Analysis of the Iberian electricity forward market hedging efficiency

An assessment of the hedging performance in the Iberian Forward Electricity Market is performed. Aggregated data from the Portuguese and Spanish clearing houses for energy derivatives are considered. The hedging performance is measured through the ratio of the final open interest of a month derivatives contract divided by its accumulated cleared volume. The base load futures in the Iberian energy derivatives exchange show the lowest ratios due to good liquidity. The peak futures show bigger ratios as their reduced liquidity is produced by auctions fixed by Portuguese regulation. The base load swaps settled in the clearing house located in Spain show initially large values due to low registered volumes, as this clearing house is mainly used for short maturity (daily and weekly swaps). This hedging ratio can be a powerful oversight tool for energy regulators when accessing to all the derivatives transactions as envisaged by European regulation.

Electricity price forecasting accounting for renewable energies: optimal combined forecasts

Electricity price forecasting is an interesting problem for all the agents involved in electricity market operation. For instance, every profit maximisation strategy is based on the computation of accurate one-day-ahead forecasts, which is why electricity price forecasting has been a growing field of research in recent years. In addition, the increasing concern about environmental issues has led to a high penetration of renewable energies, particularly wind. In some European countries such as Spain, Germany and Denmark, renewable energy is having a deep impact on the local power markets. In this paper, we propose an optimal model from the perspective of forecasting accuracy, and it consists of a combination of several univariate and multivariate time series methods that account for the amount of energy produced with clean energies, particularly wind and hydro, which are the most relevant renewable energy sources in the Iberian Market. This market is used to illustrate the proposed methodology, as it is one of those markets in which wind power production is more relevant in terms of its percentage of the total demand, but of course our method can be applied to any other liberalised power market. As far as our contribution is concerned, first, the methodology proposed by García-Martos et al(2007 and 2012) is generalised twofold: we allow the incorporation of wind power production and hydro reservoirs, and we do not impose the restriction of using the same model for 24h. A computational experiment and a Design of Experiments (DOE) are performed for this purpose. Then, for those hours in which there are two or more models without statistically significant differences in terms of their forecasting accuracy, a combination of forecasts is proposed by weighting the best models(according to the DOE) and minimising the Mean Absolute Percentage Error (MAPE). The MAPE is the most popular accuracy metric for comparing electricity price forecasting models. We construct the combi nation of forecasts by solving several nonlinear optimisation problems that allow computation of the optimal weights for building the combination of forecasts. The results are obtained by a large computational experiment that entails calculating out-of-sample forecasts for every hour in every day in the period from January 2007 to Decem ber 2009. In addition, to reinforce the value of our methodology, we compare our results with those that appear in recent published works in the field. This comparison shows the superiority of our methodology in terms of forecasting accuracy.

Propuestas regulatorias para el diseño de un mercado ibérico a plazo eficiente de la energía = Regulatory proposals for the development of an efficient iberian energy forward market

