Analysis and modeling of active occupancy of the residential sector in Spain: an indicator of residential electricity consumption

The growing energy consumption in the residential sector represents about 30% of global demand. This calls for Demand Side Management solutions propelling change in behaviors of end consumers, with the aim to reduce overall consumption as well as shift it to periods in which demand is lower and where the cost of generating energy is lower. Demand Side Management solutions require detailed knowledge about the patterns of energy consumption. The profile of electricity demand in the residential sector is highly correlated with the time of active occupancy of the dwellings; therefore in this study the occupancy patterns in Spanish properties was determined using the 2009–2010 Time Use Survey (TUS), conducted by the National Statistical Institute of Spain. The survey identifies three peaks in active occupancy, which coincide with morning, noon and evening. This information has been used to input into a stochastic model which generates active occupancy profiles of dwellings, with the aim to simulate domestic electricity consumption. TUS data were also used to identify which appliance-related activities could be considered for Demand Side Management solutions during the three peaks of occupancy.

Electricity use in the commercial kitchen

Academic and industrial literature concerning the energy use of commercial kitchens is scarce. Electricity consumption data were collected from distribution board current transformers in a sample of fourteen UK public house-restaurants. This was set up to identify patterns of appliance use as well as to assess the total energy consumption of these establishments. The electricity consumption in the selected commercial kitchens was significantly higher than current literature estimates. On average, 63% of the premises’ electricity consumption was attributed to the catering activity. Key appliances that contributed to the samples average daily electricity consumption of the kitchen were identified as refrigeration (70 kWh, 41%), fryers (11 kWh, 13%), combination ovens (35 kWh, 12%), bain maries (27 kWh, 9%) and grills (37 kWh, 12%). Behavioural factors and poor maintenance were identified as major contributors to excessive electricity usage with potential savings of 70% and 45% respectively. Initiatives are required to influence operator behaviour, such as the expansion of mandatory energy labelling, improved feedback information and the use of behaviour change campaigns. Strict maintenance protocols and more appropriate sizing of refrigeration would be of great benefit to energy reduction.

Controlling market power of vertically integrated firms in electricity networks: demand response of aggregator agents

This article reports the results of an experiment that examined how demand aggregators can discipline vertically-integrated firms - generator and distributor-retailer holdings-, which have a high share in wholesale electricity market with uniform price double auction (UPDA). We initially develop a treatment where holding members redistribute the profit based on the imposition of supra-competitive prices, in equal proportions (50%-50%). Subsequently, we introduce a vertical disintegration (unbundling) treatment with holding-s information sharing, where profits are distributed according to market outcomes. Finally, a third treatment is performed to introduce two active demand aggregators, with flexible interruptible loads in real time. We found that the introduction of responsive demand aggregators neutralizes the power market and increases market efficiency, even beyond what is achieved through vertical disintegration.

CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.

A review of time use models of residential electricity demand

Residential electricity demand in most European countries accounts for a major proportion of overall electricity consumption. The timing of residential electricity demand has significant impacts on carbon emissions and system costs. This paper reviews the data and methods used in time use studies in the context of residential electricity demand modelling. It highlights key issues which are likely to become more topical for research on the timing of electricity demand following the roll-out of smart metres.

Activities related with electricity consumption in the Spanish residential sector: variations between days of the week, Autonomous Communities and size of towns

Nowadays the electricity consumption in the residential sector attracts policy and research efforts, in order to propose saving strategies and to attain a better balance between production and consumption, by integrating renewable energy production and proposing suitable demand side management methods. To achieve these objectives it is essential to have real information about household electricity demand profiles in dwellings, highly correlated, among other aspects, with the active occupancy of the homes and to the personal activities carried out in homes by their occupants. Due to the limited information related to these aspects, in this paper, behavioral factors of the Spanish household residents, related to the electricity consumption, have been determined and analyzed, based on data from the Spanish Time Use Surveys, differentiating among the Autonomous Communities and the size of municipalities, or the type of days, weekdays or weekends. Activities involving a larger number of houses are those related to Personal Care, Food Preparation and Washing Dishes. The activity of greater realization at homes is Watching TV, which together with Using PC, results in a high energy demand in an aggregate level. Results obtained enable identify prospective targets for load control and for efficiency energy reduction recommendations to residential consumers.

Mathematical solutions for electricity networks in a low carbon future

Smart meters are becoming more ubiquitous as governments aim to reduce the risks to the energy supply as the world moves toward a low carbon economy. The data they provide could create a wealth of information to better understand customer behaviour. However at the household, and even the low voltage (LV) substation level, energy demand is extremely volatile, irregular and noisy compared to the demand at the high voltage (HV) substation level. Novel analytical methods will be required in order to optimise the use of household level data. In this paper we briefly outline some mathematical techniques which will play a key role in better understanding the customer's behaviour and create solutions for supporting the network at the LV substation level.

Multinational subsidiary sales and performance in South East Asia

We extend the theory of the multinational enterprise (MNE) by exploring the concept of subsidiary-specific advantages (SSAs) as a driver for subsidiary performance. We investigate the relationship of host country-specific advantages (host CSAs) in the form of market attractiveness, SSAs and subsidiary sales as they affect subsidiary performance. From an original primary dataset of 101 British multinational (MNE) subsidiaries in six South East Asian countries, our analysis reveals three significant findings. First, host market attractiveness has a statistically positive impact on the performance of subsidiaries. Second, the three traditional SSAs of general management, marketing capabilities and invested capital enhance subsidiary performance. Third, we examine geographic direction and types of customers for subsidiary sales by following international accounting standards. We find that these subsidiaries generate on average 95 percent of total sales from the Asia Pacific region and 91 percent of total sales from external customers. Our findings have important research and managerial implications.

