The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

The seasonal forecast of electricity demand: A hierarchical Bayesian model with climatological weather generator

In this paper we focus on the one year ahead prediction of the electricity peak-demand daily trajectory during the winter season in Central England and Wales. We define a Bayesian hierarchical model for predicting the winter trajectories and present results based on the past observed weather. Thanks to the flexibility of the Bayesian approach, we are able to produce the marginal posterior distributions of all the predictands of interest. This is a fundamental progress with respect to the classical methods. The results are encouraging in both skill and representation of uncertainty. Further extensions are straightforward at least in principle. The main two of those consist in conditioning the weather generator model with respect to additional information like the knowledge of the first part of the winter and/or the seasonal weather forecast. Copyright (C) 2006 John Wiley & Sons, Ltd.

Deciding the price of fame

Previous studies of ignorance-driven decision-making have either analyzed when ignorance should prove advantageous on theoretical grounds, or else they have examined whether human behavior is consistent with an ignorance driven inference strategy (e.g., the recognition heuristic). The current study merges these research goals by examining whether – under conditions where ignorance driven inference might be expected – the type of advantages theoretical analyses predict are evident in human performance data. A single experiment shows that, when asked to make relative wealth judgments, participants reliably use recognition as a basis for their judgments. Their wealth judgments under these conditions are reliably more accurate when some of the target names are unknown than when participants recognize all the names (the “less-is-more effect”). these data are robust against a number of variations on the size of the pool from which participants have to choose and the nature of the wealth judgment.

The price of risk in construction projects: contingency approximation model (CAM)

Little attention has been focussed on a precise definition and evaluation mechanism for project management risk specifically related to contractors. When bidding, contractors traditionally price risks using unsystematic approaches. The high business failure rate our industry records may indicate that the current unsystematic mechanisms contractors use for building up contingencies may be inadequate. The reluctance of some contractors to include a price for risk in their tenders when bidding for work competitively may also not be a useful approach. Here, instead, we first define the meaning of contractor contingency, and then we develop a facile quantitative technique that contractors can use to estimate a price for project risk. This model will help contractors analyse their exposure to project risks; and help them express the risk in monetary terms for management action. When bidding for work, they can decide how to allocate contingencies strategically in a way that balances risk and reward.

The price of space: the convergence of value in use and value in exchange

This paper discusses concepts of value from the point of view of the user of the space and the counter view of the provider of the same. Land and property are factors of production. The value of the land flows from the use to which it is put, and that in turn, is dependent upon the demand (and supply) for the product or service that is produced/provided from that space. If there is a high demand for the product (at a fixed level of supply), the price will increase and the economic rent for the land/property will increase accordingly. This is the underlying paradigm of Ricardian rent theory where the supply of land is fixed and a single good is produced. In such a case the rent of land is wholly an economic rent. Economic theory generally distinguishes between two kinds of price, price of production or “value in use” (as determined by the labour theory of value), and market price or “value in exchange” (as determined by supply and demand). It is based on a coherent and consistent theory of value and price. Effectively the distinction is between what space is ‘worth’ to an individual and that space’s price of exchange in the market place. In a perfect market where any individual has access to the same information as all others in the market, price and worth should coincide. However in a market where access to information is not uniform, and where different uses compete for the same space, it is more likely that the two figures will diverge. This paper argues that the traditional reliance of valuers to use methods of comparison to determine “price” has led to an artificial divergence of “value in use” and “value in exchange”, but now such comparison are becoming more difficult due to the diversity of lettings in the market place, there will be a requirement to return to fundamentals and pay heed to the thought process of the user in assessing the worth of the space to be let.

