SMARTGREENS 2021 Abstracts


Area 1 - Smart and Digital Services

Full Papers
Paper Nr: 16
Title:

Role of Citizens in the Development of Smart Cities: Benefit of Citizen’s Feedback for Improving Quality of Service

Authors:

Priyanka Singh, Fiona Lynch and Markus Helfert

Abstract: The initiatives around the involvement of citizens in smart city development is increasing significantly with the aim of enhancing the quality of life for the citizens of these cities through better public services. There is plethora of studies discussing various technologies and platforms to obtain citizen’s feedback for smart city development. Nonetheless, there are very limited studies which provide guidance on how to utilise those feedbacks and improve quality of the services in order to provide better experience to the citizens. This paper examines past work regarding different aspects of citizen’s involvement in smart cities and classify the existing literature through the lens of a smart city framework. This study offers an overview of diverse concepts and platforms associated with the role of citizens in smart city design and development by featuring possible linkages to the related layers of the adopted framework. This study further proposes a conceptual model to incorporate citizen’s feedback in more structured way at architecture level in order to meet their requirements and to provide improved quality of services to them.
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Short Papers
Paper Nr: 20
Title:

Edge Intelligence with Deep Learning in Greenhouse Management

Authors:

Massimiliano Proietti, Federico Bianchi, Andrea Marini, Lorenzo Menculini, Loris F. Termite, Alberto Garinei, Lorenzo Biondi and Marcello Marconi

Abstract: This paper presents a methodology to control greenhouse operations based on deep learning. The proposed methodology employs Artificial Intelligence algorithms working on edge devices, allowing the detection of anomalies in plants growth and greenhouse control equipment, in view of taking possible corrective actions. Edge Intelligence allows the greenhouse to work independently of the network to which it is connected. It also guarantees privacy to the processed data and contributes to fast and efficient decision-making. In this work, a Long-Short Time Memory Encoder-Decoder architecture is used for greenhouse anomaly detection. The best performance is achieved when using one LSTM layer and 64 LSTM units.
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Area 2 - Smart Infrastructures and Smart Buildings

Full Papers
Paper Nr: 1
Title:

An Artificial Neural Network-based Real Time DSS to Manage the Discharges of a Wastewater Treatment Plant and Reduce the Flooding Risk

Authors:

Loris F. Termite, Emanuele Bonamente, Alberto Garinei, Daniele Bolpagni, Lorenzo Menculini, Marcello Marconi, Lorenzo Biondi, Andrea Chini and Massimo Crespi

Abstract: An approach for sewerage systems monitoring based on Artificial Neural Networks is presented as a feasible and reliable way of providing operators with a real-time Decision Support System that is able to predict critical events and suggest a proper mitigation strategy. A fully-working prototype was developed and tested on a sewerage system in the city of Brescia, Italy. The system is trained to forecast flows and water levels in critical points of the grid based on their measured values as well as rainfall data. When relying on observed rainfall only, key parameters can be predicted up to 60 minutes in advance, whereas including very-short-term Quantitative Precipitation Estimates – nowcasting – the time horizon can be extended further, up to 140 minutes in the current case study. Unlike classical hydraulic modelling, the proposed approach can be effectively used run-time as the execution is performed with a negligible computational cost, and it is suitable to increase safety measures in a Smart City context.
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Paper Nr: 21
Title:

Building Indoor Point Cloud Datasets with Object Annotation for Public Safety

Authors:

Mazharul Hossain, Tianxing Ma, Thomas Watson, Brandon Simmers, Junaid A. Khan, Eddie Jacobs and Lan Wang

Abstract: An accurate model of building interiors with detailed annotations is critical to protecting the first responders’ safety and building occupants during emergency operations. In collaboration with the City of Memphis, we collected extensive LiDAR and image data for the city’s buildings. We apply machine learning techniques to detect and classify objects of interest for first responders and create a comprehensive 3D indoor space database with annotated safety-related objects. This paper documents the challenges we encountered in data collection and processing, and it presents a complete 3D mapping and labeling system for the environments inside and adjacent to buildings. Moreover, we use a case study to illustrate our process and show preliminary evaluation results.
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Paper Nr: 25
Title:

Energy Optimal Control of a Multivalent Building Energy System using Machine Learning

Authors:

Chenzi Huang, Stephan Seidel, Xuehua Jia, Fabian Paschke and Jan Bräunig

Abstract: In this contribution we develop and analyse intelligent control methods in order to optimise the energy efficiency of a modern residential building with multiple renewable energy sources. Because of alternative energy production options a non-convex mixed-integer optimisation problem arises. For the solution we first apply combined optimisation methods and integrate it into a model predictive controller (MPC). In comparison, a reinforcement learning (RL) based approach is developed and evaluated in detail. Both methods, in particular reinforcement learning approaches are able to decrease energy consumption and keep thermal comfort at the same time. However, in this paper RL can achieve better results with less computational resources than MPC approach.
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Short Papers
Paper Nr: 5
Title:

Condition Monitoring for Air Filters in HVAC Systems with Variable Volume Flow

Authors:

Oliver Gnepper and Olaf Enge-Rosenblatt

Abstract: State of the art condition monitoring systems for air filters in HVAC systems require that the HVAC system is operated at nominal volume flow. For HVAC systems with variable volume flow this assumption is only fulfilled in one operating point. Outside this operating point existing condition monitoring systems assess the air filter condition in a too optimistic manner. Therefore, polluted air filters remain undetected until their regular check, leading to unneeded energy consumption. If the true condition of an air filter is known, it could be changed before it is clogged. So, a condition monitoring systems is needed which is also reliable in case of HVAC systems with variable volume flow. This work presents a model-based approach for such a condition monitoring system. Therefore, a dataset from a building is used to assess an optimal model. Furthermore, the condition monitoring systems is evaluated on that dataset.
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Paper Nr: 14
Title:

Assessment of Building Integrated Photovoltaic Panels on Facades of Commercial Buildings with Respect to Energy Conservation Building Code

Authors:

Achinta N. Shetty, Pradeep G. Kini, Pranav Kishore and Vipin Tandon

Abstract: The formulation of the paper considered the need for adapting to renewable resources in fast-growing world. The integration of Building Integrated Photovoltaic (BIPV) panels will minimize the environment damage, climate change, and resource shortages. The BIPV system implemented on the facade is one of the suitable solutions to increase the building performance using the on-site renewable resource with a reduced impact on the surroundings. The methodology introduced in this paper is carried out by using Design Builder software initially, which provides an understanding of the PV energy produced to achieve 3% renewable energy in a modelled commercial building of 20,000 m2 according to the Energy Conservation Building Code (ECBC) while placed in a moderate climatic zone. This paper aims at studying various approaches to further enhance the energy production of the modelled building after attaining the ECBC minimum requirement. PVGIS system is used to assess parameters such as PV technology used, integration of the panels, system loss, year to year variability, tilt angles of the panels. Further, shadow analysis of the optimal angle to maximize energy production is analysed. A comparative study between the modelled building and the PVGIS system on the panel cost and payback period is conducted. Based on the optimum tilt and azimuth angles, shadow analysis and daylighting analysis is carried out. The paper provides an understanding of the optimal integration style of the BIPV panels on the building facade.
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Paper Nr: 2
Title:

Thermal Model of a House using Electric Circuits Analogy

Authors:

Xhilda Merkaj, Darjon Dhamo and Eglantina Kalluçi

Abstract: The aim of this paper is to produce a thermal model of a house using electrical circuit analogy which gives information about indoor temperatures and power consumption of electrical heater in each room of the house. The information obtained from the power consumption of each electrical heater serves to estimate the peak consumption which gives problems in the grid. The house under survey has 5 rooms: a bedroom, a bathroom, a kitchen, a living-room, and an anteroom. The layers of internal and external walls, windows, roofs and floors are thermal modeling into electrical components from which a circuit is assembled. Using node voltage method in each circuit a state space equations are obtained, each of this equations are simulated in MATLAB environment considering electrical heater time of use based on occupant behavior. Having this model allows us to simulate the change of temperature of each room, design efficiency the controls algorithm and estimates peak consumption for improving its reduction.
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Paper Nr: 15
Title:

