Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

Simulating the impact on health of internalising the cost of carbon in food prices combined with a tax on sugar-sweetened beverages

Rising greenhouse gas emissions (GHGEs) have implications for health and up to 30 % of emissions globally are thought to arise from agriculture. Synergies exist between diets low in GHGEs and health however some foods have the opposite relationship, such as sugar production being a relatively low source of GHGEs. In order to address this and to further characterise a healthy sustainable diet, we model the effect on UK non-communicable disease mortality and GHGEs of internalising the social cost of carbon into the price of food alongside a 20 % tax on sugar sweetened beverages (SSBs). Developing previously published work, we simulate four tax scenarios: (A) a GHGEs tax of £2.86/tonne of CO2 equivalents (tCO2e)/100 g product on all products with emissions greater than the mean across all food groups (0.36 kgCO2e/100 g); (B) scenario A but with subsidies on foods with emissions lower than 0.36 kgCO2e/100 g such that the effect is revenue neutral; (C) scenario A but with a 20 % sales tax on SSBs; (D) scenario B but with a 20 % sales tax on SSBs. An almost ideal demand system is used to estimate price elasticities and a comparative risk assessment model is used to estimate changes to non-communicable disease mortality. We estimate that scenario A would lead to 300 deaths delayed or averted, 18,900 ktCO2e fewer GHGEs, and £3.0 billion tax revenue; scenario B, 90 deaths delayed or averted and 17,100 ktCO2e fewer GHGEs; scenario C, 1,200 deaths delayed or averted, 18,500 ktCO2e fewer GHGEs, and £3.4 billion revenue; and scenario D, 2,000 deaths delayed or averted and 16,500 ktCO2e fewer GHGEs. Deaths averted are mainly due to increased fibre and reduced fat consumption; a SSB tax reduces SSB and sugar consumption. Incorporating the social cost of carbon into the price of food has the potential to improve health, reduce GHGEs, and raise revenue. The simple addition of a tax on SSBs can mitigate negative health consequences arising from sugar being low in GHGEs. Further conflicts remain, including increased consumption of unhealthy foods such as cakes and nutrients such as salt.

Simultaneous activities in the household and residential electricity demand in Spain

Recent research and policy studies on the low-carbon future highlight the importance of flexible electricity demand. This might be problematic particularly for residential electricity demand, which is related to simultaneous consumers’ practices in the household. This paper analyses issues of simultaneity in residential electricity demand in Spain. It makes use of the 2011 Spanish Time Use Survey data with comparisons from the previous Spanish Time Use Survey and the Harmonised European Time Use Surveys. Findings show that media activities are associated the highest levels of continuity and simultaneity, particularly in the early and late parts of the evening during weekdays.

Cross layer based protocols for energy aware and critical data delivery related applications using wireless sensor networks

Wireless Sensor Networks (WSNs) have been an exciting topic in recent years. The services offered by a WSN can be classified into three major categories: monitoring, alerting, and information on demand. WSNs have been used for a variety of applications related to the environment (agriculture, water and forest fire detection), the military, buildings, health (elderly people and home monitoring), disaster relief, and area or industrial monitoring. In most WSNs tasks like processing the sensed data, making decisions and generating emergency messages are carried out by a remote server, hence the need for efficient means of transferring data across the network. Because of the range of applications and types of WSN there is a need for different kinds of MAC and routing protocols in order to guarantee delivery of data from the source nodes to the server (or sink). In order to minimize energy consumption and increase performance in areas such as reliability of data delivery, extensive research has been conducted and documented in the literature on designing energy efficient protocols for each individual layer. The most common way to conserve energy in WSNs involves using the MAC layer to put the transceiver and the processor of the sensor node into a low power, sleep state when they are not being used. Hence the energy wasted due to collisions, overhearing and idle listening is reduced. As a result of this strategy for saving energy, the routing protocols need new solutions that take into account the sleep state of some nodes, and which also enable the lifetime of the entire network to be increased by distributing energy usage between nodes over time. This could mean that a combined MAC and routing protocol could significantly improve WSNs because the interaction between the MAC and network layers lets nodes be active at the same time in order to deal with data transmission. In the research presented in this thesis, a cross-layer protocol based on MAC and routing protocols was designed in order to improve the capability of WSNs for a range of different applications. Simulation results, based on a range of realistic scenarios, show that these new protocols improve WSNs by reducing their energy consumption as well as enabling them to support mobile nodes, where necessary. A number of conference and journal papers have been published to disseminate these results for a range of applications.

