Modelling interregional links in electricity price spikes

Abnormally high price spikes in spot electricity markets represent a significant risk to market participants. As such, a literature has developed that focuses on forecasting the probability of such spike events, moving beyond simply forecasting the level of price. Many univariate time series models have been proposed to dealwith spikes within an individual market region. This paper is the first to develop a multivariate self-exciting point process model for dealing with price spikes across connected regions in the Australian National Electricity Market. The importance of the physical infrastructure connecting the regions on the transmission of spikes is examined. It is found that spikes are transmitted between the regions, and the size of spikes is influenced by the available transmission capacity. It is also found that improved risk estimates are obtained when inter-regional linkages are taken into account.

The Financialization of Food: An Inquiry into the 2008-2011 Food Price Spikes

This dissertation investigates the question: has financial speculation contributed to global food price volatility since the mid 2000s? I problematize the mainstream academic literature on the 2008-2011 food price spikes as being dominated by neoclassical economic perspectives and offer new conceptual and empirical insights into the relationship between financial speculation and food. Presented in three journal style manuscripts, manuscript one uses circuits of capital to conceptualize the link between financial speculators in the global north and populations in the global south. Manuscript two argues that what makes commodity index speculation (aka ‘index funds’ or index swaps) novel is that it provides institutional investors with what Clapp (2014) calls “financial distance” from the biopolitical implications of food speculation. Finally, manuscript three combines Gramsci’s concepts of hegemony and ‘the intellectual’ with the concept of performativity to investigate the ideological role that public intellectuals and the rhetorical actor the market play in the proliferation and governance of commodity index speculation. The first two manuscripts take an empirically mixed method approach by combining regression analysis with discourse analysis, while the third relies on interview data and discourse analysis. The findings show that financial speculation by index swap dealers and hedge funds did indeed significantly contribute to the price volatility of food commodities between June 2006 and December 2014. The results from the interview data affirm these findings. The discourse analysis of the interview data shows that public intellectuals and rhetorical characters such as ‘the market’ play powerful roles in shaping how food speculation is promoted, regulated and normalized. The significance of the findings is three-fold. First, the empirical findings show that a link does exist between financial speculation and food price volatility. Second, the findings indicate that the post-2008 CFTC and the Dodd-Frank reforms are unlikely to reduce financial speculation or the price volatility that it causes. Third, the findings suggest that institutional investors (such as pension funds) should think critically about how they use commodity index speculation as a way of generating financial earnings.

Composite auction method for suppressing unreasonable electricity price spikes in a competitive electricity market

The existence of undesirable electricity price spikes in a competitive electricity market requires an efficient auction mechanism. However, many of the existing auction mechanism have difficulties in suppressing such unreasonable price spikes effectively. A new auction mechanism is proposed to suppress effectively unreasonable price spikes in a competitive electricity market. It optimally combines system marginal price auction and pay as bid auction mechanisms. A threshold value is determined to activate the switching between the marginal price auction and the proposed composite auction. Basically when the system marginal price is higher than the threshold value, the composite auction for high price electricity market is activated. The winning electricity sellers will sell their electricity at the system marginal price or their own bid prices, depending on their rights of being paid at the system marginal price and their offers' impact on suppressing undesirable price spikes. Such economic stimuli discourage sellers from practising economic and physical withholdings. Multiple price caps are proposed to regulate strong market power. We also compare other auction mechanisms to highlight the characteristics of the proposed one. Numerical simulation using the proposed auction mechanism is given to illustrate the procedure of this new auction mechanism.

The Financialization of Food: An Inquiry into the 2008-2011 Food Price Spikes

This dissertation investigates the question: has financial speculation contributed to global food price volatility since the mid 2000s? I problematize the mainstream academic literature on the 2008-2011 food price spikes as being dominated by neoclassical economic perspectives and offer new conceptual and empirical insights into the relationship between financial speculation and food. Presented in three journal style manuscripts, manuscript one uses circuits of capital to conceptualize the link between financial speculators in the global north and populations in the global south. Manuscript two argues that what makes commodity index speculation (aka ‘index funds’ or index swaps) novel is that it provides institutional investors with what Clapp (2014) calls “financial distance” from the biopolitical implications of food speculation. Finally, manuscript three combines Gramsci’s concepts of hegemony and ‘the intellectual’ with the concept of performativity to investigate the ideological role that public intellectuals and the rhetorical actor the market play in the proliferation and governance of commodity index speculation. The first two manuscripts take an empirically mixed method approach by combining regression analysis with discourse analysis, while the third relies on interview data and discourse analysis. The findings show that financial speculation by index swap dealers and hedge funds did indeed significantly contribute to the price volatility of food commodities between June 2006 and December 2014. The results from the interview data affirm these findings. The discourse analysis of the interview data shows that public intellectuals and rhetorical characters such as ‘the market’ play powerful roles in shaping how food speculation is promoted, regulated and normalized. The significance of the findings is three-fold. First, the empirical findings show that a link does exist between financial speculation and food price volatility. Second, the findings indicate that the post-2008 CFTC and the Dodd-Frank reforms are unlikely to reduce financial speculation or the price volatility that it causes. Third, the findings suggest that institutional investors (such as pension funds) should think critically about how they use commodity index speculation as a way of generating financial earnings.

