Data-Driven Approach to Forecast Heat Consumption of Buildings with High-Priority Weather Data

By increasing the penetration of renewable energies in district heating (DH), the intermittency of the supply-side increases for heating service providers. Therefore, forecasting the energy consumption of buildings is needed in order to hedge against renewable power intermittency. This paper investigates the application of data-driven approaches to forecast the heat consumption of buildings in the winter, using high-priority weather data. The residential buildings are connected to mixing loops of DH to supply space heating and hot water. The heating consumption of the building is calculated using sensor data, including inflow/outflow temperature and mass flow. Principal component analysis (PCA) is applied to determine the key weather data affecting heat energy consumption. Then, the study compares the competences of artificial neural networks (ANNs), linear regression models (LRM), and k-nearest neighbors (k-NN) in forecasting heat consumption, using informative data. Based on the PCA analysis, ambient temperature and solar irradiation are shown to be the highest priority weather data, contributing to 40.6% and 29.2% of heat energy forecasting, respectively. Furthermore, the ANN exhibits a forecasting accuracy of more than 50% higher than LRM and k-NN

Demand-Side Flexibility in Power Systems:A Survey of Residential, Industrial, Commercial, and Agricultural Sectors

In recent years, environmental concerns about climate change and global warming have encouraged countries to increase investment in renewable energies. As the penetration of renewable power goes up, the intermittency of the power system increases. To counterbalance the power fluctuations, demand-side flexibility is a workable solution. This paper reviews the flexibility potentials of demand sectors, including residential, industrial, commercial, and agricultural, to facilitate the integration of renewables into power systems. In the residential sector, home energy management systems and heat pumps exhibit great flexibility potential. The former can unlock the flexibility of household devices, e.g., wet appliances and lighting systems. The latter integrates the joint heat–power flexibility of heating systems into power grids. In the industrial sector, heavy industries, e.g., cement manufacturing plants, metal smelting, and oil refinery plants, are surveyed. It is discussed how energy-intensive plants can provide flexibility for energy systems. In the commercial sector, supermarket refrigerators, hotels/restaurants, and commercial parking lots of electric vehicles are pointed out. Large-scale parking lots of electric vehicles can be considered as great electrical storage not only to provide flexibility for the upstream network but also to supply the local commercial sector, e.g., shopping stores. In the agricultural sector, irrigation pumps, on-farm solar sites, and variable-frequency-drive water pumps are shown as flexible demands. The flexibility potentials of livestock farms are also surveyed

The Catalogue of Touch

he Catalogue of Touch offers a provocative and playful commentary on the commodifi -cation and commercialisation of touch and digital touch through a series of artistic responses. It imagines a menu of purchasable touch experiences facilitated by touch professionals – these respond to themes from my research on how people frame touch and digital touch in narratives of loneliness

Centralized model driven trace route mechanism for TCP/IP routers : Remote traceroute invocation using NETCONF API and YANG data model

During the recent years, utilizing programmable APIs and YANG data model for service configuration and monitoring of TCP/IP open network devices from a centralized network management system as an alternative to SNMP based network management solutions has gained popularity among service providers and network engineers. However, both SNMP and YANG lacks any data model for tracing the routes between different routers inside and outside the network that has not addressed. Having a centralized traceroute tool provides a central troubleshooting point in the network. And rather than having to individually connect to each router terminal, traceroute can be invoked remotely on different routers. And the responses can be collected on the network management system. The aim of this thesis is to develop a centralized traceroute tool called Trace that invokes traceroute CLI tool with a unique syntax from a centralized network management system on a TCP/IP router, traces the hops and BGP AS and measures RTT between a router and specific destination and returns the response back to the network management system. And evaluates the possibility of utilizing this traceroute tool along with YANG based network management solutions. This implementation has shown that YANG based data models enables a unique syntax on the network management system for invoking traceroute command on different TCP/IP devices. This unique syntax can be used to invoke the traceroute CLI command on the routers with the different operating systems. And the evaluation has shown that using NETCONF as an API between the network management system and the network devices, enables the Trace to be utilized in YANG and NETCONF based network management solutions