Energy Consumption Data as a Decision-making Tool for Energy Efficient Interventions in PA: The Case-study of Turin

European Directive 2012/27 states that Public Administration (PA) of member states must retrofit at least 3% of the useful area per year until 2020 for reducing their energy consumptions. On the other hand, the need for retrofitting PA owned buildings crashes with budget constraints and the necessity to guarantee services at all the time. For these reasons, when considering large publicly owned building stocks it is fundamental to establish prioritizing methodologies that help decision makers to address investments properly and efficiently. The present work considers the City of Turin as a case study for establishing a methodology to analyze the energy consumption data of a large buildings stock in terms of space heating, DHW and electricity needs. The first part of the work analyzed the stock as a whole, providing useful reference values for specific energy consumptions for different building categories (offices and schools in particular) and providing a tool for investments prioritization. In the second part, five buildings have been analyzed in detail collecting full historical data about electricity and thermal energy consumption. The union between data analysis and focused on-site inspections has allowed individuating specific inefficiencies in the energy-related facilities of the buildings. A preliminary economic analysis has been also assessed to show the strong energy and cost-saving potentials of simple low-cost actions aimed at the reduction of energy consumptions in PA owned buildings

Operational analysis of natural gas combined cycle CHP plants: energy performance and pollutant emissions

The natural gas-fired combined cycle (NGCC) plants are among the best technologies for power production, especially when operating in combined heat and power (CHP) generation feeding a district heating (DH) network. Even if usually designed to operate with very high utilization factors, thus satisfying mainly the base load, nowadays these plants are often used also as backup power. This is due mainly to the necessity to compensate the nonprogrammable renewable energy sources (RES) production, and it can be done, thanks to the good flexibility of these plants. However, in off-design conditions, the energy performance and the pollutant emissions may not be as good as the expected nominal ones. In this paper, the real operation of three NGCC units has been analysed in detail by considering mean hourly data over several years. A gas turbine efficiency curve at partial loads has been obtained, showing a decrease of conversion efficiency at lower unit loads. The CO emissions during the start-up and shut-down procedures of the plant reached values that are some orders of magnitude higher than in normal operation. This criticality should not be forgotten when using these units for frequent on-off operations

Opportunities for heat pumps adoption in existing buildings: real-data analysis and numerical simulation

The space heating of buildings represents one of the most important causes of energy consumption in Europe. The necessity to increase the share of renewable energy within the sector is hindered by the difficulty to renew and refurbish the existing building stock. In this context, heat pumps can have an important role in helping increase the renewable share of thermal energy production for the civil sector, in particular in those countries in which the electricity generation mix has large contributions from renewable energy sources. The paper presents a real-data analysis and a numerical simulation to evaluate the opportunity to substitute traditional heat generation systems (natural gas boilers) with air-source heat pumps or hybrid solutions. Three buildings located in Turin (Italy) are taken as case-study, and the hourly profiles of outdoor temperature, water supply temperature and absorbed thermal power are used to simulate four heat generation scenarios, that are compared in terms of primary energy consumption. Results show that (1) the substitution of the traditional natural gas boiler with a heat pump (with backup electric resistance) is always favorable (18% to 32% of primary energy reduction); (2) the influence of water supply temperature of each building on the overall primary energy saving is very high; (3) the adoption of a hybrid system (heat pump and natural gas boiler working alternatively) provides advantages in terms of reduced primary energy consumption only if the required supply water temperature is high. Further studies will investigate the economic aspects and will introduce comparisons with condensation natural gas boilers

Data Analysis of the Energy Performance of Large Scale Solar Collectors for District Heating

District Heating systems are an interesting opportunity for the increase of renewable energy share in the heating and cooling sector. The possibility of a centralized heat production allows the integration of multiple sources, including RES such as biomass, heat pumps and solar energy. This paper provides an operation analysis of the energy performance of large scale solar collectors supplying heat to DH systems in Denmark. Thanks to the availability of hourly data it has been possible to track the evolution of the collectors’ performance throughout the year, and compare it with the available radiation. The results show the good reliability of such systems, which are generally able to convert 40% to 60% of the available radiation, with annual production yields higher than 400 kWh/m2/y. The conversion efficiency shows some seasonal variations, being the winter months the less favorable, probably because of a lower direct radiation. The DH systems considered in the study show a similar performance but with some differences: other parameters such as slope, azimuth and operating temperatures could be the causes of these variations