Apple pollination: demand depends on variety and supply depends on pollinator identity

Insect pollination underpins apple production but the extent to which different pollinator guilds supply this service, particularly across different apple varieties, is unknown. Such information is essential if appropriate orchard management practices are to be targeted and proportional to the potential benefits pollinator species may provide. Here we use a novel combination of pollinator effectiveness assays (floral visit effectiveness), orchard field surveys (flower visitation rate) and pollinator dependence manipulations (pollinator exclusion experiments) to quantify the supply of pollination services provided by four different pollinator guilds to the production of four commercial varieties of apple. We show that not all pollinators are equally effective at pollinating apples, with hoverflies being less effective than solitary bees and bumblebees, and the relative abundance of different pollinator guilds visiting apple flowers of different varieties varies significantly. Based on this, the taxa specific economic benefits to UK apple production have been established. The contribution of insect pollinators to the economic output in all varieties was estimated to be £92.1M across the UK, with contributions varying widely across taxa: solitary bees (£51.4M), honeybees (£21.4M), bumblebees (£18.6M) and hoverflies (£0.7M). This research highlights the differences in the economic benefits of four insect pollinator guilds to four major apple varieties in the UK. This information is essential to underpin appropriate investment in pollination services management and provides a model that can be used in other entomolophilous crops to improve our understanding of crop pollination ecology.

Future change of climate in South America in the late twenty-first century: intercomparison of scenarios from three regional climate models

Regional climate change projections for the last half of the twenty-first century have been produced for South America, as part of the CREAS (Cenarios REgionalizados de Clima Futuro da America do Sul) regional project. Three regional climate models RCMs (Eta CCS, RegCM3 and HadRM3P) were nested within the HadAM3P global model. The simulations cover a 30-year period representing present climate (1961-1990) and projections for the IPCC A2 high emission scenario for 2071-2100. The focus was on the changes in the mean circulation and surface variables, in particular, surface air temperature and precipitation. There is a consistent pattern of changes in circulation, rainfall and temperatures as depicted by the three models. The HadRM3P shows intensification and a more southward position of the subtropical Pacific high, while a pattern of intensification/weakening during summer/winter is projected by the Eta CCS/RegCM3. There is a tendency for a weakening of the subtropical westerly jet from the Eta CCS and HadRM3P, consistent with other studies. There are indications that regions such of Northeast Brazil and central-eastern and southern Amazonia may experience rainfall deficiency in the future, while the Northwest coast of Peru-Ecuador and northern Argentina may experience rainfall excesses in a warmer future, and these changes may vary with the seasons. The three models show warming in the A2 scenario stronger in the tropical region, especially in the 5A degrees N-15A degrees S band, both in summer and especially in winter, reaching up to 6-8A degrees C warmer than in the present. In southern South America, the warming in summer varies between 2 and 4A degrees C and in winter between 3 and 5A degrees C in the same region from the 3 models. These changes are consistent with changes in low level circulation from the models, and they are comparable with changes in rainfall and temperature extremes reported elsewhere. In summary, some aspects of projected future climate change are quite robust across this set of model runs for some regions, as the Northwest coast of Peru-Ecuador, northern Argentina, Eastern Amazonia and Northeast Brazil, whereas for other regions they are less robust as in Pantanal region of West Central and southeastern Brazil.

On the cutting stock problem under stochastic demand

This paper addresses the one-dimensional cutting stock problem when demand is a random variable. The problem is formulated as a two-stage stochastic nonlinear program with recourse. The first stage decision variables are the number of objects to be cut according to a cutting pattern. The second stage decision variables are the number of holding or backordering items due to the decisions made in the first stage. The problem`s objective is to minimize the total expected cost incurred in both stages, due to waste and holding or backordering penalties. A Simplex-based method with column generation is proposed for solving a linear relaxation of the resulting optimization problem. The proposed method is evaluated by using two well-known measures of uncertainty effects in stochastic programming: the value of stochastic solution-VSS-and the expected value of perfect information-EVPI. The optimal two-stage solution is shown to be more effective than the alternative wait-and-see and expected value approaches, even under small variations in the parameters of the problem.