El mercado ibérico de futuros de energía eléctrica gestionado por OMIP (“Operador do Mercado Ibérico de Energia, Pólo Português”, con sede en Lisboa), también conocido como el mercado ibérico de derivados de energía, comenzó a funcionar el 3 de julio de 2006. Se analiza la eficiencia de este mercado organizado, por lo que se estudia la precisión con la que sus precios de futuros predicen el precio de contado. En dicho mercado coexisten dos modos de negociación: el mercado continuo (modo por defecto) y la contratación mediante subasta. En la negociación en continuo, las órdenes anónimas de compra y de venta interactúan de manera inmediata e individual con órdenes contrarias, dando lugar a operaciones con un número indeterminado de precios para cada contrato. En la negociación a través de subasta, un precio único de equilibrio maximiza el volumen negociado, liquidándose todas las operaciones a ese precio. Adicionalmente, los miembros negociadores de OMIP pueden liquidar operaciones “Over-The-Counter” (OTC) a través de la cámara de compensación de OMIP (OMIClear). Las cinco mayores empresas españolas de distribución de energía eléctrica tenían la obligación de comprar electricidad hasta julio de 2009 en subastas en OMIP, para cubrir parte de sus suministros regulados. De igual manera, el suministrador de último recurso portugués mantuvo tal obligación hasta julio de 2010. Los precios de equilibrio de esas subastas no han resultado óptimos a efectos retributivos de tales suministros regulados dado que dichos precios tienden a situarse ligeramente sesgados al alza. La prima de riesgo ex-post, definida como la diferencia entre los precios a plazo y de contado en el periodo de entrega, se emplea para medir su eficiencia de precio. El mercado de contado, gestionado por OMIE (“Operador de Mercado Ibérico de la Energía”, conocido tradicionalmente como “OMEL”), tiene su sede en Madrid. Durante los dos primeros años del mercado de futuros, la prima de riesgo media tiende a resultar positiva, al igual que en otros mercados europeos de energía eléctrica y gas natural. En ese periodo, la prima de riesgo ex-post tiende a ser negativa en los mercados de petróleo y carbón. Los mercados de energía tienden a mostrar niveles limitados de eficiencia de mercado. La eficiencia de precio del mercado de futuros aumenta con el desarrollo de otros mecanismos coexistentes dentro del mercado ibérico de electricidad (conocido como “MIBEL”) –es decir, el mercado dominante OTC, las subastas de centrales virtuales de generación conocidas en España como Emisiones Primarias de Energía, y las subastas para cubrir parte de los suministros de último recurso conocidas en España como subastas CESUR– y con una mayor integración de los mercados regionales europeos de energía eléctrica. Se construye un modelo de regresión para analizar la evolución de los volúmenes negociados en el mercado continuo durante sus cuatro primeros años como una función de doce indicadores potenciales de liquidez. Los únicos indicadores significativos son los volúmenes negociados en las subastas obligatorias gestionadas por OMIP, los volúmenes negociados en el mercado OTC y los volúmenes OTC compensados por OMIClear. El número de creadores de mercado, la incorporación de agentes financieros y compañías de generación pertenecientes a grupos integrados con suministradores de último recurso, y los volúmenes OTC compensados por OMIClear muestran una fuerte correlación con los volúmenes negociados en el mercado continuo. La liquidez de OMIP está aún lejos de los niveles alcanzados por los mercados europeos más maduros (localizados en los países nórdicos (Nasdaq OMX Commodities) y Alemania (EEX)). El operador de mercado y su cámara de compensación podrían desarrollar acciones eficientes de marketing para atraer nuevos agentes activos en el mercado de contado (p.ej. industrias consumidoras intensivas de energía, suministradores, pequeños productores, compañías energéticas internacionales y empresas de energías renovables) y agentes financieros, captar volúmenes del opaco OTC, y mejorar el funcionamiento de los productos existentes aún no líquidos. Resultaría de gran utilidad para tales acciones un diálogo activo con todos los agentes (participantes en el mercado, operador de mercado de contado, y autoridades supervisoras). Durante sus primeros cinco años y medio, el mercado continuo presenta un crecimento de liquidez estable. Se mide el desempeño de sus funciones de cobertura mediante la ratio de posición neta obtenida al dividir la posición abierta final de un contrato de derivados mensual entre su volumen acumulado en la cámara de compensación. Los futuros carga base muestran la ratio más baja debido a su buena liquidez. Los futuros carga punta muestran una mayor ratio al producirse su menor liquidez a través de contadas subastas fijadas por regulación portuguesa. Las permutas carga base liquidadas en la cámara de compensación ubicada en Madrid –MEFF Power, activa desde el 21 de marzo de 2011– muestran inicialmente valores altos debido a bajos volúmenes registrados, dado que esta cámara se emplea principalmente para vencimientos pequeños (diario y semanal). Dicha ratio puede ser una poderosa herramienta de supervisión para los reguladores energéticos cuando accedan a todas las transacciones de derivados en virtud del Reglamento Europeo sobre Integridad y Transparencia de los Mercados de Energía (“REMIT”), en vigor desde el 28 de diciembre de 2011. La prima de riesgo ex-post tiende a ser positiva en todos los mecanismos (futuros en OMIP, mercado OTC y subastas CESUR) y disminuye debido a la curvas de aprendizaje y al efecto, desde el año 2011, del precio fijo para la retribución de la generación con carbón autóctono. Se realiza una comparativa con los costes a plazo de generación con gas natural (diferencial “clean spark spread”) obtenido como la diferencia entre el precio del futuro eléctrico y el coste a plazo de generación con ciclo combinado internalizando los costes de emisión de CO2. Los futuros eléctricos tienen una elevada correlación con los precios de gas europeos. Los diferenciales de contratos con vencimiento inmediato tienden a ser positivos. Los mayores diferenciales se dan para los contratos mensuales, seguidos de los trimestrales y anuales. Los generadores eléctricos con gas pueden maximizar beneficios con contratos de menor vencimiento. Los informes de monitorización por el operador de mercado que proporcionan transparencia post-operacional, el acceso a datos OTC por el regulador energético, y la valoración del riesgo regulatorio pueden contribuir a ganancias de eficiencia. Estas recomendaciones son también válidas para un potencial mercado ibérico de futuros de gas, una vez que el hub ibérico de gas –actualmente en fase de diseño, con