Planning and operation of two small SDH plants as test site: Comparison between flat plate and vacuum collectors

A small solar district heating plant has been built to provide heat to an existing district heating system supplied by natural gas CHP units. This test site, located at 1,600 m a.s.l., allows comparing the performances of evacuated solar collectors (ETC) with flat plate double glazed ones (FPC) in a mountain environment. The preliminary results of the first months of operation show a better performance of ETC than FPC. The daily heat production shows a good correlation with available radiation, with the FPC having a slightly larger variability. Moreover, while ETC system efficiency is comparable with the theoretic curve, the FPC system efficiency show lower values. The monitoring of the SDH is still ongoing, and some control logics of the system are being performed in order to optimize the heat production from FPC. The specific electricity consumption for pumping is in the range 5 – 20 kWhel/MWhth, in accordance with usual literature values. The specific pumping consumption decreases with increasing daily heat production, and no significant difference arises from the trends of the two systems

Operational performance of an Air Handling Unit: insights from a data analysis

Space heating and cooling is one of the most relevant causes of energy consumption in both residential and tertiary sector buildings. In particular, service buildings and offices are mostly served by all-air HVAC systems in which control logics are fundamental to guarantee reliability and performance. Building automation systems are therefore becoming more and more relevant as a support tool for reducing the energy consumption in these contexts. For this reason, the detailed analysis of operational data from real units can help in understanding the main variables that affect the performance and functioning of all-air systems. This paper presents some results from operation data analysis of an Air Handling Unit (AHU) serving a large university classroom. The main drivers of the energy consumption are highlighted, and the classroom occupancy is found to have a significant importance in the energy balance of the system. The availability of historical operation data allows performing a comparison between the actual operation of the AHU and the expected performance from nominal parameters. An example of fault detection is proposed, considering the operation analysis of the heat recovery unit over different years

Data analysis and modeling of users consumption profiles in District Heating Systems

District heating represents an optimal solution to increase the efficiency of the heating sector, which accounts for a large share of the total primary energy consumption in Europe. However, the heat load demand that is generated by served buildings has a strong influence on the efficient operation of the generation plants and the network. When Combined Heat and Power units are used, the heat load shape has a close connection also with the amount of electricity that can be produced, thus having a strong impact on the system’s economic sustainability. If renewable energy sources are integrated within the network, the variability of heat load can compromise their actual contribution to the overall production.Finally, the characterization of the heat load of many buildings through physical models is prevented by both the difficulty to gather the large quantity of necessary input data and the required computational time. This research work focuses on the analysis of the heat load consumption profiles of a large stock of buildings connected to a real district heating in Italy. A numerical model for predicting the heat load profile by using the smallest possible set of input variables is proposed. The model aims at finding numerical relationship among variables that are quick and simple to collect and significant for the definition of the heat load profile. Data gathered from 85 buildings are used as data-base for developing and testing the model. Two distinct preliminary procedures have independently assessed that time-of day and outdoor temperatures are by far the two most important variables in defining the heat load profile of each studied building. The role of time-of-day depends primarily on the control unit set-ups of each building; since many buildings must be analyzed and no information was available about these schedules, a profiling algorithm has been built and tuned to automatically identify the different operation modes set by each control unit. In the successive phase this identification is used as a basis for applying to each clusterization a linear regression model between the outdoor temperature and the heat load. The capability to distinguish among each different profile state allows the linear regression model to be much more effective when applied to each clusterization w.r.t. its application to the whole set of data. The outdoor temperature variable is also corrected by an effective time constant that is calculated to consider the effect of thermal inertia on the evolution of the heat load profile. The model has been tested over a one year period at both single building and simulated network levels. The final results confirm that the proposed model is capable of forecasting with sufficient accuracy the heat load profile of the simulated network of buildings both in terms of detailed heat load shape and yearly energy consumption. The last chapter reports three possible applications of the developed model. In the first one the impact of the implementation of an advanced control function within the district heating substations is simulated. The model proves to be reliable and suggests that the implemented function could guarantee significant energy savings by avoiding the supply of heat to buildings when excessive outdoor temperatures occurr. An optimization procedure is developed as a second application that is aimed at reducing the maximum peak load of the whole network by shifting the switchon/ switch-off schedules of the simulated buildings. This application proves that such advanced control could help reduce significantly the maximum power peaks. Finally, the proposed data analysis and modeling capability is used to simulate the effect of adoption of heat pumps as an alternative heat generation technology for substituting traditional natural gas boilers. It is shown that the heat pump solution is characterized by a primary energy consumption that is considerably lower than that of the natural gas boiler considered for comparison. The final results show that (1) the demand-side has a strong impact on the efficiency and sustainability rate of district heating systems; (2) an accurate numerical model can be used to describe and predict the heat load of a large building stock at detailed time-step, provided that sufficient data is collected for training the model; (3) the model can be successfully implemented in applications regarding demandside management, advanced control simulation and local-scale energy planning opportunities

