Response theory for equilibrium and non-equilibrium statistical mechanics: causality and generalized Kramers-Kronig relations

We consider the general response theory recently proposed by Ruelle for describing the impact of small perturbations to the non-equilibrium steady states resulting from Axiom A dynamical systems. We show that the causality of the response functions entails the possibility of writing a set of Kramers-Kronig (K-K) relations for the corresponding susceptibilities at all orders of nonlinearity. Nonetheless, only a special class of directly observable susceptibilities obey K-K relations. Specific results are provided for the case of arbitrary order harmonic response, which allows for a very comprehensive K-K analysis and the establishment of sum rules connecting the asymptotic behavior of the harmonic generation susceptibility to the short-time response of the perturbed system. These results set in a more general theoretical framework previous findings obtained for optical systems and simple mechanical models, and shed light on the very general impact of considering the principle of causality for testing self-consistency: the described dispersion relations constitute unavoidable benchmarks that any experimental and model generated dataset must obey. The theory exposed in the present paper is dual to the time-dependent theory of perturbations to equilibrium states and to non-equilibrium steady states, and has in principle similar range of applicability and limitations. In order to connect the equilibrium and the non equilibrium steady state case, we show how to rewrite the classical response theory by Kubo so that response functions formally identical to those proposed by Ruelle, apart from the measure involved in the phase space integration, are obtained. These results, taking into account the chaotic hypothesis by Gallavotti and Cohen, might be relevant in several fields, including climate research. In particular, whereas the fluctuation-dissipation theorem does not work for non-equilibrium systems, because of the non-equivalence between internal and external fluctuations, K-K relations might be robust tools for the definition of a self-consistent theory of climate change.

Asymmetric response of demand-supply mismatch to investor's sentiment

We look through both the demand and supply side information to understand dynamics of price determination in the real estate market and examine how accurately investors’ attitudes predict the market returns and thereby flagging off extent of any demand-supply mismatch. Our hypothesis is based on the possibility that investors’ call for action in terms of their buy/sell decision and adjustment in reservation/offer prices may indicate impending demand-supply imbalances in the market. In the process, we study several real estate sectors to inform our analysis. The timeframe of our analysis (1995-2010) allows us to observe market dynamics over several economic cycles and in various stages of those cycles. Additionally, we also seek to understand how investors’ attitude or the sentiment affects the market activity over the cycles through asymmetric responses. We test our hypothesis variously using a number of measures of market activity and attitude indicators within several model specifications. The empirical models are estimated using Vector Error Correction framework. Our analysis suggests that investors’ attitude exert strong and statistically significant feedback effects in price determination. Moreover, these effects do reveal heterogeneous responses across the real estate sectors. Interestingly, our results indicate the asymmetric responses during boom, normal and recessionary periods. These results are consistent with the theoretical underpinnings.

Survival analysis of cereal crop variety innovations in the UK

This paper explores the changing survival patterns of cereal crop variety innovations in the UK since the introduction of plant breeders’ rights in the mid-1960s. Using non-parametric, semi-parametric and parametric approaches, we examine the determinants of the survival of wheat variety innovations, focusing on the impacts of changes to Plant Variety Protection (PVP) regime over the last four decades. We find that the period since the introduction of the PVP regime has been characterised by the accelerated development of new varieties and increased private sector participation in the breeding of cereal crop varieties. However, the increased flow of varieties has been accompanied by a sharp decline in the longevity of innovations. These trends may have contributed to a reduction in the returns appropriated by plant breeders from protected variety innovations and may explain the decline of conventional plant breeding in the UK. It may also explain the persistent demand from the seed industry for stronger protection. The strengthening of the PVP regime in conformity with the UPOV Convention of 1991, the introduction of EU-wide protection through the Community Plant Variety Office and the introduction of royalties on farm-saved seed have had a positive effect on the longevity of protected variety innovations, but have not been adequate to offset the long term decline in survival durations.

Dynamic analysis of house price diffusion across Asian financial centres

The aim of this paper is to explore effects of macroeconomic variables on house prices and also, the lead-lag relationships of real estate markets to examine house price diffusion across Asian financial centres. The analysis is based on the Global Vector Auto-Regression (GVAR) model estimated using quarterly data for six Asian financial centres (Hong Kong, Tokyo, Seoul, Singapore, Taipei and Bangkok) from 1991Q1 to 2011Q2. The empirical results indicate that the global economic conditions play significant roles in shaping house price movements across Asian financial centres. In particular, a small open economy that heavily relies on international trade such as – Singapore and Tokyo - shows positive correlations between economy’s openness and house prices, consistent with the Balassa-Samuelson hypothesis in international trade. However, region-specific conditions do play important roles as determinants of house prices, partly due to restrictive housing policies and demand-supply imbalances, as found in Singapore and Bangkok.

Using meteorological wind data to estimate turbine generation output: a sensitivity analysis

Various studies investigating the future impacts of integrating high levels of renewable energy make use of historical meteorological (met) station data to produce estimates of future generation. Hourly means of 10m horizontal wind are extrapolated to a standard turbine hub height using the wind profile power or log law and used to simulate the hypothetical power output of a turbine at that location; repeating this procedure using many viable locations can produce a picture of future electricity generation. However, the estimate of hub height wind speed is dependent on the choice of the wind shear exponent a or the roughness length z0, and requires a number of simplifying assumptions. This paper investigates the sensitivity of this estimation on generation output using a case study of a met station in West Freugh, Scotland. The results show that the choice of wind shear exponent is a particularly sensitive parameter which can lead to significant variation of estimated hub height wind speed and hence estimated future generation potential of a region.

