A new error measure for forecasts of household-level, high resolution electrical energy consumption

As low carbon technologies become more pervasive, distribution network operators are looking to support the expected changes in the demands on the low voltage networks through the smarter control of storage devices. Accurate forecasts of demand at the single household-level, or of small aggregations of households, can improve the peak demand reduction brought about through such devices by helping to plan the appropriate charging and discharging cycles. However, before such methods can be developed, validation measures are required which can assess the accuracy and usefulness of forecasts of volatile and noisy household-level demand. In this paper we introduce a new forecast verification error measure that reduces the so called “double penalty” effect, incurred by forecasts whose features are displaced in space or time, compared to traditional point-wise metrics, such as Mean Absolute Error and p-norms in general. The measure that we propose is based on finding a restricted permutation of the original forecast that minimises the point wise error, according to a given metric. We illustrate the advantages of our error measure using half-hourly domestic household electrical energy usage data recorded by smart meters and discuss the effect of the permutation restriction.

Urban heat islands and electrical energy consumption

This study proposes the development of thermal and energy consumption maps to generate useful planning information. A residential neighbourhood in a medium-sized city was selected as the study area. In this area, 40 points were taken as urban reference points where air temperatures at the pedestrian level were collected. At the same time, rural temperatures made available by the city meteorological station were registered. Data of electrical energy consumption of the building units (houses and apartments) were collected through a household survey that was also designed to identify the users' income levels. Then, maps were developed so that the configuration of urban heat islands and electrical energy consumption could be visualised, compared and analysed. The results showed that the income level was the most important variable influencing electrical energy consumption. However, a strong relationship of the consumption with the thermal environment was also observed.

Analytical models for energy consumption in infrastructure WLAN STAs carrying TCP traffic

We develop analytical models for estimating the energy spent by stations (STAs) in infrastructure WLANs when performing TCP controlled file downloads. We focus on the energy spent in radio communication when the STAs are in the Continuously Active Mode (CAM), or in the static Power Save Mode (PSM). Our approach is to develop accurate models for obtaining the fraction of times the STA radios spend in idling, receiving and transmitting. We discuss two traffic models for each mode of operation: (i) each STA performs one large file download, and (ii) the STAs perform short file transfers. We evaluate the rate of STA energy expenditure with long file downloads, and show that static PSM is worse than just using CAM. For short file downloads we compute the number of file downloads that can be completed with given battery capacity, and show that PSM performs better than CAM for this case. We provide a validation of our analytical models using the NS-2 simulator.

Model and visualise the relationship between energy consumption and temperature distribution in cold rooms

In the area of food and pharmacy cold storage, temperature distribution is considered as a key factor. Inappropriate distribution of temperature during the cooling process in cold rooms will cause the deterioration of the quality of products and therefore shorten their life-span. In practice, in order to maintain the distribution of temperature at an appropriate level, large amount of electrical energy has to be consumed to cool down the volume of space, based on the reading of a single temperature sensor placed in every cold room. However, it is not clear and visible that what is the change of energy consumption and temperature distribution over time. It lacks of effective tools to visualise such a phenomenon. In this poster, we initially present a solution which combines a visualisation tool with a Computational Fluid Dynamics (CFD) model together to enable users to explore such phenomenon.

Electrical energy balance contest in Solar Decathlon Europe 2012

Solar Decathlon Europe (SDE) is an international multidisciplinary competition in which 20 universityteams build and operate energy-efficient solar-powered houses. The aim of SDE is not only scientificbut also educational and divulgative, making visitors to understand the problems presented by realengineering applications and architecture. From a research perspective, the energy data gathered dur-ing the competition constitutes a very promising information for the analysis and understanding of thephotovoltaic systems, grid structures, energy balances and energy efficiency of the set of houses. Thisarticle focuses on the electrical energy components of SDE competition, the energy performance of thehouses and the strategies and behaviors followed by the teams. The rules evaluate the houses? electricalenergy self-sufficiency by looking at the electricity autonomy in terms of aggregated electrical energybalance; the temporary generation-consumption profile pattern correlation; and the use of electricityper measurable area. Although the houses are evaluated under the same climatological and consump-tion conditions, production results are very different due to the specific engineering solutions (differentelectrical topologies, presence or absence of batteries, diverse photovoltaic module solutions, etc.)

Energy efficient measures to reduce electrical energy use in commercial buildings in New York City

GEA Consulting Engineers, acting as the design engineers, was hired by the owner, East Village 207 Residential LLC2 for energy modeling for compliance with LEED NC V3 -- This report details the results of the energy simulation done with the 100% construction documents -- This report only refers to entities within the LEED3 project boundary -- The project consists of a new eight-story high-end residential condominium building with 81 units, as shown in illustration 1, and approximately 117,905 GSF, equivalent to 10,953.73 m2, is located at 211 E 13th Street in New York, NY -- The residential portion of the building will function 24-7 -- The design goal is to utilize energy efficient measures to reduce electrical energy use and aims to achieve LEED certification -- LEED EA Credit 14 requires a building to demonstrate a percentage improvement in the proposed building performance compared with the baseline building -- The Credit rewards 1 point for achieving 12% reduction in energy costs -- Additionally, the Credit rewards another point for each subsequent reduction of 2% in the building’s energy cost

Energy consumption and energy efficiency in olive oil mills: case studies in Portugal and Spain in the frame of TESLA project

TESLA project (Transfering Energy Save Laid on Agroindustry) financed by the European Commission, had the main goals of evaluating the energy consumption and to identify the best available practices to improve energy efficiency in key agro-food sectors, such as the olive oil mills. A general analysis of energy consumptions allowed identifying the partition between electrical and thermal energy (approximately 50%) and the production processes responsible for the higher energy consumptions, as being the in the mill and paste preparation and the phases separation. Some measures for reducing energy waste and for improving energy efficiency were identified and the impact was evaluated by using the TESLA tool developed by Circe and available at the TESLA website.

