This is a review of the literature on community energy. We analyze more than 250 studies that appeared in the academic literature in the period 1997-2018. We investigate the timing regarding the appearance of these studies, the geographical orientation of the research, and the journals in which the articles appeared. We also analyse the keywords used to identify the research. Further, we relate the articles to the theoretical perspectives employed. We also analyse keywords used by the authors in relation to the particular approaches employed and reflect on the country specifics of the case studies. We find that the majority of studies on community energy did appear in the last couple of years. Especially the UK, US, Germany and the Netherlands are being investigated. Energy Policy published most of the studies. Different theoretical perspectives study community energy, especially Governance, Sociology, Economics, Planning, Technology, and Transition. We conclude that the study of community energy is still in its infancy as there is little commonality in the terminology and key concepts used. Studying community energy requires further improvement in order to better integrate the different theoretical perspectives and to ground policy decisions.
MULTIFILE
This is a review of the literature on community energy. We analyze more than 250 studies that appeared in the academic literature in the period 1997-2018. We investigate the timing regarding the appearance of these studies, the geographical orientation of the research, and the journals in which the articles appeared. We also analyse the keywords used to identify the research. Further, we relate the articles to the theoretical perspectives employed. We also analyse keywords used by the authors in relation to the particular approaches employed and reflect on the country specifics of the case studies. We find that the majority of studies on community energy did appear in the last couple of years. Especially the UK, US, Germany and the Netherlands are being investigated. Energy Policy published most of the studies. Different theoretical perspectives study community energy, especially Governance, Sociology, Economics, Planning, Technology, and Transition. We conclude that the study of community energy is still in its infancy as there is little commonality in the terminology and key concepts used. Studying community energy requires further improvement in order to better integrate the different theoretical perspectives and to ground policy decisions.
MULTIFILE
The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable energy supply. This enables grid integration in existing energy networks with limited capacity and maximises use of decentralized sustainable generation. Buildings can play a key role in the optimization of the grid capacity by applying demand-side management control. To adjust the grid energy demand profile of a building without compromising the user requirements, the building should acquire some energy flexibility capacity. The main ambition of the Brains for Buildings Work Package 2 is to develop smart control strategies that use the operational flexibility of non-residential buildings to minimize energy costs, reduce emissions and avoid spikes in power network load, without compromising comfort levels. To realise this ambition the following key components will be developed within the B4B WP2: (A) Development of open-source HVAC and electric services models, (B) development of energy demand prediction models and (C) development of flexibility management control models. This report describes the developed first two key components, (A) and (B). This report presents different prediction models covering various building components. The models are from three different types: white box models, grey-box models, and black-box models. Each model developed is presented in a different chapter. The chapters start with the goal of the prediction model, followed by the description of the model and the results obtained when applied to a case study. The models developed are two approaches based on white box models (1) White box models based on Modelica libraries for energy prediction of a building and its components and (2) Hybrid predictive digital twin based on white box building models to predict the dynamic energy response of the building and its components. (3) Using CO₂ monitoring data to derive either ventilation flow rate or occupancy. (4) Prediction of the heating demand of a building. (5) Feedforward neural network model to predict the building energy usage and its uncertainty. (6) Prediction of PV solar production. The first model aims to predict the energy use and energy production pattern of different building configurations with open-source software, OpenModelica, and open-source libraries, IBPSA libraries. The white-box model simulation results are used to produce design and control advice for increasing the building energy flexibility. The use of the libraries for making a model has first been tested in a simple residential unit, and now is being tested in a non-residential unit, the Haagse Hogeschool building. The lessons learned show that it is possible to model a building by making use of a combination of libraries, however the development of the model is very time consuming. The test also highlighted the need for defining standard scenarios to test the energy flexibility and the need for a practical visualization if the simulation results are to be