reuniones mensuales de los agentes desde enero de 2013 en el grupo de trabajo liderado por el regulador energético español– esté operativo. El hub ibérico de gas proporcionará transparencia al atraer más agentes y mejorar la competencia, incrementando su eficiencia, dado que en el mercado OTC actual no se revela precio alguno de gas. ABSTRACT The Iberian Power Futures Market, managed by OMIP (“Operador do Mercado Ibérico de Energia, Pólo Português”, located in Lisbon), also known as the Iberian Energy Derivatives Market, started operations on 3 July 2006. The market efficiency, regarding how well the future price predicts the spot price, is analysed for this energy derivatives exchange. There are two trading modes coexisting within OMIP: the continuous market (default mode) and the call auction. In the continuous trading, anonymous buy and sell orders interact immediately and individually with opposite side orders, generating trades with an undetermined number of prices for each contract. In the call auction trading, a single price auction maximizes the traded volume, being all trades settled at the same price (equilibrium price). Additionally, OMIP trading members may settle Over-the-Counter (OTC) trades through OMIP clearing house (OMIClear). The five largest Spanish distribution companies have been obliged to purchase in auctions managed by OMIP until July 2009, in order to partly cover their portfolios of end users’ regulated supplies. Likewise, the Portuguese last resort supplier kept that obligation until July 2010. The auction equilibrium prices are not optimal for remuneration purposes of regulated supplies as such prices seem to be slightly upward biased. The ex-post forward risk premium, defined as the difference between the forward and spot prices in the delivery period, is used to measure its price efficiency. The spot market, managed by OMIE (Market Operator of the Iberian Energy Market, Spanish Pool, known traditionally as “OMEL”), is located in Madrid. During the first two years of the futures market, the average forward risk premium tends to be positive, as it occurs with other European power and natural gas markets. In that period, the ex-post forward risk premium tends to be negative in oil and coal markets. Energy markets tend to show limited levels of market efficiency. The price efficiency of the Iberian Power Futures Market improves with the market development of all the coexistent forward contracting mechanisms within the Iberian Electricity Market (known as “MIBEL”) – namely, the dominant OTC market, the Virtual Power Plant Auctions known in Spain as Energy Primary Emissions, and the auctions catering for part of the last resort supplies known in Spain as CESUR auctions – and with further integration of European Regional Electricity Markets. A regression model tracking the evolution of the traded volumes in the continuous market during its first four years is built as a function of twelve potential liquidity drivers. The only significant drivers are the traded volumes in OMIP compulsory auctions, the traded volumes in the OTC market, and the OTC cleared volumes by OMIClear. The amount of market makers, the enrolment of financial members and generation companies belonging to the integrated group of last resort suppliers, and the OTC cleared volume by OMIClear show strong correlation with the traded volumes in the continuous market. OMIP liquidity is still far from the levels reached by the most mature European markets (located in the Nordic countries (Nasdaq OMX Commodities) and Germany (EEX)). The market operator and its clearing house could develop efficient marketing actions to attract new entrants active in the spot market (e.g. energy intensive industries, suppliers, small producers, international energy companies and renewable generation companies) and financial agents as well as volumes from the opaque OTC market, and to improve the performance of existing illiquid products. An active dialogue with all the stakeholders (market participants, spot market operator, and supervisory authorities) will help to implement such actions. During its firs five and a half years, the continuous market shows steady liquidity growth. The hedging performance is measured through a net position ratio obtained from the final open interest of a month derivatives contract divided by its accumulated cleared volume. The base load futures in the Iberian energy derivatives exchange show the lowest ratios due to good liquidity. The peak futures show bigger ratios as their reduced liquidity is produced by auctions fixed by Portuguese regulation. The base load swaps settled in the clearing house located in Spain – MEFF Power, operating since 21 March 2011, with a new denomination (BME Clearing) since 9 September 2013 – show initially large values due to low registered volumes, as this clearing house is mainly used for short maturity (daily and weekly swaps). The net position ratio can be a powerful oversight tool for energy regulators when accessing to all the derivatives transactions as envisaged by European regulation on Energy Market Integrity and Transparency (“REMIT”), in force since 28 December 2011. The ex-post forward risk premium tends to be positive in all existing mechanisms (OMIP futures, OTC market and CESUR auctions) and diminishes due to the learning curve and the effect – since year 2011 – of the fixed price retributing the indigenous coal fired generation. Comparison with the forward generation costs from natural gas (“clean spark spread”) – obtained as the difference between the power futures price and the forward generation cost with a gas fired combined cycle plant taking into account the CO2 emission rates – is also performed. The power futures are strongly correlated with European gas prices. The clean spark spreads built with prompt contracts tend to be positive. The biggest clean spark spreads are for the month contract, followed by the quarter contract and then by the year contract. Therefore, gas fired generation companies can maximize profits trading with contracts of shorter maturity. Market monitoring reports by the market operator providing post-trade transparency, OTC data access by the energy regulator, and assessment of the regulatory risk can contribute to efficiency gains. The same recommendations are also valid for a potential Iberian gas futures market, once an Iberian gas hub – currently in a design phase, with monthly meetings amongst the stakeholders in a Working Group led by the Spanish energy regulatory authority since January 2013 – is operating. The Iberian gas hub would bring transparency attracting more shippers and improving competition and thus its efficiency, as no gas price is currently disclosed in the existing OTC market.