The evolution of electricity demand and the role for demand side participation, in buildings and transport

This paper explores the possible evolution of UK electricity demand as we move along three potential transition pathways to a low carbon economy in 2050.The shift away from fossil fuels through the electrification of demand is discussed, particularly through the uptake of heat pumps and electric vehicles in the domestic and passenger transport sectors. Developments in the way people and institutions may use energy along each of the pathways are also considered and provide a rationale for the quantification of future annual electricity demands in various broad sectors. The paper then presents detailed modelling of hourly balancing of these demands in the context of potential low carbon generation mixes associated with the three pathways. In all cases, hourly balancing is shown to be a significant challenge. To minimise the need for conventional generation to operate with very low capacity factors, a variety of demand side participation measures are modelled and shown to provide significant benefits. Lastly, projections of greenhouse gas emissions from the UK and the imports of fossil fuels to the UK for each of the three pathways are presented.

Assessing the impact on chronic disease of incorporating the societal cost of greenhouse gases into the price of food: an econometric and comparative risk assessment modelling study

Objectives To model the impact on chronic disease of a tax on UK food and drink that internalises the wider costs to society of greenhouse gas (GHG) emissions and to estimate the potential revenue. Design An econometric and comparative risk assessment modelling study. Setting The UK. Participants The UK adult population. Interventions Two tax scenarios are modelled: (A) a tax of £2.72/tonne carbon dioxide equivalents (tCO2e)/100 g product applied to all food and drink groups with above average GHG emissions. (B) As with scenario (A) but food groups with emissions below average are subsidised to create a tax neutral scenario. Outcome measures Primary outcomes are change in UK population mortality from chronic diseases following the implementation of each taxation strategy, the change in the UK GHG emissions and the predicted revenue. Secondary outcomes are the changes to the micronutrient composition of the UK diet. Results Scenario (A) results in 7770 (95% credible intervals 7150 to 8390) deaths averted and a reduction in GHG emissions of 18 683 (14 665to 22 889) ktCO2e/year. Estimated annual revenue is £2.02 (£1.98 to £2.06) billion. Scenario (B) results in 2685 (1966 to 3402) extra deaths and a reduction in GHG emissions of 15 228 (11 245to 19 492) ktCO2e/year. Conclusions Incorporating the societal cost of GHG into the price of foods could save 7770 lives in the UK each year, reduce food-related GHG emissions and generate substantial tax revenue. The revenue neutral scenario (B) demonstrates that sustainability and health goals are not always aligned. Future work should focus on investigating the health impact by population subgroup and on designing fiscal strategies to promote both sustainable and healthy diets.

A comparative value of electricity storage within GB market mechanisms

This paper investigates the value of a generic storage system within two GB market mechanisms and one ancillary service provision: the wholesale power market, the Balancing Mechanism and Firm Frequency Response (FFR). Three models are evaluated under perfect foresight and fixed horizon which is subsequently extended to explore the impact of a longer foresight on market revenues. The results show that comparatively, the balancing mechanism represents the highest source of potential revenues followed by the wholesale power market and Firm Frequency Response respectively. Longer horizons show diminishing returns, with the 1 day horizon providing the vast majority of total revenues. However storage power capacity utilization benefits from such long horizons. These results could imply that short horizons are very effective in capturing revenues in both the wholesale market and balancing mechanism whereas sizing of a storage system should take into consideration horizon foresight and accuracy for greater benefit.

The price of threat: the role of identity-safe marketplaces in predicting intergroup price sensitivity

In field experiments with subjects living either inside or outside Brazilian slums (n=955), we show that consumers living in slums are less price sensitive, in opposition with recent price sensitivity research. Comparing slum and non-slum dwellers, we found that negatively stereotyped consumers (e.g. slum dwellers) were more likely to pay higher amounts for friendlier customer service when facing social identity threats (SITs) in marketplaces such as banks. The mechanism which makes them less price sensitive is related to the perception of how other people evaluate their social groups, and we argue that they pay more because they are seeking identity-safe commercial relationships. This work, besides extending the literature in SITs, presents a perspective for the exchange between economics and psychology on price sensitivity, showing that consumers living in slums are willing to pay more to avoid possibly social identity threating experiences.