Techno-economic analysis of residential thermal flexibility for demand side management

The continuing rise in solar and wind production leads to an increasing demand of flexibility to stabilize the electricity grid. Furthermore, we can assume a gradual but intensive rise in the use of electrical heatpumps for household spatial heating, for different reasons. Therefore, this paper investigates the feasibility and viability of entering the flexibility market by aggregating residential thermal loads. For this research, a dataset of 200 dwellings in the Netherlands, equipped with a heatpump and smart metering infrastructure, is analysed. By means of a greybox modeling approach, a thermal model and control framework have been set up for every house, in order to identify the load shift potential and the accompanying cost of providing flexibility for the houses. We find that thermal flexibility is asymmetric: downwards flexibility is, apart from much more dependent on outdoor temperature than upwards flexibility, strictly lower than upwards flexibility. The cost for downwards flexibility is strictly negative in terms of the prosumer. Concerning upwards flexibility, the cost is most of the time positive. Moreover, it can be concluded that there is a potentially viable business case for the flexibility aggregator

Impacts of household sources on air pollution at village and regional scales in India

Approximately 3 billion people worldwide cook with solid fuels, such as wood, charcoal, and agricultural residues. These fuels, also used for residential heating, are often combusted in inefficient devices, producing carbonaceous emissions. Between 2.6 and 3.8 million premature deaths occur as a result of exposure to fine particulate matter from the resulting household air pollution (Health Effects Institute, 2018a; World Health Organization, 2018). Household air pollution also contributes to ambient air pollution; the magnitude of this contribution is uncertain. Here, we simulate the distribution of the two major health-damaging outdoor air pollutants (PM2:5 and O3) using state-of-thescience emissions databases and atmospheric chemical transport models to estimate the impact of household combustion on ambient air quality in India. The present study focuses on New Delhi and the SOMAARTH Demographic, Development, and Environmental Surveillance Site (DDESS) in the Palwal District of Haryana, located about 80 km south of New Delhi. The DDESS covers an approximate population of 200 000 within 52 villages. The emissions inventory used in the present study was prepared based on a national inventory in India (Sharma et al., 2015, 2016), an updated residential sector inventory prepared at the University of Illinois, updated cookstove emissions factors from Fleming et al. (2018b), and PM2:5 speciation from cooking fires from Jayarathne et al. (2018). Simulation of regional air quality was carried out using the US Environmental Protection Agency Community Multiscale Air Quality modeling system (CMAQ) in conjunction with the Weather Research and Forecasting modeling system (WRF) to simulate the meteorological inputs for CMAQ, and the global chemical transport model GEOS-Chem to generate concentrations on the boundary of the computational domain. Comparisons between observed and simulated O3 and PM2:5 levels are carried out to assess overall airborne levels and to estimate the contribution of household cooking emissions

Grey-box Modelling of a Household Refrigeration Unit Using Time Series Data in Application to Demand Side Management

This paper describes the application of stochastic grey-box modeling to identify electrical power consumption-to-temperature models of a domestic freezer using experimental measurements. The models are formulated using stochastic differential equations (SDEs), estimated by maximum likelihood estimation (MLE), validated through the model residuals analysis and cross-validated to detect model over-fitting. A nonlinear model based on the reversed Carnot cycle is also presented and included in the modeling performance analysis. As an application of the models, we apply model predictive control (MPC) to shift the electricity consumption of a freezer in demand response experiments, thereby addressing the model selection problem also from the application point of view and showing in an experimental context the ability of MPC to exploit the freezer as a demand side resource (DSR).Comment: Submitted to Sustainable Energy Grids and Networks (SEGAN). Accepted for publicatio

Identifying Peer Groups in a Multifamily Residential Building for Eco-Feedback Design

Most residential energy saving strategies require occupants’ participation because they control building and mechanical systems and pay their utility in general. One effective way to increase their participation is to motivate them to change their behaviors by providing relevant information and benefits in their interests. This paper presents baseline energy consumption characteristics in a multifamily housing for eco-feedback design. Although previous studies have proven the energy savings of eco-feedback and smart technology, the results were often mixed or weak because the building, mechanical, geographical, and demographical characteristics were different among houses to make a solid comparison, and the collection of detailed information in residential houses was not available in most cases. Multifamily housing provides a unique opportunity to observe the direct impact of interventions on energy consumption and related behaviors by excluding the effect of building and mechanical characteristics. This paper introduces a non-intrusive experimental setup by using off-the-shelf products to monitor detailed behavior-related information. In addition, we present various classification rules to formalize energy-related behavior such as thermostat-related actions, occupancy detection, and energy normalization. Finally, the use of the collected information is presented, which enables the design of personalized eco-feedback

Performance analysis of air source heat pumps using detailed simulations and comparison to field trial data

The take-up of heat pump technologies in the UK domestic sector has lagged far behind other countries in Europe and North America due primarily to the ready availability of cheap natural gas; this has led to the predominance of gas central heating systems in UK housing. However, with recent gas price volatility along with the depletion of the UK's natural gas reserves interest in heat pump technology, particularly Air source heat pumps (ASHPs) is growing as they have the potential to be a direct, low-carbon replacement for existing gas boiler systems. However, to-date there have been few detailed, simulation-based performance studies of ASHP systems. In this paper a robust, dynamic simulation model of an ASHP device is described. The ASHP model has been integrated into a whole-building model and used to analyse the performance of a retro-fit domestic ASHP heating system. The simulation results were then compared to field trial data

Thermal Analysis of a Hermetic Reciprocating Compressor Using Numerical Methods

Comprehensive knowledge about the heat transfer mechanisms and the temperature field inside hermetic compressors is very important for the thermal management and thus their performance. A numerical model to predict the temperature field in a hermetic reciprocating compressor for household refrigeration appliances is presented in this work. The model combines a high resolution three-dimensional heat conduction formulation of the compressor’s solid parts, a three-dimensional computational fluid dynamics (CFD) approach for the gas line domain and lumped formulations of the shell gas and the lubrication oil. Heat transfer coefficients are determined by applying CFD to the gas line side and correlations from the literature on the shell gas and oil side, respectively. The valve in the gas line simulation is modelled as a parallel moving flat plate. By means of an iterative loop the temperature field of the solid parts acts as boundary condition for the CFD calculation of the gas line which returns a cycle averaged quantity of heat to the solid parts. Using an iteration method which is based on the temperature deviation between two iteration steps, the total number of iterations and consequently the computational time can be reduced. The loop is continued until a steady-state temperature field is obtained. Calculated temperatures of the solid parts are verified against temperature measurements of a calorimeter test bench. The numerical results show reasonable agreement with the measured data