used to give advice about potential increase of the energy flexibility. The goal of the hybrid model, which is based on a white based model for the building and systems and a data driven model for user behaviour, is to predict the energy demand and energy supply of a building. The model's application focuses on the use case of the TNO building at Stieltjesweg in Delft during a summer period, with a specific emphasis on cooling demand. Preliminary analysis shows that the monitoring results of the building behaviour is in line with the simulation results. Currently, development is in progress to improve the model predictions by including the solar shading from surrounding buildings, models of automatic shading devices, and model calibration including the energy use of the chiller. The goal of the third model is to derive recent and current ventilation flow rate over time based on monitoring data on CO₂ concentration and occupancy, as well as deriving recent and current occupancy over time, based on monitoring data on CO₂ concentration and ventilation flow rate. The grey-box model used is based on the GEKKO python tool. The model was tested with the data of 6 Windesheim University of Applied Sciences office rooms. The model had low precision deriving the ventilation flow rate, especially at low CO2 concentration rates. The model had a good precision deriving occupancy from CO₂ concentration and ventilation flow rate. Further research is needed to determine if these findings apply in different situations, such as meeting spaces and classrooms. The goal of the fourth chapter is to compare the working of a simplified white box model and black-box model to predict the heating energy use of a building. The aim is to integrate these prediction models in the energy management system of SME buildings. The two models have been tested with data from a residential unit since at the time of the analysis the data of a SME building was not available. The prediction models developed have a low accuracy and in their current form cannot be integrated in an energy management system. In general, black-box model prediction obtained a higher accuracy than the white box model. The goal of the fifth model is to predict the energy use in a building using a black-box model and measure the uncertainty in the prediction. The black-box model is based on a feed-forward neural network. The model has been tested with the data of two buildings: educational and commercial buildings. The strength of the model is in the ensemble prediction and the realization that uncertainty is intrinsically present in the data as an absolute deviation. Using a rolling window technique, the model can predict energy use and uncertainty, incorporating possible building-use changes. The testing in two different cases demonstrates the applicability of the model for different types of buildings. The goal of the sixth and last model developed is to predict the energy production of PV panels in a building with the use of a black-box model. The choice for developing the model of the PV panels is based on the analysis of the main contributors of the peak energy demand and peak energy delivery in the case of the DWA office building. On a fault free test set, the model meets the requirements for a calibrated model according to the FEMP and ASHRAE criteria for the error metrics. According to the IPMVP criteria the model should be improved further. The results of the performance metrics agree in range with values as found in literature. For accurate peak prediction a year of training data is recommended in the given approach without lagged variables. This report presents the results and lessons learned from implementing white-box, grey-box and black-box models to predict energy use and energy production of buildings or of variables directly related to them. Each of the models has its advantages and disadvantages. Further research in this line is needed to develop the potential of this approach.
Client: Foundation Innovation Alliance (SIA - Stichting Innovatie Alliantie) with funding from the ministry of Education, Culture and Science (OCW) Funder: RAAK (Regional Attention and Action for Knowledge circulation) The RAAK scheme is managed by the Foundation Innovation Alliance (SIA - Stichting Innovatie Alliantie) with funding from the ministry of Education, Culture and Science (OCW). Early 2013 the Centre for Sustainable Tourism and Transport started work on the RAAK-MKB project ‘Carbon management for tour operators’ (CARMATOP). Besides NHTV, eleven Dutch SME tour operators, ANVR, HZ University of Applied Sciences, Climate Neutral Group and ECEAT initially joined this 2-year project. The consortium was later extended with IT-partner iBuildings and five more tour operators. The project goal of CARMATOP was to develop and test new knowledge about the measurement of tour package carbon footprints and translate this into a simple application which allows tour operators to integrate carbon management into their daily operations. By doing this Dutch tour operators are international frontrunners.Why address the carbon footprint of tour packages?Global tourism contribution to man-made CO2 emissions is around 5%, and all scenarios point towards rapid growth of tourism emissions, whereas a reverse development is required in order to prevent climate change exceeding ‘acceptable’ boundaries. Tour packages have a high long-haul and aviation content, and the increase of this type of travel is a