scholarly journals Component-Based Modelling for Scalable Smart City Systems Interoperability: A Case Study on Integrating Energy Demand Response Systems

Sensors ◽  
2016 ◽  
Vol 16 (11) ◽  
pp. 1810 ◽  
Author(s):  
Esther Palomar ◽  
Xiaohong Chen ◽  
Zhiming Liu ◽  
Sabita Maharjan ◽  
Jonathan Bowen
Keyword(s):  
Demand Response ◽  
Smart City ◽  
Energy Demand ◽  
Response Systems ◽  
City Systems

scholarly journals Management and Activation of Energy Flexibility at Building and Market Level: A Residential Case Study

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1188 ◽  
Author(s):  
Paolo Taddeo ◽  
Alba Colet ◽  
Rafael E. Carrillo ◽  
Lluc Casals Canals ◽  
Baptiste Schubnel ◽  
...  
Keyword(s):  
Demand Response ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Test Site ◽  
Electricity Sector ◽  
Energy Sources ◽  
Multi Level ◽  
The Difference ◽  
Real Test

The electricity sector foresees a significant change in the way energy is generated and distributed in the coming years. With the increasing penetration of renewable energy sources, smart algorithms can determine the difference about how and when energy is produced or consumed by residential districts. However, managing and implementing energy demand response, in particular energy flexibility activations, in real case studies still presents issues to be solved. This study, within the framework of the European project “SABINA H2020”, addresses the development of a multi-level optimization algorithm that has been tested in a semi-virtual real-time configuration. Results from a two-day test show the potential of building’s flexibility and highlight its complexity. Results show how the first level algorithm goal to reduce the energy injected to the grid is accomplished as well as the energy consumption shift from nighttime to daytime hours. As conclusion, the study demonstrates the feasibility of such kind of configurations and puts the basis for real test site implementation.

scholarly journals Information Integration in a Smart City System—A Case Study on Air Pollution Removal by Green Infrastructure through a Vehicle Smart Routing System

2020 ◽  
Vol 12 (12) ◽  
pp. 5099
Author(s):  
Jules Muvuna ◽  
Tuleen Boutaleb ◽  
Slobodan B. Mickovski ◽  
Keith Baker ◽  
Ghoreyshi Seyed Mohammad ◽  
...  
Keyword(s):  
Air Pollution ◽  
Information Integration ◽  
Green Infrastructure ◽  
System Integration ◽  
Smart City ◽  
Integrated System ◽  
City System ◽  
Travel Decisions ◽  
City Systems

Over the past few years, the ‘‘smart city’’ concept has emerged as a new trend to answer challenging issues related to urban development. Transformation of a city system into a smart system is meant to improve the quality of life for its people and their way of living, its environment, economy, transport, and governance. Due to benefits associated with the concept of the smart city and associated implementation challenges, traditional city systems have been undergoing transformation into smart city systems. However, observed approaches of transformation presented disconnected and fragmented city systems that usually hamper the interaction of city subsystems with the efficient and environmentally friendly urban environment. This work emphasizes the systematic view of a city system and proposes a novel method of smart city system integration. The results of our study show that in a smart city environment, where ecosystem services are valorised, air pollution emitted by vehicles can be removed by taking into consideration information related to air pollution reduction. A case study is presented to demonstrate that, with an integrated system, information outputs on travel decisions are different and more valuable. The case study explores the operability of the system, its limitations, and potential future improvements.

SenCity – Evaluating Users’ Experiences of Intelligent Lighting for Well-Being in Smart Cities

2018 ◽  
pp. 60-67
Author(s):  
Henrika Pihlajaniemi ◽  
Anna Luusua ◽  
Eveliina Juntunen
Keyword(s):  
Case Studies ◽  
Smart City ◽  
Smart Cities ◽  
Well Being ◽  
Evaluation Methods ◽  
Data Analyses ◽  
Sense Of Security ◽  
System Data

This paper presents the evaluation of usersХ experiences in three intelligent lighting pilots in Finland. Two of the case studies are related to the use of intelligent lighting in different kinds of traffic areas, having emphasis on aspects of visibility, traffic and movement safety, and sense of security. The last case study presents a more complex view to the experience of intelligent lighting in smart city contexts. The evaluation methods, tailored to each pilot context, include questionnaires, an urban dashboard, in-situ interviews and observations, evaluation probes, and system data analyses. The applicability of the selected and tested methods is discussed reflecting the process and achieved results.

scholarly journals Analysis of the System of Controlling Paid Parking Zones

2021 ◽  
Vol 13 (8) ◽  
pp. 4211
Author(s):  
Maciej Kozłowski ◽  
Andrzej Czerepicki ◽  
Piotr Jaskowski ◽  
Kamil Aniszewski
Keyword(s):  
Control System ◽  
Smart City ◽  
Measurement Errors ◽  
Fundamental Problem ◽  
Urban Traffic ◽  
Statistical Dependence ◽  
Actual State ◽  
Event Time ◽  
Operational Data

Urban traffic can be curbed in various ways, for instance, by introducing paid unguarded parking zones (PUPZ). The operational functionality of this system depends on whether or not the various system features used to document parking cases function properly, including those which enable positioning of vehicles parked in the PUPZ, recognition of plate numbers, event time recording, and the correct anonymisation of persons and other vehicles. The most fundamental problem of this system is its reliability, understood as the conformity of control results with the actual state of matters. This characteristic can be studied empirically, and this article addresses the methodology proposed for such an examination, discussed against a case study. The authors have analysed the statistical dependence of the e-control system’s measurement errors based on operational data. The results of this analysis confirm the rationale behind the deployment of the e-control system under the implementation of the smart city concept in Warsaw.

