence and control necessary to convert to the safe, secure, and efficient Smart Grid of the future.
Abstract: Three dominant factors are impacting future electric systems of the world: governmental policies at both federal and state levels, customer efficiency needs, and new intelligent computer software and hardware technologies. In addition, environmental concerns are driving the entire energy system to efficiency, conservation, and renewable sources of electricity. Customers are becoming more proactive and are being empowered to engage in energy consumption decisions affecting their day-to-day lives. At the same time, energy needs are continually expanding. For example, consumer participation will soon include extensive use of electric vehicles (both cars and trucks), remote control of in-home appliances to promote energy conservation, ownership of distributed generation from ever more renewable energy sources, and management of electricity storage to locally match supply to demand. The availability of new technologies such as distributed sensors, two-way secure communication, advanced software for data management, and intelligent and autonomous controllers has opened up new opportunities for changing the energy system. For instance, while networking technologies and systems have been greatly enhanced, the Smart Grid faces challenges in terms of reliability and security in both wired and wireless communication environments. In particular, smart home appliances represent a major part of the Smart Grid vision, which aims at increasing energy efficiency. To achieve this goal, home appliances need to communicate with entities and players in other Smart Grid domains via home area networks. Therefore, the electric system of the future will address all these needs and concerns by using new advanced technologies to create a smarter, more efficient and sustainable grid. Although many different definitions have been proposed for the Smart Grid, in most cases, the users have chosen narrowly focused definitions related to their specific applications and local needs. The main objective of this special issue is to report on some, if not all, of the technical challenges posed by this conversion. While acknowledging its limited coverage, this special issue offers a range of valuable contributions. For the benefit of readers before beginning your excursion, we first provide a description of the current conventional electric energy system. We then identify the key areas that must change in order to provide the intelligence and control necessary to convert to the safe, secure, and efficient Smart Grid of the future.

218 citations

Journal ArticleDOI
TL;DR: An in depth review on the application characteristics and traffic requirements of several emerging smart grid applications and highlights some of the key research challenges present in this arena are offered.

217 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
20231,334
20223,167
20212,356
20202,968
20193,278