major factor in tourism emission growth. Dutch tour operators recognise their responsibility, and feel the need to engage in carbon management.What is Carbon management?Carbon management is the strategic management of emissions in one’s business. This is becoming more important for businesses, also in tourism, because of several economical, societal and political developments. For tour operators some of the most important factors asking for action are increasing energy costs, international aviation policy, pressure from society to become greener, increasing demand for green trips, and the wish to obtain a green image and become a frontrunner among consumers and colleagues in doing so.NetworkProject management was in the hands of the Centre for Sustainable Tourism and Transport (CSTT) of NHTV Breda University of Applied Sciences. CSTT has 10 years’ experience in measuring tourism emissions and developing strategies to mitigate emissions, and enjoys an international reputation in this field. The ICT Associate Professorship of HZ University of Applied Sciences has longstanding expertise in linking varying databases of different organisations. Its key role in CARMATOP was to create the semantic wiki for the carbon calculator, which links touroperator input with all necessary databases on carbon emissions. Web developer ibuildings created the Graphical User Interface; the front end of the semantic wiki. ANVR, the Dutch Association of Travel Agents and Tour operators, represents 180 tour operators and 1500 retail agencies in the Netherlands, and requires all its members to meet a minimum of sustainable practices through a number of criteria. ANVR’s role was in dissemination, networking and ensuring CARMATOP products will last. Climate Neutral Group’s experience with sustainable entrepreneurship and knowledge about carbon footprint (mitigation), and ECEAT’s broad sustainable tourism network, provided further essential inputs for CARMATOP. Finally, most of the eleven tour operators are sustainable tourism frontrunners in the Netherlands, and are the driving forces behind this project.
Wat is de mogelijke rol van lokale duurzame energiesystemen en –initiatieven in de overgang naar een duurzame samenleving? En hoe kunnen op lokale toepassing gerichte innovaties worden ontwikkeld en toegepast op een zodanige manier dat deze bij lokale systemen en initiatieven aansluiten?Deze vragen staan centraal in dit onderzoeksproject dat zich richt op innovaties die rekening houden met een grotere rol van burgers bij een duurzame energievoorziening. Het project behelst echter meer dan het verrichten van onderzoek. Het beoogt bouwstenen te leveren voor een duurzame samenleving waarin meer ruimte is voor lokale (burger)initiatieven. We stellen drie deelprojecten voor:1. een vergelijkende studie naar energiecoöperaties en vergelijkbare innovatieve initiatieven, binnen en buiten Nederland, in heden en verleden. Daarbij hopen we lering te kunnen trekken uit de succesvolle ervaringen in Denemarken en Oostenrijk en van innovaties door coöperatiesen collectieven in het verleden.2. een analyse van energie-innovaties die beogen aan te sluiten bij lokale energiesystemen. Concreet zal het onderzoek zich richten op speciale batterijen, ontwikkeld dor het bedrijf Dr.Ten, en een soort slimme grote zoneboiler, ontwikkeld door het gelijknamige bedrijf Ecovat.3. De ontwikkeling van drie scenario’s, gebaseerd op inzichten uit studies 1 en 2. De scenario’s zullen bijvoorbeeld inhoudelijk verschillen in de mate waarin deze geïntegreerd zijn in bestaande energiesystemen. Deze zullen worden ontwikkeld en besproken met relevante stakeholders.Het onderzoek moet leiden tot een nauwkeurig overzicht van de mate van interesse en betrokkenheid van stakeholders en van de beperkingen en mogelijkheden van lokale energiesystemen en daarbij betrokken technologie. Ook leidt het tot een routemap voor duurzame energiesystemen op lokaal niveau. Het project heeft een technisch aspect, onderzoek naar verfijning en ontwikkeling van de technologie en een sociaal en normatief aspect, studies naar aansluitingsmogelijkheden bij de wensen en mogelijkheden van burgers, instanties en bedrijven in Noord-Nederland. Bovenal is het integratief en ontwerpend van karakter.This research proposal will explore new socio- technical configurations of local community-based sustainable energy systems. Energy collectives successfully combine technological and societal innovations, developing new business and organization models. A better understanding of their dynamics and needs will contribute to their continued success and thereby contribute to fulfilling the Top Sector’s Agenda. This work will also enhance the knowledge position of the Netherlands on this topic. Currently, over 500 local energy collectives are active in The Netherlands, many of them aim to produce their own sustainable energy, with thousands more in Europe. These collectives search for a new more local-based ways of organizing a sustainable society, including more direct democratic decision-making and influence on local living environment. The development of the collectives is enabled by openings in policy but –evenly important - by innovations in local energy production technologies (solar panels, windmills, biogas installations). Their future role in the sustainable energy transition can be strengthened by careful aligning new organizational and technological innovations in local energy production, storage and smart micro-grids.