scholarly journals Challenges and Barriers for Net‐Zero/Positive Energy Buildings and Districts—Empirical Evidence from the Smart City Project SPARCS

Buildings ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 78
Author(s):  
Daria Uspenskaia ◽  
Karl Specht ◽  
Hendrik Kondziella ◽  
Thomas Bruckner
Keyword(s):  
Smart City ◽  
Urban Areas ◽  
Smart Cities ◽  
Scale Up ◽  
Practical Experience ◽  
Positive Energy ◽  
Low Carbon ◽  
Net Zero ◽  
Multidimensional Representation

Without decarbonizing cities energy and climate objectives cannot be achieved as cities account for approximately two thirds of energy consumption and emissions. This goal of decarbonizing cities has to be facilitated by promoting net-zero/positive energy buildings and districts and replicating them, driving cities towards sustainability goals. Many projects in smart cities demonstrate novel and groundbreaking low-carbon solutions in demonstration and lighthouse projects. However, as the historical, geographic, political, social and economic context of urban areas vary greatly, it is not always easy to repeat the solution in another city or even district. It is therefore important to look for the opportunities to scale up or repeat successful pilots. The purpose of this paper is to explore common trends in technologies and replication strategies for positive energy buildings or districts in smart city projects, based on the practical experience from a case study in Leipzig—one of the lighthouse cities in the project SPARCS. One of the key findings the paper has proven is the necessity of a profound replication modelling to deepen the understanding of upscaling processes. Three models analyzed in this article are able to provide a multidimensional representation of the solution to be replicated.

scholarly journals A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 156
Author(s):  
Paige Wenbin Tien ◽  
Shuangyu Wei ◽  
John Calautit
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Energy Demand ◽  
Energy Savings ◽  
Internal Heat ◽  
Electrical Equipment ◽  
Building Energy ◽  
Hvac Systems ◽  
Equipment Usage

Because of extensive variations in occupancy patterns around office space environments and their use of electrical equipment, accurate occupants’ behaviour detection is valuable for reducing the building energy demand and carbon emissions. Using the collected occupancy information, building energy management system can automatically adjust the operation of heating, ventilation and air-conditioning (HVAC) systems to meet the actual demands in different conditioned spaces in real-time. Existing and commonly used ‘fixed’ schedules for HVAC systems are not sufficient and cannot adjust based on the dynamic changes in building environments. This study proposes a vision-based occupancy and equipment usage detection method based on deep learning for demand-driven control systems. A model based on region-based convolutional neural network (R-CNN) was developed, trained and deployed to a camera for real-time detection of occupancy activities and equipment usage. Experiments tests within a case study office room suggested an overall accuracy of 97.32% and 80.80%. In order to predict the energy savings that can be attained using the proposed approach, the case study building was simulated. The simulation results revealed that the heat gains could be over or under predicted when using static or fixed profiles. Based on the set conditions, the equipment and occupancy gains were 65.75% and 32.74% lower when using the deep learning approach. Overall, the study showed the capabilities of the proposed approach in detecting and recognising multiple occupants’ activities and equipment usage and providing an alternative to estimate the internal heat emissions.

scholarly journals Passive Solar Solutions for Buildings: Criteria and Guidelines for a Synergistic Design

2021 ◽  
Vol 11 (1) ◽  
pp. 376
Author(s):  
Giacomo Cillari ◽  
Fabio Fantozzi ◽  
Alessandro Franco
Keyword(s):  
Energy Demand ◽  
Theoretical Background ◽  
Environmental Benefits ◽  
Passive Systems ◽  
Extrinsic Factors ◽  
Solar Systems ◽  
Final Performance ◽  
Passive Solar ◽  
Energy Simulations

Passive solar system design is an essential asset in a zero-energy building perspective to reduce heating, cooling, lighting, and ventilation loads. The integration of passive systems in building leads to a reduction of plant operation with considerable environmental benefits. The design can be related to intrinsic and extrinsic factors that influence the final performance in a synergistic way. The aim of this paper is to provide a comprehensive view of the elements that influence passive solar systems by means of an analysis of the theoretical background and the synergistic design of various solutions available. The paper quantifies the potential impact of influencing factors on the final performance and then investigates a case study of an existing public building, analyzing the effects of the integration of different passive systems through energy simulations. General investigation has highlighted that latitude and orientation impact energy saving on average by 3–13 and 6–11 percentage points, respectively. The case study showed that almost 20% of the building energy demand can be saved by means of passive solar systems. A higher contribution is given by mixing direct and indirect solutions, as half of the heating and around 25% of the cooling energy demand can be cut off.

Learning-Enabled Residential Demand Response: Automation and Security of Cyberphysical Demand Response Systems

2021 ◽  
Vol 9 (1) ◽  
pp. 36-44
Author(s):  
Robert Mieth ◽  
Samrat Acharya ◽  
Ali Hassan ◽  
Yury Dvorkin
Keyword(s):  
Demand Response ◽  
Response Systems ◽  
Residential Demand
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