Electricity without borders: a plan to make the internal market work. Bruegel Blueprint Series 20, 5 September 2013

The most straightforward European single energy market design would entail a European system operator regulated by a single European regulator. This would ensure the predictable development of rules for the entire EU, significantly reducing regulatory uncertainty for electricity sector investments. But such a first-best market design is unlikely to be politically realistic in the European context for three reasons. First, the necessary changes compared to the current situation are substantial and would produce significant redistributive effects. Second, a European solution would deprive member states of the ability to manage their energy systems nationally. And third, a single European solution might fall short of being well-tailored to consumers’ preferences, which differ substantially across the EU. To nevertheless reap significant benefits from an integrated European electricity market, we propose the following blueprint: First, we suggest adding a European system-management layer to complement national operation centres and help them to better exchange information about the status of the system, expected changes and planned modifications. The ultimate aim should be to transfer the day-to-day responsibility for the safe and economic operation of the system to the European control centre. To further increase efficiency, electricity prices should be allowed to differ between all network points between and within countries. This would enable throughput of electricity through national and international lines to be safely increased without any major investments in infrastructure. Second, to ensure the consistency of national network plans and to ensure that they contribute to providing the infrastructure for a functioning single market, the role of the European ten year network development plan (TYNDP) needs to be upgraded by obliging national regulators to only approve projects planned at European level unless they can prove that deviations are beneficial. This boosted role of the TYNDP would need to be underpinned by resolving the issues of conflicting interests and information asymmetry. Therefore, the network planning process should be opened to all affected stakeholders (generators, network owners and operators, consumers, residents and others) and enable the European Agency for the Cooperation of Energy Regulators (ACER) to act as a welfare-maximising referee. An ultimate political decision by the European Parliament on the entire plan will open a negotiation process around selecting alternatives and agreeing compensation. This ensures that all stakeholders have an interest in guaranteeing a certain degree of balance of interest in the earlier stages. In fact, transparent planning, early stakeholder involvement and democratic legitimisation are well suited for minimising as much as possible local opposition to new lines. Third, sharing the cost of network investments in Europe is a critical issue. One reason is that so far even the most sophisticated models have been unable to identify the individual long-term net benefit in an uncertain environment. A workable compromise to finance new network investments would consist of three components: (i) all easily attributable cost should be levied on the responsible party; (ii) all network users that sit at nodes that are expected to receive more imports through a line extension should be obliged to pay a share of the line extension cost through their network charges; (iii) the rest of the cost is socialised to all consumers. Such a cost-distribution scheme will involve some intra-European redistribution from the well-developed countries (infrastructure-wise) to those that are catching up. However, such a scheme would perform this redistribution in a much more efficient way than the Connecting Europe Facility’s ad-hoc disbursements to politically chosen projects, because it would provide the infrastructure that is really needed.

