A Widespread Review of Smart Grids Towards Smart Cities

Farmanbar, Mina; Parham, Kiyan; Arild, Øystein; Rong, Chunming

doi:10.3390/en12234484

Cited by 95 publications

(31 citation statements)

References 102 publications

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“…For example, in [130], an energy storage system is combined with the classical positive-sequence control strategy and the threephase damping control strategy to provide insight into power quality. A transversal review between smart grid and smart city framework is given in [131].…”

Section: F New Energy Demand and Deliverymentioning

confidence: 99%

Context Aware Control Systems: An Engineering Applications Perspective

et al. 2020

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Cyber-physical systems revolve around context awareness, empowering objective-oriented services, products and operations based on real data. Self-aware and self-control systems are core elements in the Industry 4.0 framework towards self-sustainable adaptive manufacturing and personalized services. This development is witnessed by the context-aware pervasive assistance to users and machines in decisions making process for optimizing product performance and economic yield. While integration of the virtual and the physical world entails smart sensors communication and complex data analytics, it relies on artificial intelligence tools to manage process operations. The objective of the article is to create awareness that systems & control community must address theoretical and practical aspects from a larger perspective. Context aware control is emerging as a natural solution to maximize the use of available sensing instrumentation and the relatively low cost data logging, i.e. an important source for extracting information, interpreting and using context information and adapt its functionality to the current context of use. This article presents a concise overview of applications where context aware systems and control methodologies are relevant in the seven societal challenges acknowledged by European policy-makers: Digital Society;

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Section: F New Energy Demand and Deliverymentioning

confidence: 99%

Context Aware Control Systems: An Engineering Applications Perspective

et al. 2020

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“…This approach could significantly reduce transmission loss and increase system efficiency [2,3]. The microgrid concept is one of the DG implementation outcomes, which aims to ensure the optimal power supply to connected loads [4]. Integration of renewable energy sources like solar and wind in microgrids ensures the mitigation of environmental effects.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of a Hybrid Nanogrid/Microgrid: Application to Desert Camps in Hafr Al-Batin

et al. 2021

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This paper presents an optimal design for a nanogrid/microgrid for desert camps in the city of Hafr Al-Batin in Saudi Arabia. The camps were designed to operate as separate nanogrids or to operate as an interconnected microgrid. The hybrid nanogrid/microgrid considered in this paper consists of a solar system, storage batteries, diesel generators, inverter, and load components. To offer the designer/operator various choices, the problem was formulated as a multi-objective optimization problem considering two objective functions, namely: the cost of electricity (COE) and the loss of power supply probability (LPSP). Furthermore, various component models were implemented, which offer a variety of equipment compilation possibilities. The formulated problem was then solved using the multi-objective evolutionary algorithm, based on both dominance and decomposition (MOEA/DD). Two cases were investigated corresponding to the two proposed modes of operation, i.e., nanogrid operation mode and microgrid operation mode. The microgrid was designed considering the interconnection of four nanogrids. The obtained Pareto front (PF) was reported for each case and the solutions forming this front were discussed. Based on this investigation, the designer/operator can select the most appropriate solution from the available set of solutions using his experience and other factors, e.g., budget, availability of equipment and customer-specific requirements. Furthermore, to assess the quality of the solutions found using the MOEA/DD, three different methods were used, and their results compared with the MOEA/DD. It was found that the MOEA/DD obtained better results (nondominated solutions), especially for the microgrid operation mode.

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“…High-resolution data generated by smart meters, on the other hand, provide suppliers with several controlling functions such as power quality monitoring and power loss identification. Moreover, it opens many doors of opportunities in electricity load analysis such as load forecasting with high accuracy at lower aggregation levels [3,4].…”

Section: Introductionmentioning

confidence: 99%

Short-Term Load Forecasting Using Smart Meter Data: A Generalization Analysis

et al. 2020

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Short-term load forecasting ensures the efficient operation of power systems besides affording continuous power supply for energy consumers. Smart meters that are capable of providing detailed information on buildings energy consumption, open several doors of opportunity to short-term load forecasting at the individual building level. In the current paper, four machine learning methods have been employed to forecast the daily peak and hourly energy consumption of domestic buildings. The utilized models depend merely on buildings historical energy consumption and are evaluated on the profiles that were not previously trained on. It is evident that developing data-driven models lacking external information such as weather and building data are of great importance under the situations that the access to such information is limited or the computational procedures are costly. Moreover, the performance evaluation of the models on separated house profiles determines their generalization ability for unseen consumption profiles. The conducted experiments on the smart meter data of several UK houses demonstrated that if the models are fed with sufficient historical data, they can be generalized to a satisfactory level and produce quite accurate results even if they only use past consumption values as the predictor variables. Furthermore, among the four applied models, the ones based on deep learning and ensemble techniques, display better performance in predicting daily peak load consumption than those of others.

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A Widespread Review of Smart Grids Towards Smart Cities

Cited by 95 publications

References 102 publications

Context Aware Control Systems: An Engineering Applications Perspective

Context Aware Control Systems: An Engineering Applications Perspective

Multi-Objective Optimization of a Hybrid Nanogrid/Microgrid: Application to Desert Camps in Hafr Al-Batin

Short-Term Load Forecasting Using Smart Meter Data: A Generalization Analysis

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