Identifying trends in domestic electricity consumption in Botswana

Data on electricity consumption patterns relating to different end uses in domestic houses in Botswana is virtually non-existent, despite the fact that the total electricity consumption patterns are available. This can be attributed to the lack of measured and quantified data and in other instances the lack of modern technology to perform such investigations. This paper presents findings from initial studies that are envisaged to bridge the gap. Electricity consumption patterns of 73 domestic households across three cities have been studied. This was carried out through a questionnaire survey, calculated national metering data and electricity measurements. All together nine appliance groups were identified. The results showed the mean electricity consumption for the households considering the calculated consumption from bills and the survey to be t = 4.23; p < 0.000067, two-tailed. The findings of this paper focus on a relatively small sample size (73). It would therefore not be wise to draw sweeping conclusions from the analysis or to make statements that would be aimed at influencing policies. However, the results presented forms a formidable base for further research, which is currently on going.

Using standby generators in support of an electricity network: logistics and experience

Electricity load shifting is becoming a big topic in the world of ‘green’ retail. Marks & Spencer (M&S) aim to become the world’s most sustainable retailer (1) and part of that commitment means contributing to the future electricity network. While intelligent operation of fridges and Heating, Ventilation and Air Conditioning (HVAC) systems are a wide area of research, standby generators should be considered too, as they are the most widely adopted form of distributed generation. In this paper, the experience of using standby generators in Northern Ireland to support the grid is shared and the logistics of future projects are discussed. Interactions with maintenance schedules, electricity costs, grid code, staffing and store opening times are discussed as well as the financial implications associated with running generators for grid support.

Privatisation and cross-border electricity trade: from internal market to European Supergrid?

he perspective European Supergrid would consist of an integrated power system network, where electricity demands from one country could be met by generation from another country. This paper makes use of a bi-linear fixed-effects model to analyse the determinants for trading electricity across borders among 34 countries connected by the European Supergrid. The key question that this paper aims to address is the extent to which the privatisation of European electricity markets has brought about higher cross-border trade of electricity. The analysis makes use of distance, price ratios, gate closure times, size of peaks and aggregate demand as standard determinants. Controlling for other standard determinants, it is concluded that privatisation in most cases led to higher power exchange and that the benefits are more significant where privatisation measures have been in place for a longer period.

Investigating preferences for dynamic electricity tariffs: the effect of environmental and system benefit disclosure

Dynamic electricity pricing can produce efficiency gains in the electricity sector and help achieve energy policy goals such as increasing electric system reliability and supporting renewable energy deployment. Retail electric companies can offer dynamic pricing to residential electricity customers via smart meter-enabled tariffs that proxy the cost to procure electricity on the wholesale market. Current investments in the smart metering necessary to implement dynamic tariffs show policy makers’ resolve for enabling responsive demand and realizing its benefits. However, despite these benefits and the potential bill savings these tariffs can offer, adoption among residential customers remains at low levels. Using a choice experiment approach, this paper seeks to determine whether disclosing the environmental and system benefits of dynamic tariffs to residential customers can increase adoption. Although sampling and design issues preclude wide generalization, we found that our environmentally conscious respondents reduced their required discount to switch to dynamic tariffs around 10% in response to higher awareness of environmental and system benefits. The perception that shifting usage is easy to do also had a significant impact, indicating the potential importance of enabling technology. Perhaps the targeted communication strategy employed by this study is one way to increase adoption and achieve policy goals.

Trends in domestic electricity consumption in Botswana

Data on electricity consumption patterns relating to different end uses in domestic houses in Botswana is virtually non-existent, despite the fact that the total electricity consumption patterns are available. This can be attributed to the lack of measured and quantified data and in other instances the lack of modern technology to perform such investigations. This paper presents findings from initial studies that are envisaged to bridge the gap. Electricity consumption patterns of 275 domestic households in Gaborone (the capital city of Botswana) have been studied. This was carried out through a questionnaire survey and electricity measurements. Households were categorized based on the number of people occupying the house. From the study, it was evident that the number of people influences the amount of energy a household use although this cannot be treated as an independent factor when assessing energy use. The study also indicated that heating, cooling and domestic hot water (DHW) account for over 30% of energy used in the home. This is worth considering in energy consumption reduction measures. Due to a small sample size, it would not be wise to draw sweeping conclusions from the analysis of this paper or to make statements that would be aimed at influencing policies. However, the results presented forms a formidable base for further research, which is currently on going.

Identifying behavioural predictors of small power electricity consumption in office buildings

It is widely accepted that there is a gap between design energy and real world operational energy consumption. The behaviour of occupants is often cited as an important factor influencing building energy performance. However, its consideration, both during design and operation, is overly simplistic, often assuming a direct link between attitudes and behaviour. Alternative models of decision making from psychology highlight a range of additional influential factors and emphasise that occupants do not always act in a rational manner. Developing a better understanding of occupant decision making could help inform office energy conservation campaigns as well as models of behaviour employed during the design process. This paper assesses the contribution of various behavioural constructs on small power consumption in offices. The method is based upon the Theory of Planned Behaviour (TPB) which assumes that intention is driven by three factors: attitude, subjective norms, and perceived behavioural control, but we also consider a fourth construct: habit measured through the Self- Report Habit Index (SRHI). A questionnaire was issued to 81 participants in two UK offices. Questionnaire results for each behavioural construct were correlated against each participant’s individual workstation electricity consumption. The intentional processes proposed by TPB could not account for the observed differences in occupants’ interactions with small power appliances. Instead, occupants were interacting with small power “automatically”, with habit accounting for 11% of the variation in workstation energy consumption. The implications for occupant behaviour models and employee engagement campaigns are discussed.