A probabilistic analysis of the future potential of evaporative cooling systems in a temperate climate

The probabilistic projections of climate change for the United Kingdom (UK Climate Impacts Programme) show a trend towards hotter and drier summers. This suggests an expected increase in cooling demand for buildings – a conflicting requirement to reducing building energy needs and related CO2 emissions. Though passive design is used to reduce thermal loads of a building, a supplementary cooling system is often necessary. For such mixed-mode strategies, indirect evaporative cooling is investigated as a low energy option in the context of a warmer and drier UK climate. Analysis of the climate projections shows an increase in wet-bulb depression; providing a good indication of the cooling potential of an evaporative cooler. Modelling a mixed-mode building at two different locations, showed such a building was capable of maintaining adequate thermal comfort in future probable climates. Comparing the control climate to the scenario climate, an increase in the median of evaporative cooling load is evident. The shift is greater for London than for Glasgow with a respective 71.6% and 3.3% increase in the median annual cooling load. The study shows evaporative cooling should continue to function as an effective low-energy cooling technique in future, warming climates.

Do smart grids offer a new incentive for SME carbon reduction?

Collectively small and medium sized enterprises (SMEs) are significant energy users although many are unregulated by existing policies due to their low carbon emissions. Carbon reduction is often not a priority but smart grids may create a new opportunity. A smart grid will give electricity suppliers a picture of real-time energy flows and the opportunity for consumers to receive financial incentives for engaging in demand side management. As well as creating incentives for local carbon reduction, engaging SMEs with smart grids has potential for contributing to wider grid decarbonisation. Modelling of buildings, business activities and technology solutions is needed to identify opportunities for carbon reduction. The diversity of the SME sector complicates strategy development. SMEs are active in almost every business area and occupy the full range of property types. This paper reviews previous modelling work, exposing valuable data on floor space and energy consumption associated with different business activities. Limitations are seen with the age of this data and an inability to distinguish SME energy use. By modelling SME energy use, electrical loads are identified which could be shifted on demand, in a smart network. Initial analysis of consumption, not constrained by existing policies, identifies heating and cooling in retail and commercial offices as having potential for demand response. Hot water in hotel and catering and retail sectors may also be significant because of the energy storage potential. Areas to consider for energy efficiency schemes are also indicated.

Causal relationship between obesity and vitamin D status: bi-directional mendelian randomization analysis of multiple cohorts

BACKGROUND: Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis. METHODS AND FINDINGS: We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m(2) higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10⁻²⁷). The BMI allele score was associated both with BMI (p = 6.30×10⁻⁶²) and 25(OH)D (-0.06% [95% CI -0.10 to -0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10⁻⁵⁷ for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: -4.2 [95% CI -7.1 to -1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores). CONCLUSIONS: On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.

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.

Demand side response: patterns in Europe and future policy perspectives under capacity mechanisms

Demand Side Response (DSR) has been slow to emerge in European electricity markets. This paper aims to both examine the reasons for low levels of DSR in Europe and reflect on factors that might affect the participation of DSR in capacity mechanisms. It relies on available evidence from the literature, secondary data on existing DSR programmes and energy aggregator's data from industries participating in DSR. Findings show that changes to the duration of contracted loads under existing or new programmes might increase the penetration of DSR. The introduction of capacity mechanisms may increase DSR from demand turn down if longer response times were available.

The timing and societal synchronisation of energy demand

It is increasingly important to know about when energy is used in the home, at work and on the move. Issues of time and timing have not featured strongly in energy policy analysis and in modelling, much of which has focused on estimating and reducing total average annual demand per capita. If smarter ways of balancing supply and demand are to take hold, and if we are to make better use of decarbonised forms of supply, it is essential to understand and intervene in patterns of societal synchronisation. This calls for detailed knowledge of when, and on what occasions many people engage in the same activities at the same time, of how such patterns are changing, and of how might they be shaped. In addition, the impact of smart meters and controls partly depends on whether there is, in fact scope for shifting the timing of what people do, and for changing the rhythm of the day. Is the scheduling of daily life an arena that policy can influence, and if so how? The DEMAND Centre has been linking time use, energy consumption and travel diary data as a means of addressing these questions and in this working paper we present some of the issues and results arising from that exercise.

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.

Any response? How demand response could be enhanced based on early UK experience

Policy makers are in broad agreement that demand response should play a major role in EU electricity systems and provide much needed future system flexibility. Yet, little demand response has been forthcoming in member states to date. This paper identifies some of the technical potential for demand response, based on empirical data from one UK demand aggregator. Half-hourly electricity readings of demand during normal operation and during response events have been analysed for different industry and service sectors. We review these findings in the context of ongoing EU policy developments with particular focus on the role appropriate arrangements to enhance the available resource. We conclude that in some sectors appropriate policy and regulation could triple the available response capacity and thereby lead to stronger commercial uptake of demand response.

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.