Designing Green Infrastructure Guidelines: A Methodological Approach

Authors:

Andrea De Montis, Giovanna Calia, Valentina Puddu and Antonio Ledda

Abstract: Natural capital and biodiversity are in decline as consequence of human activities. To promote the conservation of biodiversity and the achievement of sustainability goals, the European Commission proposes the use of green infrastructures (GIs), which are networks of naturals areas aimed at the conservation of ecosystems and providing ecosystem services in urban and peri-urban areas. Effective implementation of GIs is hindered by institutional and behavioural barriers; thus, public administrations issue guidance documents to steer GI planning, design, realization, and maintenance. Current guidance documents mainly contain references to components of GI. The scientific literature lacks specific methods for the design of guidelines concerning the implementation of GI. In this respect, we identify and propose a method for drafting up guidelines aimed at GI planning and design in regional and local Italian contexts. The method is rooted in the analysis and summary of scientific and grey literature and consists of six phases. The results of this study are a first step for steering municipal and regional administrations at the development of GI guidelines tailored for specific contexts.
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Area 3 - Sustainable Computing and Systems

Full Papers
Paper Nr: 12
Title:

Energy Saving Potential in Building Envelopes through Energy Conservation Building Code and Design Alternatives in Warm and Humid Climate

Authors:

Anuthama Mahesh, Pradeep Kini and Pranav Kishore

Abstract: Energy usage in commercial buildings significantly adds to the total annual energy consumption of the building sector in India which is growing at a fast pace. A large fraction of energy consumed in buildings is attributed to space cooling systems. Heat transfer through the building envelope leads to higher demand for space cooling and increased electricity usage for space cooling systems which further leads to higher levels of emissions enabling climate change. In this study, the energy savings potential for commercial buildings through the implementation of Energy Conservation Building Code (ECBC) of India has been studied for commercial building envelope in the warm and humid climate zone of India. The existing building envelope is analysed through documentation and a simulation model is created towards the baseline case. A second model is then simulated with ECBC prescriptive requirements using Energy Conservation Measures (ECM) and is evaluated based on energy consumption to analyse the relative performance of building envelope components. The implementation of ECBC prescriptive requirements is found to reduce energy consumption by 15.86% in the baseline case. Further implementation of Design Alternatives (DA) in the building envelope achieved a reduction in overall annual energy consumption by 32.31%.
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Short Papers
Paper Nr: 30
Title:

Application of Pretopological Hierarchical Clustering for Buildings Portfolio

Authors:

Loup-Noé Lévy, Jérémie Bosom, Guillaume Guerard, Soufian Ben Amor, Marc Bui and Hai Tran

Abstract: Our paper deals with the problem of the comparison of heterogeneous energy consumption profiles for energy optimization. Doing case-by-case in depth auditing of thousands of buildings would require a massive amount of time and money as well as a significant number of qualified people. Thus, an automated method must be developed in order to establish a relevant and effective recommendations system. Comparing sites to extract similar profiles refers to a machine learning set of methods called clustering. To answer this problematic, pretopology is used to model the sites’ consumption profiles and a multi-criteria hierarchical clustering algorithm, using the properties of pretopological space, has been developed using a Python library. The pretopological hierarchical clustering algorithm is able to identify the clusters and provide a hierarchy between complex items. Tested on benchmarks of generated time series (from literature and from french energy company), the algorithm is able to identify the clusters using Pearson’s correlation with an Adjusted Rand Index of 1 and returns relevant results on real energy systems’ consumption data.
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Paper Nr: 6
Title:

A Multi-Scale, Web-based Application for Strategic Assessment of PV Potentials in City Quarters

Authors:

Sally Köhler, Rosanny Sihombing, Eric Duminil, Volker Coors and Bastian Schröter

Abstract: This paper introduces a web-based application that visualizes building specific simulation results regarding renewable potentials and economics for entire city quarters. Focusing on the building stock, this application enables decision-makers to consider energy related aspects in early-stage city quarter planning. The application builds on the existing energy simulation platform, SimStadt, which allows the detailed assessment of buildings’ energetic performance or photovoltaic rooftop potentials based on 3D CityGML models. A new, user-friendly and browser-based graphical user interface (GUI) makes energetic modeling more accessible and independent of a user’s operating system. Furthermore, a customizable economic analysis was added to the pre-existing workflow to calculate rooftop PV potentials, allowing the evaluation of renewable energy potentials with their associated total investments or levelized cost of electricity (LCOE) at building level. Combined, these improvements create new use cases for modeling environments previously reserved for researchers, such as enabling utilities and their house-owning customers to identify PV potentials and costs, or PV project developers to more easily and accurately locate neighborhoods with high potential. Further functionalities such as building heating and cooling demand assessment will be included in a next step to extend the scope of this application towards a versatile urban energy system simulation platform.
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Paper Nr: 10
Title:

Hybrid Energy Production Analysis and Modelling for Radio Access Network Supply

Authors:

Greta Vallero and Michela Meo

Abstract: To move towards sustainability, Renewable Energy Sources (RES) have started to partially substitute fossil fuels based energy generation. Also for the Information and Communication Technology (ICT) ecosystem supply, and in particular in the Radio Access Networks (RANs), the usage of PV panels has been considered an effective solution. Since the communication infrastructure has to be powered continuously, to face the problem of the absence of the Photovoltaic (PV) panel energy production during the night, we consider a hybrid solution, composed by a PV panel and a wind turbine, for the supply of Base Stations (BSs). Starting from the characterisation of wind energy production, we assess the impact of the employment of the combination of these RES on the excesses and deficits of energy production, highlighting that the hybrid solution better fits the BS energy demand. In order to predict performance, we build polynomial models, which highlight the effects of the variation of the installed wind and solar capacities.
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Paper Nr: 24
Title:

Model-based Systems Design for Green IoT Systems

Authors:

Kristin Majetta, Jan Bräunig, Christoph Sohrmann, Roland Jancke and Dirk Mayer

Abstract: The energy consumption of the Internet of Things is predicted to be about a quarter of the total world-wide energy consumption by 2030. There are already numerous approaches and operating strategies to reduce the energy consumption of wireless sensors. Nevertheless, it is essential to implement a formalized model-based development process that enables the designer of IoT nodes, platforms and systems to balance between the function and non-functional requirements with respect to energy consumption. Therefore we promote a model-based systems design methodology that employs multi-physical co-simulation in a virtual simulation environment in order to optimize the overall energy consumption.
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Area 4 - Energy-Aware Systems and Technologies

Short Papers
Paper Nr: 9
Title:

Toward Sustainable Energy Communities

Authors:

Giuseppe Anastasi and Marco Raugi

Abstract: Currently energy resources are adapted to user requests. In the perspective of an increasingly sustainable use of energy, it will be more and more useful to aggregate the consumption of groups of buildings of various types (for example for residential, office, commercial and industrial use), forming the so-called "Energy Communities". In that way the overall requests for energy can be easily adapted to the available energy resources, in terms of both overall consumption and hourly distribution. The AUTENS (Sustainable Energy Autarchy) project aims to identify possible solutions for the complete energy self-sufficiency of "Energy Communities" through innovative methods optimizing the integration of electrical and thermal systems (generators and storages), supplied only by renewable sources produced locally. This will be targeted by means of suitable integration of ICT technologies, artificial intelligence and social sciences. We intend to examine situations in which it is not possible, or sustainable, to use the primary power and gas grid, and therefore the use of energy from an "Energy Community" must be made with only renewable sources to be produced locally through solar and wind energy, geothermal and biomass. The project also proposes the construction of some demonstrators.
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Paper Nr: 19
Title:

Detection and Prevention of Denial-of-Service in Cloud-based Smart Grid

Authors:

Abdul Razaq, Muhammad M. Hussain, Waqas Javed, Tasmiyah Javed and Zulfiqar A. Memon

Abstract: Smart Grid (SG), components with historical set of security challenges, becomes more vulnerable because Information and Communications Technology (ICT) has its own share of problems while Cloud infrastructure adds yet another unpredicted layer of threats. Scalability and availability, which are strong aspects of the cloud platform making it attractive to users, also attracts security threats for the same reasons. The malware installed on single host offers very limited scope compared to attack magnitude that compromised Cloud platform can offer. Therefore, the strongest aspect of Cloud itself becomes a nightmare in Cloud-Based SG. A breach in such a delicate system can cause severe consequences including interruption of electricity, equipment damage, data breach, complete blackouts, or even life-threatening consequences. We mimic Denial-of-Service (DoS) attacks to demonstrate interruption of electricity in SG with open-source solution to co-simulate power and communication systems.
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Paper Nr: 22
Title:

Energy Efficiency of Low Voltage Direct Current Supplies Including PV Sources

Authors:

Anis Ammous, Ammar Assaidi, Abdulrahman Alahdal and Kaiçar Ammous

Abstract: The low Voltage Direct Current (LVDC) system concept has been growing in the recent times due to its characteristics and advantages like renewable energy source compatibility, more straightforward integration with storage utilities through power electronic converters and distributed loads. This paper presents the energy efficiency performances of a proposed LVDC supply concept and others classical PV chains architectures. A PV source was considered in the studied nanogrids. The notion of Relative Saved Energy (RSE) was introduced to compare the studied PV systems energy performances. The obtained results revealed that the employment of the LVDC chain supply concept is very interesting and the use of DC loads as an alternative to AC loads, when a PV power is generated locally, is more efficient. The installed PV power source in the building should be well sized regarding to the consumed power in order to register a high system RSE.
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Paper Nr: 23
Title:

Design of a Very Low Frequency Test Device for Faults Diagnosis in Underground Cable

Authors:

Anis Ammous, Mohamed A. Zdiri, Ammar Assaidi, Abdulrahman Alahdal and Kaiçar Ammous

Abstract: In this paper, we present the design of a Very low frequency (VLF) generator made of power electronics converter coupled to a mechanical system. This device is used to detect and locate faults in cables. This VLF test is an AC type test at 0.1 Hz of a cosine-rectangular waveform performed on an underground cable. Simulations were carried out for the following cable faults: open-circuit, short-circuit, resistance fault and spark gap. For each fault type, simulations are performed for different locations in order to collect databases in a neural network relating the distance and the corresponding voltage from the fault location. This allows to register the range of voltages variation in each fault, which is useful for its identification. In addition, these databases are used to determine the fault location using the Spline interpolation method. The tests were performed on a 20 km cable length. The obtained results show the high performance and efficiency of the investigated methods in terms of cable fault identification precision and localization.
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Paper Nr: 3
Title:

Synchronised Power Scheduling of Widely Distributed Refrigerators using IoT

Authors:

M. Z. Sabegh and C. M. Bingham

Abstract: The paper proposes an IoT controlled platform to remotely monitor and control appliances in the residential sector. An IP-based synchronized wireless mesh network is implemented through IoT hardware (based on a NodeMCU) and Google Sheets to monitor and schedule the operation of aggregated domestic refrigerators under a Model Predictive Control (MPC) scheme. Benefits afforded by the proposed technique are investigated through experimental trials from VonShef 13/291 (50W), iGENIX IG 3920 (55W) and Russell Hobbs RHCLRF17B (50W) domestic refrigerators sited in three different domestic locations in the city of Lincoln, UK. Results demonstrate the ability to monitor and control widely distributed networks of refrigerators and adaptively schedule the appliances to reduce peak operational loads and facilitate Demand Side Response (DSR). Further widespread expansion of the proposed technique would allow for a rapidly deployed regional DSR strategy to aid grid stability. Ultimately the underlying principles also could be used for the co-ordinated scheduling of other distributed appliances and equipment, both domestic and industrial.
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Paper Nr: 13
Title:

The Study of Transition to the Isolated Operation of Power Supply Systems with Distributed Generation Plants and High Power Energy Storage Units

Authors:

Yuri N. Bulatov, Andrey V. Kryukov and Konstantin V. Suslov

Abstract: The development of power engineering, under current conditions, is aimed at the use of distributed generation plants in power supply systems located in immediate proximity from power consumers. The article deals with power supply system with turbo generator plant and high power energy storage unit. Description of a power supply system model with turbo generator plant, energy storage unit and asynchronous load is provided, and modeling results of power supply system transition to the isolated operating mode. The model of the power supply system under study was carried out in the MATLAB environment using the Simulink and SimPowerSystems simulation packages. In work is a description of the PSS model used with DG plant and ESU, as well as the simulation results. Based on the computer simulation results the conclusion, that use of prognostic controllers turbo generator plant allows improving the damping properties of the system when switching to an isolated mode of operation.
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Area 5 - Smart Cities

Full Papers
Paper Nr: 29
Title:

An Automated Clustering Process for Helping Practitioners to Identify Similar EV Charging Patterns across Multiple Temporal Granularities

Authors:

René Richard, Hung Cao and Monica Wachowicz

Abstract: Electric vehicles (EVs) are part of the solution towards cleaner transport and cities. Clustering EV charging events has been useful for ensuring service consistency and increasing EV adoption. However, clustering presents challenges for practitioners when first selecting the appropriate hyperparameter combination for an algorithm and later when assessing the quality of clustering results. Ground truth information is usually not available for practitioners to validate the discovered patterns. As a result, it is harder to judge the effectiveness of different modelling decisions since there is no objective way to compare them. In this work, we propose a clustering process that allows for the creation of relative rankings of similar clustering results. The overall goal is to support practitioners by allowing them to compare a cluster of interest against other similar clusters over multiple temporal granularities. The efficacy of this analytical process is demonstrated with a case study using real-world Electric Vehicle (EV) charging event data from charging station operators in Atlantic Canada.
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Short Papers
Paper Nr: 4
Title:

Design of an Urban Monitoring System for Air Quality in Smart Cities

Authors:

Andrea Marini, Patrizia Mariani, Alberto Garinei, Stefania Proietti, Paolo Sdringola, Massimiliano Proietti, Lorenzo Menculini and Marcello Marconi

Abstract: Pollution is one of the main problems faced by cities nowadays, due to the increase in emissions from anthropogenic sources resulting from economic, industrial and demographic development. High values of pollutants, such as atmospheric particulate matter, lead to adverse effects on the environment and human health, causing the spread of respiratory, cardiovascular and neurological problems. For instance, recent work shows a connection between the spread of the Covid-19 pandemic and environmental pollution. In this context, urban monitoring of pollutants can allow to evaluate and perform actions aimed at reducing pollution in order to safeguard citizens’ health. This study proposes a method to design an urban air quality monitoring system. It uses the AHP multi-criteria decision-making technique to define the initial positioning of the sensors, and the cellular automata mathematical model for the following optimization, from which the final configuration of the network is derived. In the present case study, the monitoring concerns atmospheric particulate matter (PM10 and PM2.5) and is carried out with six sensors that constitute a LoRaWAN network, as often used for monitoring activities in smart cities.
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Paper Nr: 8
Title:

Insights with Big Data Analysis for Commercial Buildings Flexibility in the Context of Smart Cities

Authors:

Simona-Vasilica Oprea, Adela Bâra, Cătălin Ceaparu, Anca A. Ducman, Vlad Diaconița and Gabriela Dobrița Ene