Reforming the Market Design of EU Electricity Markets: Addressing the Challenges of a Low-Carbon Power Sector. CEPS Task Force Report, 27 July 2015

This CEPS Task Force Report focuses on whether there is a need to adapt the EU’s electricity market design and if so, the options for doing so. In a first step, it analyses the current market trends by distinguishing between their causes and their consequences. Then, the current blueprint of EU power market design – the target model – is briefly introduced, followed by a discussion of the shortcomings of the current approach and the challenges in finding suitable solutions. The final chapter offers an inventory of solutions differentiating between recommendations shared among Task Force members and non-consensual options.

Short-term electricity price forecasting using wavelet and SVM techniques

In deregulated electricity market, modeling and forecasting the spot price present a number of challenges. By applying wavelet and support vector machine techniques, a new time series model for short term electricity price forecasting has been developed in this paper. The model employs both historical price and other important information, such as load capacity and weather (temperature), to forecast the price of one or more time steps ahead. The developed model has been evaluated with the actual data from Australian National Electricity Market. The simulation results demonstrated that the forecast model is capable of forecasting the electricity price with a reasonable forecasting accuracy.

Az MTA KRTK KTI munkaerő-piaci előrejelző rendszere = The Institute of Economics labour-market forecasting system

Ebben a cikkben bemutatjuk az MTA KRTK KTI munkaerő-piaci előrejelző rendszerének nagy léptékű szerkezetét, a szerkezet kialakítása során követett főbb elveket. Ismertetjük a hazai gyakorlatban egyedülállóan összetett és széles körű adatrendszert, amelyen a becslést és az előrejelzést elvégeztük. Röviden kitérünk az ágazati GDP előrejelzésére, a modell keresleti és kínálati oldalának működésére, valamint a kereslet és kínálat közötti eltérések dinamikájának vizsgálatára. ______ The article presents the overall structure, and main principles followed in devising the structure, of the labour-market forecasting system developed by the Institute of Economics of the Research Centre for Economic and Regional Studies of the Hungarian Academy of Sciences (MTA KRTK KTI). The authors present the broad, comprehensive data system unprecedented in Hungarian practice, from which the estimate and forecast are made. The article diverges briefly onto the forecasting of branch GDP, the mode of operation of the supply and demand sides of the model, and examination of the dynamics of discrepancies between supply and demand.

Stochastic modelling of financial time series with memory and multifractal scaling

Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

An analysis of the Brisbane residential property market and the global financial crisis

The period from 2007 to 2009 covered the residential property boom from early 2000, to the property recession following the Global Financial Crisis. Since late 2008, a number of residential property markets have suffered significant falls in house prices, buth this has not been consistent across all market sectors. This paper will analyze the housing market in Brisbane Australia to determine the impact, similarities and differences that the4 GFC had on range of residential sectors across a divesified property market. Data analysis will provide an overview of residential property prices, sales and listing volumes over the study period and will provide a comparison of median house price performance across the geographic and socio-economic areas of Brisbane.