Scheduling Grid Applications with Software Requirements

The aim of task scheduling is to minimize the makespan of applications, exploiting the best possible way to use shared resources. Applications have requirements which call for customized environments for their execution. One way to provide such environments is to use virtualization on demand. This paper presents two schedulers based on integer linear programming which schedule virtual machines (VMs) in grid resources and tasks on these VMs. The schedulers differ from previous work by the joint scheduling of tasks and VMs and by considering the impact of the available bandwidth on the quality of the schedule. Experiments show the efficacy of the schedulers in scenarios with different network configurations.

Short-time behaviour of demand and price viewed through an exactly solvable model for heterogeneous interacting market agents

We introduce a stochastic heterogeneous interacting-agent model for the short-time non-equilibrium evolution of excess demand and price in a stylized asset market. We consider a combination of social interaction within peer groups and individually heterogeneous fundamentalist trading decisions which take into account the market price and the perceived fundamental value of the asset. The resulting excess demand is coupled to the market price. Rigorous analysis reveals that this feedback may lead to price oscillations, a single bounce, or monotonic price behaviour. The model is a rare example of an analytically tractable interacting-agent model which allows LIS to deduce in detail the origin of these different collective patterns. For a natural choice of initial distribution, the results are independent of the graph structure that models the peer network of agents whose decisions influence each other. (C) 2009 Elsevier B.V. All rights reserved.

Applicatiion of Almost ideal demand system for a pharmaceutical

This thesis is an application of the Almost Ideal Demand System approach of Deaton and Muellbauer,1980, for a particular pharmaceutical, Citalopram, in which GORMAN´s (1971) multi-stage budgeting approach is applied basically since it is one of the most useful approach in estimating demand for differentiated products. Citalopram is an antidepressant drug that is used in the treatment of major depression. As for most other pharmaceuticals whose the patent has expired, there exist branded and generic versions of Citalopram. This paper is aimed to define its demand system with two stage models for the branded version and five generic versions, and to show whether generic versions are able to compete with the branded version. I calculated the own price elasticities, and it made me possible to compare and make a conclusion about the consumers’ choices over the brand and generic drugs. Even though the models need for being developed with some additional variables, estimation results of models and uncompensated price elasticities indicated that the branded version has still power in the market, and generics are able to compete with lower prices. One important point that has to be taken into consideration is that the Swedish pharmaceutical market faced a reform on October 1, 2002, that aims to make consumer better informed about the price and decrease the overall expenditures for pharmaceuticals. Since there were not significantly enough generic sales to take into calculation before the reform, my paper covers sales after the reform.

Modelling Recreation Demand Using Choice Experiments : Using Swedish Snowmobilers Demand for Groomed trails

This paper is concerned with the use of the choice experiment method for modeling the demand for snowmobiling . The Choice Experiment includes five attributes, standard, composition, length, price day card and experience along trail. The paper estimates the snowmobile owners’ preferences and the most preferred attributes, including their will-ingness to pay for a daytrip on groomed snowmobile trail. The data consists of the an-swers from 479 registered snowmobile owners, who answered two hypothetical choice questions each. Estimating using the multinominal logit model, it is found that snow-mobilers on average are willing to pay 22.5 SEK for one day of snowmobiling on a trail with quality described as skidded every 14th day. Furthermore, it is found that the WTP increases with the quality of trail grooming. The result of this paper can be used as a yardstick for snowmobile clubs wanting to develop their trail net worth, organizations and companies developing snowmobiling as a recreational activities and marketers in-terested in marketing snowmobiling as recreational activities.

Passive solar options for reducing heating demand and maintain indoor climate in a multifamily house in Sweden

This research was carried out by studying possible renovation of a two-storey detached multifamily building by using passive solar design options in a cold climate in Borlänge, Sweden where the heating Degree Days are 4451 (base 20°C). Borlänge`s housing company, Tunabyggen, plans to renovate the project house located inthe multicultural district, Jakobsgårdarna. The goal of the thesis was to suggest a redesign of the current building, decrease the heating energy use, by applying passive solar design and control strategies, in a most reasonable way. In addition ensure a better thermal comfort for the tenants in the dwellings. Literatures have been studied, from which can be inferred that passive design should be abasic design consideration for all housing constructions, because it has advantages to ensure thermal comfort, and reduce the energy use. In addition further savings can be achieved applying different types of control strategies, from which the house will be more personalized, and better adapted to the user’s needs.The proposed method is based on simulations by using TRNSYS software. First a proper building model was set up, which represents the current state of the project building. Then the thermal insulation and the windows were upgraded, based on today's building regulations. The developments of the passive solar options were accomplished in two steps. First of all the relevant basic passive design elements were considered, then those advantages were compared to the advantages of applying new conventional thermostat, and shading control strategies.The results show that there is significant potential with the different types of passive solar design; their usage depends primarily on the location of the site as well as the orientation of the project building. Applying the control strategies, such as thermostat, and shading control, along the thermal insulation upgrade, may lead to significant energy savings (around 40 %), by comparison to the reference building without any upgrade.