Abstract: The commercial buildings generate a significant volume of data that can be processed to assess the flexibility of the electricity consumption and their potential contribution to flatten the load curve or provide ancillary services. With the constant increase of the volatile output of the Renewable Energy Sources (RES) and numerous Electric Vehicles (EV), the flexibility potential of the commercial buildings has to be investigated to create smarter green cities. However, the volume of consumption data is significantly increasing when various activities are profiled, such as cooling, heating, fans, lights, equipment, etc. In this paper, we propose a big data processing framework or methodology to extract interesting insights from very large datasets and identify the flexibility of the commercial buildings (of several types from the United State of America – U.S.A.) and its market value in correlation with the Demand Response (DR) capabilities at the state and Independent System Operator (ISO) level. This is a theoretical approach combining several aspects, such as: large datasets processing techniques, DR programs, consumption data, flexibility potential estimation, scenarios and DR enabling technologies costs. Applying one of the DR programs, significant results in terms of savings are revealed from simulations.
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Paper Nr: 26
Title:

A Comparative Analysis of Smart Cities Frameworks based on Data Lifecycle Requirements

Authors:

Claudia Roessing and Markus Helfert

Abstract: Citizens migrate from rural areas to urban centres in search of better living conditions. The rural-urban migration combined with rapid population growth lead to overpopulation, which consequently creates challenges to cities in the use and reallocation of their resources. Smart cities have emerged as an opportunity to assist cities to overcome these difficulties with the usage of information and communication technology (ICT) to improve the lifestyle of their citizens. However, maintenance of a smart city is a difficult task. In this multi-stakeholder system, services from different domains are offered to citizens, which collect data from different sources with different formats that need to be in compliance with regulations, privacy, and security requirements. Therefore, a data lifecycle plays a vital role as a data management framework as a means of reducing the complexity of their ecosystems to assist align their objectives and services offered to the citizens. Prior researches have stated a need for improvement in this framework modelling. The aim of this paper is to address this gap and define data lifecycle requirements which will be used to analyse a selection of smart cities architecture frameworks.
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Paper Nr: 27
Title:

Hazard Analysis for Decentralized Charging Management of Electric Vehicles

Authors:

Stylianos Karatzas, Panagiotis Farmakis, Athanasios Chassiakos and Zoi Christoforou

Abstract: This paper deals with the hazard analysis in the design of an application for decentralized EVs charging management at all stages of the process, including identification of charging points, selection of the optimum charging station, charging and successful transactions between user and provider, by applying the nondeterministic System-Theoretic Process Analysis (STPA). The aim is to explore the possibilities offered by the proposed systemic model of hazard analysis in a complex system and examine the effectiveness of the implementation in the development of an application, ensuring the safe operation and interactions between the various subsystems and processes in charging management. The identification of accident scenarios and corresponding safety constraints guides safety analysts in the design phase of the application, to prevent losses and costly interventions during actual operation phase.
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Paper Nr: 17
Title:

GREECOPE: Green Computing with Piezoelectric Effect

Authors:

Meghana Kshirsagar, Rutuja Lahoti, Tanishq More and Conor Ryan

Abstract: The growing interest in the search and use of alternative resources for renewable energy can lead the future towards substantially decreasing carbon footprint and reduce the effects of global warming. The proposed research explores the possibility of harnessing piezoelectric energy from the environment of moving vehicles on road. Although the technology is still immature, it has the advantage of having zero carbon footprints thus making it ideal to investigate the potential for green energy generation. The main objective is to develop regression models that can estimate energy generated from vehicular traffic. Energy is generated when force is applied to piezoelectric transducers which depend on significant factors such as the number of piezoelectric transducers and their arrangement, load applied and frequency. We design Support Vector Machine (SVM) and Generalised Linear Model (GLM) for predicting energy. The best features for training the model were selected by incorporating feature selection techniques such as Pearson’s correlation coefficient and Mutual Information Statistics. The experimental setup makes use of simulated data which takes into account vehicle count of different vehicles with and without load. The accuracy achieved from SVM and GLM are 99.6% and 99.7% respectively. The energy savings achieved by making use of generated piezoelectric energy is discussed with a sample scenario of Motorway50 of Dublin, the Irish Capital city. Through this work, we propose to investigate deeper into the feasibility towards cost-effectiveness by utilizing energy which is wasted by human and vehicular locomotion.
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