Montana Kaimin, October 23, 2008

Student newspaper of the University of Montana, Missoula.https://scholarworks.umt.edu/studentnewspaper/6217/thumbnail.jp

АНАЛІЗ МЕТОДИКИ РОЗРАХУНКУ НОРМАТИВНИХ ВИТРАТ ЕЛЕКТРИЧНОЇ ЕНЕРГІЇ НА ВИРОБНИЦТВО І ТРАНСПОРТУВАННЯ ТЕПЛА

Стаття присвячена питанням аналізу та удосконалення існуючої в Україні системи нормування питомих витрат електроенергії. Наведено результати аналізу діючої методики розрахунку та визначено її основні недоліки щодо встановлення норм питомої витрати електроенергії на котельних, які надають послуги з централізованого постачання гарячої води, опалення та вентиляції житлових і громадських будівель. Обґрунтована необхідність удосконалення методики з метою здійснення більш об’єктивного контролю енергетичної ефективності функціонування підприємств теплоенергетики

МЕТОДИЧНІ ОСНОВИ МОНІТОРИНГУ РЕЗУЛЬТАТІВ ВПРОВАДЖЕННЯ ЗАХОДІВ З ЕНЕРГОЗБЕРЕЖЕННЯ

Стаття присвячена питанням вдосконалення підходів до контролю ефективності енерговикористання. Розглянуто методи встановлення та контролю виконання цільових змінних для здійснення моніторингу результатів впровадження заходів з енергозбереження та створено універсальну процедуру контролю рівня енергоефективності, що ґрунтується на удосконаленні існуючих методів встановлення контрольних границь та процедур контролю

Digital Energy Platforms Considering Digital Privacy and Security by Design Principles

The power system and markets have become increasingly complex, along with efforts to digitalize the energy sector. Accessing flexibility services, in particular, through digital energy platforms, has enabled communication between multiple entities within the energy system and streamlined flexibility market operations. However, digitalizing these vast and complex systems introduces new cybersecurity and privacy concerns, which must be properly addressed during the design of the digital energy platform ecosystems. More specifically, both privacy and cybersecurity measures should be embedded into all phases of the platform design and operation, based on the privacy and security by design principles. In this study, these principles are used to propose a holistic but generic architecture for digital energy platforms that are able to facilitate multiple use cases for flexibility services in the energy sector. A hybrid framework using both DLT and non-DLT solutions ensures trust throughout the layers of the platform architecture. Furthermore, an evaluation of numerous energy flexibility service use cases operating at various stages of the energy value chain is shown and graded in terms of digital energy platform technical maturity, privacy, and cybersecurity issues

Selecting the model and influencing variables for DHW heat use prediction in hotels in Norway

Domestic hot water heat use prediction modelling is an important instrument for increasing energy efficiency in many buildings. This article addressed hourly domestic hot water heat use prediction, using a Norwegian hotel as a case study. Since the information available for buildings may vary, two widespread situations with different input variables were studied. For the first situation, the prediction is based only on data obtained from historical measured domestic hot water heat use. For the second situation, additional variables that affect domestic hot water heat use were applied. These variables were determined using the Wrapper approach. The Wrapper approach showed that factors related to the guests presence have the most significant influence on the domestic hot water heat use in the hotel. Nevertheless, daily data about the number of guests booked at the hotel did not appear to be informative enough for precise hourly modelling. Therefore, to improve the accuracy of the prediction, it was proposed to use an artificial variable. This artificial variable explained the hourly intensity of the guests domestic hot water use. In order to select the best model for the domestic hot water heat use prediction, ten advanced time series and machine learning techniques were tested based on the criteria of models adequacy. For both considered situations, the Prophet model showed the best results with R2 equal to 0.76 for the first situation, and 0.83 the second situation.publishedVersio

Splitting measurements of the total heat demand in a hotel into domestic hot water and space heating heat use