Price elasticity of demand for cigarettes : The Case of Sweden

Due to health problems and the negative externalities associated with cigarette consumption, many governments try to discourage cigarette consumption by increasing its price through taxation. However, cigarette, like the other addictive goods, is viewed as that it is not sensitive to demand rules and the market forces. This study analyses the effect of price increase on cigarette consumption. We used Swedish time series data from 1970 to 2010. Our results reveal that though cigarette is addictive substance its demand is sensitive to changes in the price. Estimates from this study indicate short-run price-elasticity of -0.29 and the long run price elasticity of -0.47.

En jämförelse av molnbaserade realtidsanalystjänster : Skillnader i användbarhet mellan multi-tenant och single-tenant arkitekturer

Internet of Things är ett samlingsbegrepp för den utveckling som innebär att olika typer av enheter kan förses med sensorer och datachip som är uppkopplade mot internet. En ökad mängd data innebär en ökad förfrågan på lösningar som kan lagra, spåra, analysera och bearbeta data. Ett sätt att möta denna förfrågan är att använda sig av molnbaserade realtidsanalystjänster. Multi-tenant och single-tenant är två typer av arkitekturer för molnbaserade realtidsanalystjänster som kan användas för att lösa problemen med hanteringen av de ökade datamängderna. Dessa arkitekturer skiljer sig åt när det gäller komplexitet i utvecklingen. I detta arbete representerar Azure Stream Analytics en multi-tenant arkitektur och HDInsight/Storm representerar en single-tenant arkitektur. För att kunna göra en jämförelse av molnbaserade realtidsanalystjänster med olika arkitekturer, har vi valt att använda oss av användbarhetskriterierna: effektivitet, ändamålsenlighet och användarnöjdhet. Vi kom fram till att vi ville ha svar på följande frågor relaterade till ovannämnda tre användbarhetskriterier: • Vilka likheter och skillnader kan vi se i utvecklingstider? • Kan vi identifiera skillnader i funktionalitet? • Hur upplever utvecklare de olika analystjänsterna? Vi har använt en design and creation strategi för att utveckla två Proof of Concept prototyper och samlat in data genom att använda flera datainsamlingsmetoder. Proof of Concept prototyperna inkluderade två artefakter, en för Azure Stream Analytics och en för HDInsight/Storm. Vi utvärderade dessa genom att utföra fem olika scenarier som var för sig hade 2-5 delmål. Vi simulerade strömmande data genom att låta en applikation kontinuerligt slumpa fram data som vi analyserade med hjälp av de två realtidsanalystjänsterna. Vi har använt oss av observationer för att dokumentera hur vi arbetade med utvecklingen av analystjänsterna samt för att mäta utvecklingstider och identifiera skillnader i funktionalitet. Vi har även använt oss av frågeformulär för att ta reda på vad användare tyckte om analystjänsterna. Vi kom fram till att Azure Stream Analytics initialt var mer användbart än HDInsight/Storm men att skillnaderna minskade efter hand. Azure Stream Analytics var lättare att arbeta med vid simplare analyser medan HDInsight/Storm hade ett bredare val av funktionalitet.

Principles of Personalisation of Service Discovery

We define personalisation as the set of capabilities that enables a user or an organisation to customise their working environment to suit their specific needs, preferences and circumstances. In the context of service discovery on the Grid, the demand for personalisation comes from individual users, who want their preferences to be taken into account during the search and selection of suitable services. These preferences can express, for example, the reliability of a service, quality of results, functionality, and so on. In this paper, we identify the problems related to personalising service discovery and present our solution: a personalised service registry or View. We describe scenarios in which personsalised service discovery would be useful and describe how our technology achieves them.