Forecasting volatility and correlation : the role of option implied measures

Forecasts of volatility and correlation are important inputs into many practical financial problems. Broadly speaking, there are two ways of generating forecasts of these variables. Firstly, time-series models apply a statistical weighting scheme to historical measurements of the variable of interest. The alternative methodology extracts forecasts from the market traded value of option contracts. An efficient options market should be able to produce superior forecasts as it utilises a larger information set of not only historical information but also the market equilibrium expectation of options market participants. While much research has been conducted into the relative merits of these approaches, this thesis extends the literature along several lines through three empirical studies. Firstly, it is demonstrated that there exist statistically significant benefits to taking the volatility risk premium into account for the implied volatility for the purposes of univariate volatility forecasting. Secondly, high-frequency option implied measures are shown to lead to superior forecasts of the intraday stochastic component of intraday volatility and that these then lead on to superior forecasts of intraday total volatility. Finally, the use of realised and option implied measures of equicorrelation are shown to dominate measures based on daily returns.

Beyond demand management : the value of sharing electricity information

Technologies such as smart meters and electricity feedback are becoming an increasingly compelling focus for HCI researchers in light of rising power prices and peak demand. We argue, however, that a pre-occupation with the goal of demand management has limited the scope of design for these technologies. In this paper we present our work-in-progress investigating the potential value of socially sharing electricity information as a means of broadening the scope of design for these devices. This paper outlines some preliminary findings gathered from a design workshop and a series of qualitative interviews with householders in Brisbane, Australia, regarding their attitudes towards electricity feedback and sharing consumption information. Preliminary findings suggest that; (1) the social sharing of electricity feedback information has the potential to be of value in better informing consumption decisions, however; (2) the potential for sharing may be constrained by attitudes towards privacy, trust and the possibility of misinformation being shared. We conclude by outlining ideas for our future research on this topic and invite comments on these ideas.

Construction Prices : the Market Effect

Teachers of construction economics and estimating have for a long time recognised that there is more to construction pricing than detailed calculation of costs (to the contractor). We always get to the point where we have to say "of course, experience or familiarity of the market is very important and this needs judgement, intuition, etc". Quite how important is the matter in construction pricing is not known and we tend to trivialise its effect. If judgement of the market has a minimal effect, little harm would be done, but if it is really important then some quite serious consequences arise which go well beyond the teaching environment. Major areas of concern for the quantity surveyor are in cost modelling and cost planning - neither of which pay any significant attention to the market effect. There are currently two schools of thought about the market effect issue. The first school is prepared to ignore possible effects until more is known. This may be called the pragmatic school. The second school exists solely to criticise the first school. We will call this the antagonistic school. Neither the pragmatic nor the antagonistic schools seem to be particularly keen to resolve the issue one way or the other. The founder and leader of the antagonistic school is Brian Fine whose paper in 1974 is still the basic text on the subject, and in which he coined the term 'socially acceptable' price to describe what we now recognise as the market effect. Mr Fine's argument was then, and is since, that the uncertainty surrounding the contractors' costing and cost estimating process is such that the uncertainty surrounding the contractors' cost that it logically leads to a market-orientated pricing approach. Very little factual evidence, however, seems to be available to support these arguments in any conclusive manner. A further, and more important point for the pragmatic school, is that, even if the market effect is as important as Mr Fine believes, there are no indications of how it can be measured, evaluated or predicted. Since 1974 evidence has been accumulating which tends to reinforce the antagonists' view. A review of the literature covering both contractors' and designers' estimates found many references to the use of value judgements in construction pricing (Ashworth & Skitmore, 1985), which supports the antagonistic view in implying the existence of uncertainty overload. The most convincing evidence emerged quite by accident in some research we recently completed with practicing quantity surveyors in estimating accuracy (Skitmore, 1985). In addition to demonstrating that individual quantity surveyors and certain types of buildings had significant effect on estimating accuracy, one surprise result was that only a very small amount of information was used by the most expert surveyors for relatively very accurate estimates. Only the type and size of building, it seemed, was really relevant in determining accuracy. More detailed information about the buildings' specification, and even a sight to the drawings, did not significantly improve their accuracy level. This seemed to offer clear evidence that the constructional aspects of the project were largely irrelevant and that the expert surveyors were somehow tuning in to the market price of the building. The obvious next step is to feed our expert surveyors with more relevant 'market' information in order to assess its effect. The problem with this is that our experts do not seem able to verbalise their requirements in this respect - a common occurrence in research of this nature. The lack of research into the nature of market effects on prices also means the literature provides little of benefit. Hence the need for this study. It was felt that a clearer picture of the nature of construction markets would be obtained in an environment where free enterprise was a truly ideological force. For this reason, the United States of America was chosen for the next stage of our investigations. Several people were interviewed in an informal and unstructured manner to elicit their views on the action of market forces on construction prices. Although a small number of people were involved, they were thought to be reasonably representative of knowledge in construction pricing. They were also very well able to articulate their views. Our initial reaction to the interviews was that our USA subjects held very close views to those held in the UK. However, detailed analysis revealed the existence of remarkably clear and consistent insights that would not have been obtained in the UK. Further evidence was also obtained from literature relating to the subject and some of the interviewees very kindly expanded on their views in later postal correspondence. We have now analysed all the evidence received and, although a great deal is of an anecdotal nature, we feel that our findings enable at least the basic nature of the subject to be understood and that the factors and their interrelationships can now be examined more formally in relation to construction price levels. I must express my gratitude to the Royal Institution of Chartered Surveyors' Educational Trust and the University of Salford's Department of Civil Engineering for collectively funding this study. My sincere thanks also go to our American participants who freely gave their time and valuable knowledge to us in our enquiries. Finally, I must record my thanks to Tim and Anne for their remarkable ability to produce an intelligible typescript from my unintelligible writing.