Increasing underwater vehicle autonomy by reducing energy consumption

In this paper, we concern ourselves with finding a control strategy that minimizes energy consumption along a trajectory connecting two given configurations. We develop an algorithm, based on our previous work with the time optimal problem, which provides implementable control strategies that are energy efficient. We find an interesting correlation between the duration of these trajectories and the optimal duration. We present the algorithm, control strategy and experimental results from our test-bed vehicle.

Implementable efficient time and energy consumption trajectories design for an autonomous underwater vehicle

In this paper we consider the implementation of time and energy efficient trajectories onto a test-bed autonomous underwater vehicle. The trajectories are losely connected to the results of the application of the maximum principle to the controlled mechanical system. We use a numerical algorithm to compute efficient trajectories designed using geometric control theory to optimize a given cost function. Experimental results are shown for the time minimization problem.

Vertical vegetation design decisions and their impact on energy consumption in subtropical cities

Vertical vegetation is vegetation growing on, or adjacent to, the unused sunlit exterior surfaces of buildings in cities. Vertical vegetation can improve the energy efficiency of the building on which it is installed mainly by insulating, shading and transpiring moisture from foliage and substrate. Several design parameters may affect the extent of the vertical vegetation's improvement of energy performance. Examples are choice of vegetation, growing medium geometry, north/south aspect and others. The purpose of this study is to quantitatively map out the contribution of several parameters to energy savings in a subtropical setting. The method is thermal simulation based on EnergyPlus configured to reflect the special characteristics of vertical vegetation. Thermal simulation results show that yearly cooling energy savings can reach 25% with realistic design choices in subtropical environments. Heating energy savings are negligible. The most important parameter is the aspect of walls covered by vegetation. Vertical vegetation covering walls facing north (south for the northern hemisphere) will result in the highest energy savings. In making plant selections, the most significant parameter is Leaf Area Index (LAI). Plants with larger LAI, preferably LAI>4, contribute to greater savings whereas vertical vegetation with LAI<2 can actually consume energy. The choice of growing media and its thickness influence both heating and cooling energy consumption. Change of growing medium thickness from 6cm to 8cm causes dramatic increase in energy savings from 2% to 18%. For cooling, it is best to use a growing material with high water retention, due to the importance of evapotranspiration for cooling. Similarly, for increased savings in cooling energy, sufficient irrigation is required. Insufficient irrigation results in the vertical vegetation requiring more energy to cool the building. To conclude, the choice of design parameters for vertical vegetation is crucial in making sure that it contributes to energy savings rather than energy consumption. Optimal design decisions can create a dramatic sustainability enhancement for the built environment in subtropical climates.

Optimisation of indoor environmental quality and energy consumption within office buildings

This research investigated airborne particle characteristics and their dynamics inside and around the envelope of mechanically ventilated office buildings, together with building thermal conditions and energy consumption. Based on these, a comprehensive model was developed to facilitate the optimisation of building heating, ventilation and air conditioning systems, in order to protect the health of their occupants and minimise the energy requirements of these buildings.

The psychological and economic factors that influence energy consumption habits of low-income earners

Social marketers and governments have often targeted hard to reach or vulnerable groups (Gordon et al., 2006) such as young adults and low income earners. Past research has shown that low-income earners are often at risk of poor health outcomes and diminished lifestyle (Hampson et al., 2009; Scott et al., 2012). Young adults (aged 18 to 35) are in a transition phase of their life where lifestyle preferences are still being formed and are thus a useful target for long-term sustainable change. An area of focus for all levels of government is the use of energy with an aim to reduce consumption. There is little research to date that combines both of these groups and in particular in the context of household energy usage. Research into financially disadvantaged consumers is challenging the notion that that low income consumer purchasing and usage of products and services is based upon economic status (Sharma et al., 2012). Prior research shows higher income earners view items such as televisions and computers as necessities rather than non-essential (Karlsson et al., 2004). Consistent with this is growing evidence that low income earners purchase non-essential, energy intensive electronic appliances such as multiple big screen TV sets and additional refrigerators. With this in mind, there is a need for knowledge about how psychological and economic factors influence the energy consumption habits (e.g. appliances on standby power, leaving appliances turned on, running multiple devices at one time) of low income earners. Thus, our study sought to address the research question of: What are the factors that influence young adult low-income earners energy habits?

Co-optimisation of indoor environmental quality and energy consumption within urban office buildings

This study aimed to develop a multi-component model that can be used to maximise indoor environmental quality inside mechanically ventilated office buildings, while minimising energy usage. The integrated model, which was developed and validated from fieldwork data, was employed to assess the potential improvement of indoor air quality and energy saving under different ventilation conditions in typical air-conditioned office buildings in the subtropical city of Brisbane, Australia. When operating the ventilation system under predicted optimal conditions of indoor environmental quality and energy conservation and using outdoor air filtration, average indoor particle number (PN) concentration decreased by as much as 77%, while indoor CO2 concentration and energy consumption were not significantly different compared to the normal summer time operating conditions. Benefits of operating the system with this algorithm were most pronounced during the Brisbane’s mild winter. In terms of indoor air quality, average indoor PN and CO2 concentrations decreased by 48% and 24%, respectively, while potential energy savings due to free cooling went as high as 108% of the normal winter time operating conditions. The application of such a model to the operation of ventilation systems can help to significantly improve indoor air quality and energy conservation in air-conditioned office buildings.