To achieve more efficient energy use in buildings, space heating (SH) and domestic hot water (DHW) heat use should be analysed separately. Unfortunately, in many buildings, the heat meters measure the total heat use only, typically not divided into SH and DHW. This article presented a method for splitting the total heat use into the SH and the DHW. The splitting follows the assumption that the outdoor temperature is the main parameter explaining the hourly SH heat use, while the hourly DHW heat use is not influenced by this parameter. In the article, the modelled SH heat use was extracted from the total heat use based on the energy signature curve and the singular spectrum analysis. Thereafter, from the residuals between the modelled SH heat use and the total heat use, the DHW heat use was identified. The application of the method for the hotel in Norway showed that restored values represented the trends of the measured SH and DHW heat use well. The coefficient of determination (R2) for the modelled SH heat use was 0.97, and 0.76 for DHW. The methodology is useful for obtaining valuable information for monitoring and improving the energy performance of SH and DHW systemspublishedVersio

Analysis of energy signatures and planning of heating and domestic hot water energy use in buildings in Norway

Widespread introduction of low energy buildings (LEBs), passive houses, and zero emission buildings (ZEBs) are national target in Norway. In order to achieve better energy performance in these types of buildings and successfully integrate them in energy system, reliable planning and prediction techniques for heat energy use are required. However, the issue of energy planning in LEBs currently remains challenging for district heating companies. This article proposed an improved methodology for planning and analysis of domestic hot water and heating energy use in LEBs based on energy signature method. The methodology was tested on a passive school in Oslo, Norway. In order to divide energy signature curve on temperature dependent and independent parts, it was proposed to use piecewise regression. Each of these parts were analyzed separately. The problem of dealing with outliers and selection of the factors that had impact of energy was considered. For temperature dependent part, the different methods of modelling were compared by statistical criteria. The investigation showed that linear multiple regression model resulted in better accuracy in the prediction than SVM, PLS, and LASSO models. In order to explain temperature independent part of energy signature the hourly profiles of energy use were developed.The authors gratefully acknowledge the support from the Research Council of Norway through the research projects: the Research Centre on Zero Emission Neighbourhoods in Smart Cities (FME ZEN) and Energy for domestic hot water in the Norwegian low emission society under VarmtVann2030 within EnergiX program.publishedVersio

DHW tank sizing considering dynamic energy prices

Due to the rapid development of the building stock in Norway, the energy use in this segment is drastically increasing. Therefore, improving the energy performance of buildings becoming an urgent problem. Among technical systems in buildings, domestic hot water (DHW) systems have still significant untapped potential for energy saving. Storage tanks enable us to change DHW demand in buildings in a more energy-efficient and cost-effective way. However, to achieve this effect, the proper sizing and operation of the storage tanks are required. The aim of this study was to define a method for the DHW tank size optimization considering dynamic electricity prices and to assess how different electricity pricing methods would influence the DHW tank size. A dynamic discretized model of the DHW tank was used as a DHW tank model. Dynamic optimization was implemented as the optimization method to find the optimal tank charging rate based on the different pricing methods. Two pricing methods were considered in this study: 1) the current method with the fixed grid fee and 2) the power extraction method with the pricing of the maximum power extraction. The results showed that the electricity pricing pattern had significant impact on the DHW charging heating rate. In the case of the extraction fee pricing method, the charging rate was more stable over the day than in the case of the fixed grid fee. This stable charging rate gave stable DHW tank temperature over the day and the highest decrease in the total cost. A general conclusion was that the extraction grid fee pricing method would promote for stable charging over the day.publishedVersio

Energy consumption for domestic hot water use in Norwegian hotels and nursing homes

Domestic Hot Water (DHW) production constitutes a significant proportion of the energy demand of modern buildings, and as the building envelope is improved the share increases. This article discusses the results from a measurement campaign in Norwegian hotels and nursing homes. The energy demand for DHW and distribution heat losses for 3 hotels and 3 nursing homes are shown. The results show that number of bedrooms is a better parameter for describing DHW consumption than sqm of heated floor area. There are large variations in the measured distribution losses, mainly due to malfunctioning of the hot water circulation system. For nursing homes, the measured energy consumption is significantly lower than the normative profiles, which can have large impact on the requirements for the design of the building heating system. For hotels, the measured energy consumption is in the range of the normative profiles.publishedVersio