Smart grid-demand side response model to mitigate prices and peak impact on the electrical system

The aims of this project is to develop demand side response model which assists electricity consumers who are exposed to the market price through aggregator to manage the air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimise the energy cost caused by the air-conditioning load considering the electricity market price and network overload. The model is tested with selected characteristics of the room, Queensland electricity market data from Australian Energy Market Operator and data from the Bureau of Statistics on temperatures in Brisbane, during weekdays on hot days from 2011 - 2012.

Estimating benefits of energy storage for aggregate storage applications in electricity distribution networks in Queensland

Electric Energy Storage (EES) is considered as one of the promising options for reducing the need for costly upgrades in distribution networks in Queensland (QLD). However, It is expected, the full potential for storage for distribution upgrade deferral cannot be fully realized due to high cost of EES. On the other hand, EES used for distribution deferral application can support a variety of complementary storage applications such as energy price arbitrage, time of use (TOU) energy cost reduction, wholesale electricity market ancillary services, and transmission upgrade deferral. Aggregation of benefits of these complementary storage applications would have the potential for increasing the amount of EES that may be financially attractive to defer distribution network augmentation in QLD. In this context, this paper analyzes distribution upgrade deferral, energy price arbitrage, TOU energy cost reduction, and integrated solar PV-storage benefits of EES devices in QLD.

Environmental efficiency of energy, materials, and emissions

This study estimates the environmental efficiency of international listed firms in 10 worldwide sectors from 2007 to 2013 by applying an order-m method, a non-parametric approach based on free disposal hull with subsampling bootstrapping. Using a conventional output of gross profit and two conventional inputs of labor and capital, this study examines the order-m environmental efficiency accounting for the presence of each of 10 undesirable inputs/outputs and measures the shadow prices of each undesirable input and output. The results show that there is greater potential for the reduction of undesirable inputs rather than bad outputs. On average, total energy, electricity, or water usage has the potential to be reduced by 50%. The median shadow prices of undesirable inputs, however, are much higher than the surveyed representative market prices. Approximately 10% of the firms in the sample appear to be potential sellers or production reducers in terms of undesirable inputs/outputs, which implies that the price of each item at the current level has little impact on most of the firms. Moreover, this study shows that the environmental, social, and governance activities of a firm do not considerably affect environmental efficiency.