In our increasingly global society, organizations face many opportunities in innovation, improved productivity and easy access to talent. At the same time, one of the greatest challenges, businesses experience nowadays, is the importance of social and/or human capital for their effectiveness and success (Backhaus and Tikoo, 2004; Mosley, 2007; Theurer et al., 2018; Tumasjan et al., 2020). High-quality employees are crucial to the competitive strength of an organization in the global economy, as these employees have a major influence on organizational reputation (Dowling at al., 2012). An important question is how, under these global circumstances, organizations and companies in the Netherlands can best be stimulated to attract and preserve social capital.Several studies have suggested the scarcity of talent and the crucial importance of gaining competitive advantage with recruitment communication to find the fit between personal and fundamental organizational characteristics and values for employees (Cable and Edwards, 2004; Bhatnagar and Srivastava, 2008; ManPower Group, 2014; European Communication Monitor (ECM), 2018). In order to become an employer of choice, organizations have to not only stand out from the crowd during the recruitment process but work on developing loyalty and a culture of trust in their relationship with employees (ECM, 2018). Employer Branding focuses on the process of promoting an organization, as the “employer of choice” to a desired target group, which an organization aims to attract and retain. This process encompasses building an identifiable and unique employer identity or, more specifically, “the promotion of a unique and attractive image” as an employer (Backhaus 2004, p. 117; Backhaus and Tikoo 2004, p. 502).One of the biggest challenges in the North of the Netherlands at the moment is the urgent need for qualified labor in the IT, energy and healthcare sectors and the excess supply of international graduates who are able to find a job in the North of the Netherlands (AWVN, 2019). Talent development, as part of the regional labor market and education policy, has been an important part of government programs and strategies in the region (VNO-NCW Noord, 2018). For instance, North Netherlands Alliance (SNN) signed a Northern Innovation Agenda for the 2014-2020 period. SNN encourages, facilitates and connects ambitions focused on the development of the Northern Netherlands. Also, the Social Economic council North Netherlands issued an advice on the labour market in the North Netherlands (SER Noord Nederland, 2017). Knowledge institutions also contribute through employability programs. Another example is the Regional Talent Agreement (Talent Akkoord) framework issued by the Groningen educational institutions, employers and employees’ organizations and regional authorities in which they jointly commit to recruiting, training, retaining and developing talent for the Northern labor market. Most of the hires with a maximum of five year of experience at companies are represented by millennials. To learn what values make an attractive brand for employees in the of the North of the Netherlands, we conducted a first study. When ranking the most important values of corporate culture which matter to young employees, they mention creative freedom, purposeful work, flexibility, work-life balance as well as personal development. Whereas attractive workplace and job security do not matter to such a degree. A positive work environment and a good relationship with colleagues are valued highly (Hein, 2019).To date, as far as we know, no other employer branding studies have been carried out for the North of the Netherlands. Further insight is needed into the role of employer branding as a powerful tool to retain talent in Northern industry in particular.The goal of this study is to provide a detailed analysis of the regional industry in the Northern Netherlands and contribute to: 1) the scientific body of knowledge about whether and how employer branding can strengthen the attractiveness of a regional industry in the labor market; 2) the application of this knowledge and insights by companies and governments in local policy development in the North of the Netherlands.