Multicarrier energy systems: Optimization model based on real data and application to a case study

Multicarrier energy systems are increasingly used for a number of applications, among which the supply of electricity, heating, and cooling in buildings. The possibility of switching between different energy sources is a crucial advantage for the optimal fulfillment of the energy demand. The flexibility of these systems can benefit from the integration with smart grids, which have strong variations in time during their operation. The energy price is the parameter that is usually considered, but also the primary energy factor and the greenhouse gases emissions need to be accounted. This paper presents an application of an operational optimization method for a multicarrier energy system, based on real data-driven model and applied to different countries. The generation plant of a hospital is considered as case study, coping with multiple energy needs by relying on different conversion technologies. The optimal operation of the system shows a wide range of variability, depending on the chosen objective function, the hour of the day, the season, and the country. The results are affected mostly by the energy mix of the electricity supplied from the power grid, which has a direct influence on the primary energy consumption and the greenhouse gases emissions and an indirect influence on the electricity prices

Multicarrier energy systems: Optimization model based on real data and application to a case study

Multicarrier energy systems are increasingly used for a number of applications, among which the supply of electricity, heating, and cooling in buildings. The possibility of switching between different energy sources is a crucial advantage for the optimal fulfillment of the energy demand. The flexibility of these systems can benefit from the integration with smart grids, which have strong variations in time during their operation. The energy price is the parameter that is usually considered, but also the primary energy factor and the greenhouse gases emissions need to be accounted. This paper presents an application of an operational optimization method for a multicarrier energy system, based on real data-driven model and applied to different countries. The generation plant of a hospital is considered as case study, coping with multiple energy needs by relying on different conversion technologies. The optimal operation of the system shows a wide range of variability, depending on the chosen objective function, the hour of the day, the season, and the country. The results are affected mostly by the energy mix of the electricity supplied from the power grid, which has a direct influence on the primary energy consumption and the greenhouse gases emissions and an indirect influence on the electricity prices

Assessing Commuting Energy and Emissions Savings through Remote Working and Carpooling: Lessons from an Italian Region

Effective solutions are needed to decrease the greenhouse gases emissions of the transport sector, not only in terms of supply-side measures, but also including demand-side solutions. This paper focuses on the passenger demand related to daily commuting, either for work or study purposes. A bottom-up analysis is presented, which draws from detailed data for Lombardy, the most populous region in Northern Italy, to build an estimate of the annual energy consumption and emissions related to commuting. The potential of different measures to decrease emissions is evaluated, including the renovation of the vehicle stock, higher levels of remote working, and the deployment of carpooling schemes. The results show that the largest part of the current emissions from commuting is caused by car use, both due to its higher modal share and to the higher specific emissions, which are in turn also contributed by the low occupancy rates. The renewal of the current vehicle stock can lead to significant emission savings, thanks to both improved efficiency and higher shares of electrification. Remote working could also play a significant part, especially when it is applied to workers that face the longest commuting distances. Conversely, carpooling seems to be providing lower benefits, not so much because of lower effectiveness but more so because of constraints and barriers to its implementation