SMARTGREENS 2018 Abstracts

Area 1 - Smart Cities and Smart Buildings
Full Papers Short Papers
Area 2 - Sustainable Computing and Systems
Full Papers Short Papers
Area 3 - Energy-Aware Systems and Technologies
Full Papers Short Papers

Area 1 - Smart Cities and Smart Buildings

Full Papers
Paper Nr: 22
Title:

A New Crypto-classifier Service for Energy Efficiency in Smart Cities
Authors:

Oana Stan, Mohamed-Haykel Zayani, Renaud Sirdey, Amira Ben Hamida, Alessandro Ferreira Leite and Mallek Mziou-Sallami
Abstract: Smart Cities draw a nice picture of a connected city where useful services and data are ubiquitous, energy is properly used and urban infrastructures are well orchestrated. Fulfilling this vision in our cities implies unveiling citizens data and assets. Thus, security and data privacy appear as crucial issues to consider. In this paper, we study a way of offering a secured energy management service for diagnosis and classification of buildings in a district upon their energy consumption. Our remote service can be beneficial both for local authorities and householders without revealing private data. Our framework is designed such that the private data is permanently encrypted and that the server performing the classification algorithm has no information about the sensitive data and no capability to decrypt it. The underlying cryptographic technology used is homomorphic encryption, allowing to perform calculations directly on encrypted data. We present here the prototype of a crypto-classification service for energy consumption profiles involving different actors of a smart city community, as well as the associated performances results. We assess our proposal atop of real data taken from an Irish residential district and we show that our service can achieve acceptable performances in terms of security, execution times and memory requirements.
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Paper Nr: 26
Title:

A Predictive Comfort- and Energy-aware MPC-driven Approach based on a Dynamic PMV Subjectification towards Personalization in an Indoor Climate Control Scenario
Authors:

Antonios Karatzoglou, Julian Janßen, Vethiga Srikanthan, Christof Urbaczek and Michael Beigl
Abstract: There exist two ways of improving the climate conditions within a building; upgrading the building insulation and applying modern heating technology, whereby the combination of both would obviously yield the best result. Recent heating technologies lay high emphasis on forward-looking behavior in order to be capable of providing both more comfort and a higher energy efficiency. Some rely on outdoor and indoor temperature predictive models. Other utilize occupancy prediction. The majority and in particular the ones based on the Predicted Mean Vote (PMV), employ a PMV-driven fixed single temperature point, range (e.g. 22-24C) or curve as reference. In this paper, we introduce a hybrid, personalized heating control approach. It combines a probabilistic occupancy prediction model together with an energy- and subjectified comfort-aware model-based predictive controller (MPC), which can be tailored dynamically to the users’ preference of comfort. Starting with a default PMV and a corresponding first temperature set point, our system learns from the users’ interaction with the system’s comfort-driven UI and adapts online the MPC’s target comfort and thereby the MPC’s optimization function respectively. We conducted a user study in a real office environment and show that our dynamic customizable approach outperforms significantly the non-dynamic one in respect of both comfort and energy.
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Paper Nr: 58
Title:

Application Independent Flexibility Assessment and Forecasting for Controlled EV Charging
Authors:

Marcus Voß, Mathias Wilhelm and Sahin Albayrak
Abstract: Electric vehicles (EVs) have been proposed to provide flexibility to the energy grid in various ways. With EV exhibiting very diverse usage patterns on the one hand, and many demand response (DR) schemes and their respective requirements on the other, aggregators of flexibility, as well as operators of controlled charging infrastructure, need models and methods to assess the suitability of specific EVs for specific schemes. In this paper, we provide an application independent flexibility model that allows quantifying the potential amount of flexibility based on a historical dataset. Further, we provide a process to assess the predictability of flexibility through modeling it as a short-term load forecasting problem suitable also for smaller aggregations. Our key findings using real-world data of over 200 charging points are that up- and downwards flexibility per interval have a similar magnitude, but it is unexpectedly low for the high number of charging points. Further, we find that forecast errors are quite high, although we can improve upon naive benchmarks by almost 20% in mean absolute errors with learning models.
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Short Papers
Paper Nr: 3
Title:

Analyzing Urban Mobility Carbon Footprint with Large-scale, Agent-based Simulation
Authors:

Eduardo Felipe Zambom Santana, Lucas Kanashiro, Diego Bogado Tomasiello, Fabio Kon and Mariana Giannotti
Abstract: The growth of cities around the world bring new challenges to urban management and planning. Tools, such as simulators, can help the decision-making process by enabling the understanding of the current situation of the city and comparison of multiple scenarios with regard to changes in the urban infrastructure and in public policy. This paper presents an analysis of mobility parameters, such as distance, cost, travel time, and carbon footprint, for different simulated scenarios in a large metropolis in a developing country. We simulated the scenarios using an open source, large-scale, agent-based Smart City simulator that we developed.
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Paper Nr: 19
Title:

Innovative Low Power Multiradio Sensing and Control Device for Non-Intrusive Occupancy Monitoring
Authors:

Marco De Donno and Brendan O'Flynn
Abstract: New tools and methodologies to reduce the gap between predicted and actual energy performances at the level of buildings and blocks of buildings are in continuous development in academic and industry organizations. The development of Wireless Sensor Networking (WSN) technology plays a core role in this field since their development enables the monitoring and control of application within the building environment. In this paper the development of a low power consumption multiradio and multisensing system to monitor building conditions and enable the interaction of occupants with devices through embedded actuators is described. The device (named NOD) incorporates a 32-bit ARM-Cortex microcontroller, a variety of sensors to monitor the ambient conditions – luminance, temperature, humidity, air quality - and multiple radio interfaces - WiFi/Bluetooth LE/868MHz. The NOD is intended to be used as a desktop device with a dedicated user interface. A description of the system and its features and functionalities is provided.
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Paper Nr: 28
Title:

Industrial Optimal Operation Planning with Financial and Ecological Objectives
Authors:

Camille Pajot, Benoit Delinchant, Yves Maréchal, Frederic Wurtz, Lou Morriet, Benjamin Vincent and François Debray
Abstract: As energy transition is fundamental to have a chance to fight climate change, every stakeholder concerned by energy should be able to get a better knowledge of the consequences of these actions. However, it could be very complex to understand energy problematics without being an expert. This article focuses on giving the possibility to an energy intensive consumer of a district to make decisions about its energy planning while taking into account its specific operating constraints. A practical case has been studied in a heat recovery project to help the experiments planning of a research laboratory according to the thermal needs of the district. At first, the energy planning only aims to reduce its electricity consumption bill. In a second time, we consider re-using the thermal power from processes cooling. Then, two energy planning were realised: reducing district CO2 emissions and reducing district supply cost. Finally, trade-offs between these two goals have been studied. The work is based on mixed-integer linear optimization models (MILP) gathered into a Python library to provide a modular decisions tool for energy stakeholders.
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Paper Nr: 41
Title:

Towards Cost-Effective Utility Business Models - Selecting a Communication Architecture for the Rollout of New Smart Energy Services
Authors:

Toni Goeller, Marc Wenninger and Jochen Schmidt
Abstract: The IT architecture for meter reading and utility services is at the core of new business models and has a decisive role as an enabler for resource efficiency measures. The communication architecture used by those services has significant impact on cost, flexibility and speed of new service rollout. This article describes how the dominant system model for meter reading came about, what alternative models exist, and what trade-offs those models have for rollout of new services by different stakeholders. Control of a self learning home automation system by dynamic tariff information (Real-Time-Pricing) is given as an application example.
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Paper Nr: 42
Title:

Centralized Scheduling Approach to Manage Smart Charging of Electric Vehicles in Smart Cities
Authors:

Giuseppe Graber, Vincenzo Galdi, Vito Calderaro, Francesco Lamberti and Antonio Piccolo
Abstract: Electric vehicles (EVs) are emerging as the future of individual mobility systems in smart cities since they reduce greenhouse gas emissions and fossil fuel dependence. However, the deepening penetration of battery EVs forecasted for the incoming years could cause significant stress on distribution networks (DNs), as well as the need to address the growing energy demand. In order to limit the negative drawbacks associated with EVs charging demand, the paper proposes a centralized approach for the EVs smart charging, and its performance are compared with the uncontrolled charging approach. An optimization framework is formulated in order to reduce both the overall peak power demand and the EVs charging cost according to the electricity prices during the day. Finally, several Monte Carlo simulations are carried out to evaluate the benefits introduced by the proposed scheduling strategy on a real case study, in terms of charging cost for EVs’ users, satisfaction of EVs charging needs, and flattening of the load profile.
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Paper Nr: 53
Title:

Autonomous Vehicles for Independent Living of Older Adults - Insights and Directions for a Cross-European Qualitative Study
Authors:

Shane McLoughlin, David Prendergast and Brian Donnellan
Abstract: Autonomous Vehicles (AV) are expected to have a revolutionary impact on future Society, forming an integral component of future Smart Cities & regions. ‘Impacts’ range from changes in mobility, environment, planning, infrastructure, employment, leisure time to disruptive business models etc. Designing user centred mobility experiences for citizens ensuring trust, adoption and enhanced experience of emerging AV systems, products and services is an important emerging research challenge today. It is projected that ‘older adults’ (65+) will encompass approximately one third of the mobility marketplace by 2060, with the broader ‘Silver Economy’ set to provide enormous potential for new forms of product/services and related business models. AV’s have the potential to prolong independent living of ‘older adults’ (OA) thus enhancing overall quality of life. For example, driving cessation and mobility barriers correlate with poorer health outcomes. Ensuring future AV adoption requires designing mobility experiences addressing the differing life contexts (i.e. health, financial, mobility needs etc.) of OA. This paper presents context, motivation and initial findings from a qualitative pilot study of Irish Older adults that informs the design of a cross-European study to support ‘Independent Living of Older adults’ in a future AV marketplace that encompasses new Mobility As A Service offerings.
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Paper Nr: 63
Title:

Energy Building Stock Simulation and Planning for Small Municipalities - A Web-based Urban Energy System Model for Potential Analysis and Citizen Participation
Authors:

Simon Schneider, Thomas Zelger and Pierre Laurent
Abstract: City planning for sustainable energy and development goals in small municipalities suffers from unresolved complexities, insufficient data and prohibitive cost. We propose a low-cost urban energy system for building stock assessment and urban energy planning by combining archetype-based dynamic energy demand and coverage simulation with incentive-based citizen participation as a means to improve data quality. Combining a white-box based physical approach with multi-dimensional archetypes for individual building energy demand and supply estimation with statistical top-down validation and calibration, we obtain an energy simulation method that requires less data on the building stock than other typical methods.
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Paper Nr: 9
Title:

A Comparison of Smart City Development and Big Data Analytics Adoption Approaches
Authors:

Zohreh Pourzolfaghar, Christian Bremser, Markus Helfert and Gunther Piller
Abstract: This paper intends to elucidate the similarities between smart city development and big data analytics adoption. Both concepts promise new opportunities: smart cities to improve citizens’ life quality and big data analytics to drive companies towards the competitive edge. Consequently, the number of organisational big data initiatives and efforts to implement smart city concepts are increasing. In the context of big data analytics adoption, it could be shown that there are two distinct approaches companies follow. They either focus on the search for potential use cases or on the development of a technology infrastructure. Based on a comparison of various smart city and big data analytics use cases, this paper discloses that both of these approaches either concentrate on developing new service development or providing the required infrastructures for future services.
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Paper Nr: 25
Title:

Distributed Energy Resource ICT Reference Architecture - Distributed Control Architecture for Hardware Limited Internet of Things DERs

Authors:

Bo Petersen, Henrik Bindner, Bjarne Poulsen and Shi You
Abstract: For Distributed Energy Resources to participate in the grid, and help solve the problems of unreliability and inefficiency, caused by weather dependent, and distributed energy resources, they must have a processing unit, data connection, and an ICT architecture. The aim of the paper is to describe the software components of the ICT architecture, thereby improving the design of scalable ICT architectures for automatically controlled DERs. Future plug ‘n’ play software components that improve the scalability and eases the development of such ICT architectures are also described in the paper. The ICT architecture should be scalable to many different types of DERs with minimal effort and should enable control by automated generic controlling entities. The ICT architecture primarily consists of three layers, the driver layer that uses native communication to talk to the unit hardware, the data layer that supplies historical data, real-time data, and future prediction to the communication layer, which is responsible for talking to the controlling entities. With the plug ‘n’ play extension components which adds the application launcher, automatic configuration, self-healing and topology detection.
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Paper Nr: 27
Title:

Citizen Participation in Urban Planning-Management Processes - Assessing Urban Accessibility in Smart Cities
Authors:

Raquel Pérez-delHoyo, María Dolores Andújar-Montoya, Higinio Mora and Virgilio Gilart-Iglesias
Abstract: The concept of Smart City, supported by the latest technological advances in the field of Information and Communication Technology, offers great potential to meet the challenges of cities in the economic globalization context. As a consequence, the present work is focused on the deployment of these technologies through public participation activities to generate knowledge for the processes of urban planning, design and management.The methodology proposed in this work allows obtaining information about accessibility problems directly from citizens, based on their own experience. Citizens have a communication channel that allows them to inform, at any time and in any place, about all the accessibility problems they encounter when they move around a city in their daily activity. The work presents a Case Study focused on a experience of citizen participation which has been developed to evaluate the accessibility of urban environments in Benalúa neighbourhood of Alicante in Spain. A diverse group of neighbors of different ages, gender and abilities have participated in the experience. After the experimentation it was concluded that the research offers new forms of communication to facilitate information flows between the Administration and citizens, allowing their integration and feedback.
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Paper Nr: 40
Title:

Multi-agent Model for Domotics and Smart Houses
Authors:

Guillaume Guerard, Loup-Noé Levy and Hugo Pousseur
Abstract: Most of the demand-side management programs focus on the interactions between an aggregator and its users. Moreover, renewable energy production being irregular, increasing their number implies to predict consumption and energy storage or discharge in real time. This is why the consumption patterns of every device connected to the grid must be organized in order to optimize the global consumption of the grid. Studying the smart grid through modeling and simulation provides us with valuable results which cannot be obtained in the real world due to time and cost related constraints. In this paper, we focus on a multi-agent model to simulate a microgrid and domotics through automaton and energy consumption scheduling.
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Paper Nr: 46
Title:

Measuring Happyiness and Wellbeing in Smart Cities - Lisbon Case Study
Authors:

Joana Branco Gomes, João Sousa Rego and Miguel de Castro Neto
Abstract: This paper presents the results of a data analysis on Lisbon rates of happiness and wellbeing as a measure of smart cities. To analyse this issue we collected, respectively, objective and subjective data from an open portal data website and a survey of subjective data filed by the citizens, represented at parish level, using a ranking of 1 to 5. The 52 datasets of objective and subjective data supported the production of a dashboard at parish level. The parishes with high performances (Avenidas Novas, Misericórdia, Santo António and S. Vicente) are all in the centre of the city. One of the possible conclusions is that there is a cluster of higher values in the city centre, that could be explain for economic reasons and also because to the proximity to city facilities.
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Paper Nr: 54
Title:

Digitalization of Legacy Building Data - Preparation of Printed Building Plans for the BIM Process
Authors:

Hermann Mayer
Abstract: Today, preparing existing building plans for a 3D BIM (building information modelling) process is a tedious work involving lots of manual steps. Even if the data is already in a digitized and vectorised format, the lack of semantics often prevents the data from being processed in automated workflows. However, the requirements for simulation tasks, which are relevant for brown-field projects, are not too demanding regarding the level of detail. In most cases (e.g. optimized placement of fire safety equipment, evacuation planning, daylighting simulation etc.), only information about spaces and their interconnections are needed. If coefficients for the heat-transfer between spaces can be added, also energy simulations can be performed. Therefore the goal of this work is to provide a basic standardized building model, which can be derived from all sorts of legacy data (different CAD formats and styles and even scanned plans). Also basic semantics will be added to the data, which complements the definitions of the BIM standard used in this work. Based on the models, building simulation can be enabled as a cheap surplus service, promoting the usage of cloud implementation of the BIM process.
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Area 2 - Sustainable Computing and Systems

Full Papers
Paper Nr: 16
Title:

A Model Predictive Control based Peak Shaving Application for a Grid Connected Household with Photovoltaic and Battery Storage
Authors:

Deepranjan Dongol, Thomas Feldmann and Elmar Bollin
Abstract: The increase in households with grid connected Photovoltaic (PV) battery system poses challenge for the grid due to high PV feed-in as a result of mismatch in energy production and load demand. The purpose of this paper is to show how a Model Predictive Control (MPC) strategy could be applied to an existing grid connected household with PV battery system such that the use of battery is maximized and at the same time peaks in PV energy and load demand are reduced. The benefits of this strategy are to allow increase in PV hosting capacity and load hosting capacity of the grid without the need for external signals from the grid operator. The paper includes the optimal control problem formulation to achieve the peak shaving goals along with the experiment set up and preliminary experiment results. The goals of the experiment were to verify the hardware and software interface to implement the MPC and as well to verify the ability of the MPC to deal with the weather forecast deviation. A prediction correction has also been introduced for a short time horizon of one hour within this MPC strategy to estimate the PV output power behavior.
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Paper Nr: 17
Title:

Intelligent Thermal Control Method for Small-Size Air Conditioning System
Authors:

Hung-Wen Lin, Min-Der Wu, Guan-Wen Chen and Ying Xuan Tan
Abstract: To decrease the energy consumption and maintaining the comfort of the area, a great deal of work has been done on HVAC control algorithms. A control system with the least enthalpy difference theory applied is proposed in this paper. By using the indoor air temperature and relative humidity as the feedback of the control system, the temperature set for the air conditioner is able to satisfy the indoor thermal comfort. The simulation and experimental results of this controller have shown positive energy saving while maintaining indoor thermal comfort.
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Paper Nr: 18
Title:

IoT Architecture for Decentralised Heating Control in Households
Authors:

Gillian Basso, Dominique Gabioud and Pierre Roduit
Abstract: Over the last two decades, electrical energy generation has become more sustainable (photovoltaic, wind energy, etc.), but also more distributed, less predictable, and less controllable. Besides storage and flexible production, Demand Response (DR) offers great opportunities to help stabilizing the electrical grid. This paper presents how the flexibility of space and domestic hot water heating in existing residential buildings can be controlled for grid services. It focuses on the Internet of Things (IoT) framework including both hardware and software to connect existing buildings to a central Virtual Power Plant (VPP) intelligence. It also presents field experiments that were performed during the European FP7 SEMIAH project.
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Short Papers
Paper Nr: 43
Title:

Proactive Workload Management for Bare Metal Deployment on Microservers
Authors:

Daniel Schlitt, Christian Pieper and Wolfgang Nebel
Abstract: This paper introduces a concept for an energy-aware workload management (WM) for heterogeneous microserver environments. Its main focus is on highly dynamic service-driven workloads often coupled to user requests requiring fast response times. The WM is developed in scope of the M2DC (Modular Microserver Data Center) project, in which a new server generation of composable microservers is designed. Targeting an easy industrial applicability, the underlying middleware is based on a turnkey OpenStack platform. As part of that middleware, the WM makes use of workload/utilization and power data as well as corresponding (prediction) models to deploy applications on the most suitable microservers and temporarily shut down unused capacities, either proactively or reactively (in case of deviations from forecasts). The WM has been implemented and simulated within a virtual environment. However, the integration, refinement and evaluation on the new M2DC hardware is still work in progress.
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Paper Nr: 60
Title:

SLES: Synchronized Load-Aware Energy Scheme in Mobile Broadband Network
Authors:

Ibrahim Saidu, Aminu Mohammed, Bello Nakone and Sagiru Musa Tanimu
Abstract: The proliferation of mobile devices, which are usually battery enabled, has made energy saving a critical challenge in mobile broadband networks such as WiMAX. An efficient energy saving scheme becomes necessary in order to prolong the lifetime of a mobile subscriber station. Existing energy saving scheme uses exponential sleep pattern to compute sleep window sizes which lead to energy inefficiency when dealing with variable bit traffic. In addition, it fails to synchronize the previous sleep interval and the listening window which result to an increase in average delay. In this paper, a Synchronized Load-Aware Energy Scheme (SLES) is proposed to improve energy efficiency and to reduce the average delay. The SLES determines sleep window intervals based on traffic estimation at the base station. The scheme also synchronizes previous sleep interval and the listening window. Simulation results prove that the SLES significantly outperforms the compared schemes in terms of energy efficiency and average delay.
Paper Nr: 4
Title:

Creating a Roadmap for Smart City Development based on Regional Strategy Work
Authors:

Mikko Mantyneva and Heikki Ruohomaa
Abstract: This paper focuses on introducing a strategy linked roadmap supporting coordinated and collaborative smart city development between various stakeholders. The primary focus on the roadmapping work is to identify those actions required to make smart city ambitions a reality in a region. In a case study, a roadmapping approach is linked to regional strategy work in Southern Finland. The introduced roadmap is generic by nature and it could be applied also to other cities and regions willing to steer their smart city initiatives further.
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Paper Nr: 44
Title:

Usage Analytics: Research Directions to Discover Insights from Cloud-based Applications
Authors:

Duc-Tien Dang-Nguyen, Manoj Kesavulu and Markus Helfert
Abstract: Usage in the software field deals with knowledge about how end-users use the application and how the application reacts to the users’ actions. In a complex and heterogeneous cloud computing environment, the process of extracting and analysing usage data is difficult since the usage data is spread across various front-end interfaces and back-end underlying infrastructural components of the cloud that host the application. In this paper we propose Usage Analytics, a set of potential research directions that could help tackle various challenges in the cloud domain. We provide an overview of usage analytics in the cloud environment and propose how to discover insights using these analytics solutions. We give some discussions about challenges in discovering insights from the usage data as well as provide vision of how usage data will bring benefits to the cloud environment.
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Paper Nr: 56
Title:

Market Design for Renewable Energy Dissemination
Authors:

Jun Maekawa and Koji Shimada
Abstract: Renewable energy has less environmental impact and little marginal cost. Due to this nature, it is desirable to disseminate it from the viewpoint of economic efficiency. On the other hand, because of the uncertainty of the supply of renewable energy and the specialty of electricity as goods, it is difficult to achieve efficient allocation even if the normal competitive market is applied as it is. Problems such as how to secure power capacity and how to deal with the risk of power outage are concerned in European countries that have already adopted measures to cope with these problems in practice. These problems suggest that a new market design is required for the power market.
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Area 3 - Energy-Aware Systems and Technologies

Full Papers
Paper Nr: 5
Title:

Spatial Dependence of Solar Photovoltaic Systems: Data Gathering Process, Related Issues and Preliminary Results
Authors:

Sergio Copiello
Abstract: In a previous study (Copiello and Grillenzoni, En. Proc., 2017), we have proven the solar photovoltaic capacity in Italy to be characterized by spatial dependence. In that research, the units of analysis were the Italian provinces, which correspond to level 3 of the European NUTS (Nomenclature of territorial units for statistics) classification. Here we focus on new data encoded according to the Italian townships, namely, the municipalities corresponding to level 2 of the European LAU (Local administrative units) classification. The change of scale is a huge challenge, due to both the difficulty to find reliable information and the time-consuming definition of the proximity structure of the units: while the provinces are about 100, the Italian municipalities are several thousands, and each one shares the borders with many others. In particular, three neighboring regions - Veneto, Trentino-Alto Adige, and Friuli-Venezia Giulia, in North-eastern Italy - and their 1,121 towns are considered in this study, which primarily aims to delve into the issues related to the data gathering process. As far as the preliminary findings are concerned, we find more clues about the role played by the so-called neighborhood and peer effects.
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Paper Nr: 7
Title:

Mining Sequential Patterns for Appliance Usage Prediction
Authors:

Mathieu Kalksma, Brian Setz, Azkario Rizky Pratama, Ilche Georgievski and Marco Aiello
Abstract: Reducing the energy consumption in buildings and homes can be achieved by predicting how energy-consuming appliances are used, and by discovering their patterns. To mine these patterns, a smart-metering architecture needs to be in place complemented by appropriate data analysis mechanisms. Once the usage patterns are obtained, they can be employed to optimize the way energy from renewable installations, home batteries, and even microgrids is managed. We present an approach and related experiments for mining sequential patterns in appliance usage. In particular, we mine patterns that allow us to perform device usage prediction, energy usage prediction, and device usage prediction with failed sensors. The focus of this work is on the sequential relationships between the state of distinct devices. We use data sets from three existing buildings, of which two are households and one is an office building. The data is used to train our modified Support-Pruned Markov Models which use a relative support threshold. Our experiments show the viability of the approach, as we achieve an overall accuracy of 87% in device usage predictions, and up to 99% accuracy for devices that have the strongest sequential relationships. For these devices, the energy usage predictions have an accuracy of around 90%. Predicting device usage with failed sensors is feasible, assuming there is a strong sequential relationship for the devices.
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Paper Nr: 11
Title:

Blending Acceptance as Additional Evaluation Parameter into Carbon Capture and Utilization Life-Cycle Analyses
Authors:

K. Arning, B. Zaunbrecher, A. Sternberg, A. Bardow and M. Ziefle
Abstract: Carbon Capture and Utilization (CCU) captures and uses CO2 as a feedstock to produce carbon-based saleable products. However, sustainable technology innovations are only attractive to investors and justify (public) subsidies if they provide economical or ecological added value. Therefore, life cycle analyses (LCA) are applied to identify the environmentally most optimal option of a technology scenario. Since LCA do not address the social dimension of sustainable innovations so far, a study is presented, where acceptance is assessed as additional life cycle evaluation parameter. A prestudy (qualitative interviews, n = 25 participants) was run to identify acceptance-relevant parameters of CCU site deployment. In a conjoint study (n = 110), which investigated the acceptance of CCU site deployment scenarios, the profitability, CO2-source, and type of CO2-derived product were systematically varied as acceptance-relevant criteria. Findings show, that profitability had the highest impact on CCU technology scenario preferences. Fuel was the most attractive CCU product option and steel plants were the most preferred CO2-source. In sensitivity analyses specific acceptable and nonacceptable CCU technology scenarios were identified. The assessment of acceptance for CCU deployment scenario parameters allows to include acceptance as additional evaluation and weighting parameter into life cycle analyses of CCU technology scenarios.
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Paper Nr: 13
Title:

Forecasting Short-term Solar Radiation for Photovoltaic Energy Predictions
Authors:

Alessandro Aliberti, Lorenzo Bottaccioli, Giansalvo Cirrincione, Enrico Macii, Andrea Acquaviva and Edoardo Patti
Abstract: In the world, energy demand continues to grow incessantly. At the same time, there is a growing need to reduce CO2 emissions, greenhouse effects and pollution in our cities. A viable solution consists in producing energy by exploiting renewable sources, such as solar energy. However, for the efficient use of this energy, accurate estimation methods are needed. Indeed, applications like Demand/Response require prediction tools to estimate the generation profiles of renewable energy sources. This paper presents an innovative methodology for short-term (e.g. 15 minutes) forecasting of Global Hor- izontal Solar Irradiance (GHI). The proposed methodology is based on a Non-linear Autoregressive neural network. This neural network has been trained and validated with a dataset consisting of solar radiation samples collected for four years by a real weather station. Then GHI forecast, the output of the neural network, is given as input to our Photovoltaic simulator to predict energy production in short-term time periods. Finally, experimental results for both GHI forecast and Photovoltaic energy prediction are presented and discussed.
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Paper Nr: 48
Title:

Soft Load Shedding: An Efficient Approach to Manage Electricity Demand in a Renewable Rich Distribution System
Authors:

Tayyab Aslam and Naveed Arshad
Abstract: Matching demand and supply of electricity generation is difficult in a renewable-rich system. This is partly due to the long-term variability and short-term uncertainty of wind and solar. Utilities use several approaches to deal with the variations of renewable generation. Some of these include having extra fossil fuel based peaker plants, managing flexible loads using demand-side management, real-time pricing etc. In this paper, we present another approach to manage supply variations by introducing semi-flexible loads at the demand side. These semi-flexible loads are residential loads that cannot be shut down or be moved completely to another hour but have the possibility to shed a small percentage of their load for a short time. This approach called soft load shedding is challenging as residential customers have the multitude of energy usage patterns. In this paper we compare and contrast three soft load shedding techniques and discuss their strengths and shortcomings in matching the demand with available supply.
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Paper Nr: 61
Title:

Demand Response of Medical Freezers in a Business Park Microgrid
Authors:

Rosa Morales González, Madeleine Gibescu, Sjef Cobben, Martijn Bongaerts, Marcel de Nes-Koedam and Wouter Vermeiden
Abstract: This paper presents a demand response (DR) framework that utilizes the flexibility inherent to the thermodynamic behavior of four groups of independently-controlled medical freezers in a privately-owned business park microgrid that contains rooftop photovoltaics (PV). The optimization objectives may be chosen from the following 3 options: minimizing electricity exchanges with the public grid; minimizing costs by considering prices and RES availability; and minimizing peak load. The proposed DR framework combines thermodynamic models with automated, genetic-algorithm-based optimization, resulting in demonstrable benefits in terms of cost, energy efficiency, and peak power reduction for the consumer, local energy producer, and grid operator. The resulting optimal DR schedules of the freezers are compared against unoptimized, business-as-usual scenarios with- and without PV. Results show that flexibility can be harnessed from the thermal mass of the freezers and their contents, improving the cost- and energy performance of the system with respect to the business-as-usual scenarios.
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Paper Nr: 62
Title:

Flexibility Definition for Smart Grid Cells in a Decentralized Energy System
Authors:

Helen Sawall, Andreas Scheuriker and Daniel Stetter
Abstract: The networking of individual cells to form a decentralised network represents a possible approach for an energy system of the future, which is up to the challenges of the energy transition, such as stochastic electricity generation through renewable energies and the participation of many small producers. In this context, the sharing of flexibility in load profiles of cells requires a uniform definition to create a communication basis. This paper presents a generic description of flexibility by defining the latter as the set of all possible and permissible load profiles, taking into account dependencies between plants, technical constraints and maintaining energy balance within networks. The resulting solution space for load optimization problems, in form of the flexibility of a cell, can be described as a partial set of the RpT by derived constraints. The solution space is the keystone for further flexibility communication.
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Short Papers
Paper Nr: 21
Title:

Uncovering the Impact of Trust and Perceived Fairness on the Acceptance of Wind Power Plants and Electricity Pylons
Authors:

Anika Linzenich and Martina Ziefle
Abstract: Success of the German energy transition towards renewables relies not only on technical and economic factors, but also on the public acceptance of the required energy infrastructure, e.g., wind power plants and power lines. In this paper, acceptance-relevant process characteristics (perceived fairness of project planning, trust in stakeholders, and trust in technology) were investigated by comparing users’ acceptance for wind energy and power line planning, using an online survey in Germany (n = 70). Acceptance, trust, and perceived fairness were significantly higher for wind power plants than for electricity pylons. General acceptance of wind power plants and electricity pylons was affected by trust, with trust in technology playing a more important role than trust in stakeholders. Local acceptance was directly influenced by general acceptance and perceived fairness. Trust indirectly affected local acceptance through general acceptance. The results contribute to an improved planning of energy infrastructure by adequately addressing public requirements.
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Paper Nr: 45
Title:

Distributed Infrastructure for Multi-Energy-Systems Modelling and Co-simulation in Urban Districts
Authors:

Lorenzo Bottaccioli, Edoardo Patti, Enrico Macii and Andrea Acquaviva
Abstract: In recent years, many governments are promoting a widespread deployment of Renewable Energy Sources (RES) together with an optimization of energy consumption. The main purpose consists on decarbonizing the energy production and reducing the CO2 footprints. However, RES imply uncertain energy production. To foster this transition, we need novel tools to model and simulate Multi-Energy-Systems combining together different technologies and analysing heterogeneous information, often in (near-) real-time. In this paper, first we present the main challenges identified after a literature review and the motivation that drove this research in developing MESsi. Then, we propose MESsi, a novel distributed infrastructure for modelling and cosimulating Multi-Energy-Systems. This infrastructure is a framework suitable for general purpose energy simulations in cities. Finally, we introduce possible simulation scenarios that have different spatio-temporal resolutions. Space resolution ranges from the single dwelling up to districts and cities. Whilst, time resolution ranges from microseconds, to simulate the operational status of distribution networks, up to years, for planning and refurbishment activities.
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Paper Nr: 51
Title:

Concept for Intra-Hour PV Generation Forecast based on Distributed PV Inverter Data - An Approach Considering Machine Learning Techniques and Distributed Data
Authors:

Stefan Übermasser, Simon Kloibhofer, Philipp Weihs and Matthias Stifter
Abstract: The mass-introduction of small scale power generation units like photovoltaic systems at household levels increase the risk for system unbalances, due to their stochastic generation profile. Additionally, upcoming technologies such as electric vehicles, battery storage systems and energy management systems lead to a change from consumer households to prosumers with a significant different residual load profile. For optimizing the profile of future prosumers, especially the forecast for PV generation is crucial. Whilst traditional weather forecasts are based on a few hundred metering locations in the case of Austria, more than 55000 PV systems are currently connected to the Austrian Power grid. Due to the low areal coverage of common metering locations, weather forecasts do not take local phenomena like shadows from clouds into account. An approach using generation data from neighbouring PV systems together with machine learning methods provides a promising alternative for individual location based intra-hour forecasts. This paper describes the requirements and methods of such a concept and concludes with a first proof of concept.
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Paper Nr: 55
Title:

An Overview of Renewable Smart District Heating and Cooling Applications with Thermal Storage in Europe
Authors:

Fivos Galatoulas, Marc Frere and Christos Ioakimidis
Abstract: A series of transformations in heat and cold distribution systems is undergoing with the introduction of 4th generation District Heating and Cooling (DHC) technologies. At the center of this process is the integration of renewable technologies, such as solar heating, geothermal systems with large heat pumps and cooling from natural water formations. In this context, smart DHC systems are designed and early prototype implementations are demonstrated in sites across the world. The purpose of this paper is to trace the latest advancements in existing DHC networks and to identify early smart city technologies incorporated. A summary of basic components and characteristics is attempted with focus on thermal storage technologies coupled with renewable heating and cooling.
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Paper Nr: 57
Title:

The Good, the Bad and the Ugly: Affect and its Role for Renewable Energy Acceptance
Authors:

Barbara S. Zaunbrecher, Katrin Arning and Martina Ziefle
Abstract: To foster a socially accepted energy transition, it is essential to gain insights into motives for acceptance or rejection of technologies related to renewable energies. The study aims to shed light on the emotional evaluation of renewable energy technologies and in how far the affective responses are correlated with the acceptance of those technologies. An empirical study is conducted in which a semantic differential is used to assess emotional evaluation of wind power, solar power (PV) and biomass for electricity production. Furthermore, general acceptance of the technologies was assessed. It was found that not only did the technologies differ in terms of emotional responses they evoked, but that those responses also varied significantly between groups of high and low levels of acceptance concerning the respective energy technology. By analyzing spontaneous associations with the three energy sources, possible reasons for the affective evaluations were identified, which can provide essential topics for the communication about those technologies. Overall, the three renewable energy technologies revealed different emotional evaluations which might considerably impact the overall acceptance. It is argued that knowledge about such affective perceptions is useful to tailor energy technology development in early phases and to steer public information and communication strategies.
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Paper Nr: 64
Title:

A Flexible Data Migration Strategy for Power Savings in Distributed Storage Systems
Authors:

Koji Hasebe, Sho Takai and Kazuhiko Kato
Abstract: We present a power-saving technique for datacenter-scale distributed storage systems. In particular, we focus on storage in environments where a large number of data are continuously uploaded, as typified by the platforms of social networking services. In achieving this objective, the main idea is to use virtual nodes and migrate them dynamically so as to skew the workload toward a small number of disks without overloading them. We improve this previously introduced idea by making the data migration strategy flexible in the present study. As a result, our proposed technique can maintain a high-load aggregation rate during the continuous addition of disks, which was difficult to handle in our previous study. The performance of our technique is evaluated in simulations. The results show that our technique improves the technique in the previous study and effectively skews the workload during a constant massive influx of data.
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Paper Nr: 10
Title:

A Decentralized Algorithm to Revisit the Debate of Centralization and Decentralization Approaches for Cloud Scheduling
Authors:

Cheikhou Thiam, Georges Da Costa and Jean-Marc Pierson
Abstract: In Cloud Computing, scheduling jobs is a major and difficult issue. The main objectives of cloud services providers are the efficient use of their computing resources. Existing cloud management systems are mostly based on centralized architectures and energy management mechanisms are suffering several limitations. To address these limitations, our contribution is to design, implement, and evaluate a novel cloud management system which provides a holistic energy-efficient VM management solution by integrating advanced VM management mechanisms such as underload mitigation, VM consolidation, and power management. In this paper, we introduce a distributed task scheduling algorithm for Clouds that enables to schedule VMs cooperatively and dynamically inside a federation of clouds. We evaluated our prototype through simulations, to compare our decentralized approach with a centralized one. Our results showed that the proposed scheduler is very reactive.
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Paper Nr: 20
Title:

High Performance and Privacy for Distributed Energy Management: Introducing PrivADE+ and PPPM
Authors:

Daniel Brettschneider, Daniel Hölker and Ralf Tönjes
Abstract: Distributed Energy Management (DEM) will play a vital role in future smart grids. An important and often overlooked factor in this concept is privacy. This paper presents two privacy-preserving DEM algorithms called PrivADE+ and PPPM. PrivADE+ uses a round-based energy management procedure for switchable and dynamically adaptable loads. PPPM utilises on the market-based PowerMatcher approach. Both algorithms apply homomorphic encryption to privately gather aggregated data and exchange commands. Simulations show that PrivADE+ and PPPM achieve good energy management quality with low communication requirements and without negative influences on robustness.
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Paper Nr: 49
Title:

Evaluation of Small Modular Wind Energy Conversion System
Authors:

Christos S. Ioakimidis, Fivos Galatoulas and Robert R. Porter
Abstract: A probabilistic method based on the Weibull distribution for predicting the economic performance and reliability of small autonomous wind energy conversion (WEC) systems is described. These systems contain WARP (Wind Amplified Rotor Platform), an adaptable design of wind generator, along with the WARP-GT (generation-transmission) system which combines both electricity generation through wind energy conversion and electric power transmission. Furthermore, this work explores the use of pumped-storage, aiming to firm up the intermittent nature of the system. Results of this prediction are applied in the cost estimation of an investment from the private owner view. The cost estimation is based on a power law ratio for industrial equipment. Results are presented for two case studies located in Greek islands.
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