Energy Efficiency through Thermal Energy Storage - Evaluation of the Possibilities for the Swedish Building Stock, Phase 1

As a first step in assessing the potential of thermal energy storage in Swedish buildings, the current situation of the Swedish building stock and different storage methods are discussed in this paper. Overall, many buildings are from the 1960’s or earlier having a relatively high energy demand, creating opportunities for large energy savings. The major means of heating are electricity for detached houses and district heating for multi dwelling houses and premises. Cooling needs are relatively low but steadily increasing, emphasizing the need to consider energy storage for both heat and cold. The thermal mass of a building is important for passive storage of thermal energy but this has not been considered much when constructing buildings in Sweden. Instead, common ways of storing thermal energy in Swedish buildings today is in water storage tanks or in the ground using boreholes, while latent thermal energy storage is still very uncommon.

Environmental Objectives, Cost Efficiency, and Multivariate Stochastic Control

This paper is concerned with the cost efficiency in achieving the Swedish national air quality objectives under uncertainty. To realize an ecologically sustainable society, the parliament has approved a set of interim and long-term pollution reduction targets. However, there are considerable quantification uncertainties on the effectiveness of the proposed pollution reduction measures. In this paper, we develop a multivariate stochastic control framework to deal with the cost efficiency problem with multiple pollutants. Based on the cost and technological data collected by several national authorities, we explore the implications of alternative probabilistic constraints. It is found that a composite probabilistic constraint induces considerably lower abatement cost than separable probabilistic restrictions. The trend is reinforced by the presence of positive correlations between reductions in the multiple pollutants.

Policy instruments to improve energy efficiency in buildings

The newly adopted energy efficiency directive (2012/27/EU) highlights the importance of energy efficiency in reaching the Union’s 2020 targets. The directive commits member states to defining national energy efficiency targets (art. 3), achieving yearly energy savings of 1.5% of the annual energy sales through the energy efficiency obligation scheme (art. 7), and providing a long-term strategy for the building sector that aims at a 3% refurbishment rate for public buildings (art. 4+5). Buildings currently account for 40% of energy use in most countries, putting them among the largest end-use sectors. This report takes a closer look at the best practices for implementing increasing energy efficiency in different regions and countries in Europe. The final aim is to identify some policy tools to be suggested to the region of Dalarna (Dalarna having been chosen as the pilot county in Sweden) as a means of implementing energy efficiency in the building sector. The final objective is to give analysts and decision-makers a better analytical foundation to explore future policy development in the area of buildings to be proposed and tested at the regional level in Dalarna and later at the national level in Sweden.

AN APPROACH TO ILLUSTRATE STRATEGIES FOR IMPROVED ENERGY EFFICIENCY AT THE MUNICIPAL LEVEL

REESBE

Adaptive, Decentralized, And Real-Time Sampling Strategies For Resource Constrained Hydraulic And Hydrologic Sensor Networks

We discuss the development and performance of a low-power sensor node (hardware, software and algorithms) that autonomously controls the sampling interval of a suite of sensors based on local state estimates and future predictions of water flow. The problem is motivated by the need to accurately reconstruct abrupt state changes in urban watersheds and stormwater systems. Presently, the detection of these events is limited by the temporal resolution of sensor data. It is often infeasible, however, to increase measurement frequency due to energy and sampling constraints. This is particularly true for real-time water quality measurements, where sampling frequency is limited by reagent availability, sensor power consumption, and, in the case of automated samplers, the number of available sample containers. These constraints pose a significant barrier to the ubiquitous and cost effective instrumentation of large hydraulic and hydrologic systems. Each of our sensor nodes is equipped with a low-power microcontroller and a wireless module to take advantage of urban cellular coverage. The node persistently updates a local, embedded model of flow conditions while IP-connectivity permits each node to continually query public weather servers for hourly precipitation forecasts. The sampling frequency is then adjusted to increase the likelihood of capturing abrupt changes in a sensor signal, such as the rise in the hydrograph – an event that is often difficult to capture through traditional sampling techniques. Our architecture forms an embedded processing chain, leveraging local computational resources to assess uncertainty by analyzing data as it is collected. A network is presently being deployed in an urban watershed in Michigan and initial results indicate that the system accurately reconstructs signals of interest while significantly reducing energy consumption and the use of sampling resources. We also expand our analysis by discussing the role of this approach for the efficient real-time measurement of stormwater systems.