Modelling Spikes in Electricity Prices

uring periods of market stress, electricity prices can rise dramatically. Electricity retailers cannot pass these extreme prices on to customers because of retail price regulation. Improved prediction of these price spikes therefore is important for risk management. This paper builds a time-varying-probability Markov-switching model of Queensland electricity prices, aimed particularly at forecasting price spikes. Variables capturing demand and weather patterns are used to drive the transition probabilities. Unlike traditional Markov-switching models that assume normality of the prices in each state, the model presented here uses a generalised beta distribution to allow for the skewness in the distribution of electricity prices during high-price episodes.

Defining expected cost for the air conditioning to avoid a price spike of electricity market under DSR model

This work presents a demand side response model (DSR) which assists small electricity consumers, through an aggregator, exposed to the market price to proactively mitigate price and peak impact on the electrical system. The proposed model allows consumers to manage air-conditioning when as a function of possible price spikes. The main contribution of this research is to demonstrate how consumers can minimise the total expected cost by optimising air-conditioning to account for occurrences of a price spike in the electricity market. This model investigates how pre-cooling method can be used to minimise energy costs when there is a substantial risk of an electricity price spike. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics during hot days on weekdays in the period 2011 to 2012.

Electricity market price spike forecast with data mining techniques

Electricity market price forecast is a changeling yet very important task for electricity market managers and participants. Due to the complexity and uncertainties in the power grid, electricity prices are highly volatile and normally carry with spikes. which may be (ens or even hundreds of times higher than the normal price. Such electricity spikes are very difficult to be predicted. So far. most of the research on electricity price forecast is based on the normal range electricity prices. This paper proposes a data mining based electricity price forecast framework, which can predict the normal price as well as the price spikes. The normal price can be, predicted by a previously proposed wavelet and neural network based forecast model, while the spikes are forecasted based on a data mining approach. This paper focuses on the spike prediction and explores the reasons for price spikes based on the measurement of a proposed composite supply-demand balance index (SDI) and relative demand index (RDI). These indices are able to reflect the relationship among electricity demand, electricity supply and electricity reserve capacity. The proposed model is based on a mining database including market clearing price, trading hour. electricity), demand, electricity supply and reserve. Bayesian classification and similarity searching techniques are used to mine the database to find out the internal relationships between electricity price spikes and these proposed. The mining results are used to form the price spike forecast model. This proposed model is able to generate forecasted price spike, level of spike and associated forecast confidence level. The model is tested with the Queensland electricity market data with promising results. Crown Copyright (C) 2004 Published by Elsevier B.V. All rights reserved.

Demand Response for Residential Appliances in a Smart Electricity Distribution Network: Utility and Customer Perspectives

This thesis introduces advanced Demand Response algorithms for residential appliances to provide benefits for both utility and customers. The algorithms are engaged in scheduling appliances appropriately in a critical peak day to alleviate network peak, adverse voltage conditions and wholesale price spikes also reducing the cost of residential energy consumption. Initially, a demand response technique via customer reward is proposed, where the utility controls appliances to achieve network improvement. Then, an improved real-time pricing scheme is introduced and customers are supported by energy management schedulers to actively participate in it. Finally, the demand response algorithm is improved to provide frequency regulation services.

A new global wheat marketmodel (GLOWMM) for the analysis of wheat export prices

Food commodity prices fluctuations have important impacts on poverty and food insecurity across the world. Conventional models have not provided a complete picture of recent price spikes in agricultural commodity markets, while there is an urgent need for appropriate policy responses. Perhaps new approaches are needed in order to better understand international spill-overs, the feedback between the real and the financial sectors and also the link between food and energy prices. In this paper, we present results from a new worldwide dynamic model that provides short and long-run impulse responses of wheat international prices to various real shocks.

Modeling electricity price events as point processes

Energy prices are highly volatile and often feature unexpected spikes. It is the aim of this paper to examine whether the occurrence of these extreme price events displays any regularities that can be captured using an econometric model. Here we treat these price events as point processes and apply Hawkes and Poisson autoregressive models to model the dynamics in the intensity of this process.We use load and meteorological information to model the time variation in the intensity of the process. The models are applied to data from the Australian wholesale electricity market, and a forecasting exercise illustrates both the usefulness of these models and their limitations when attempting to forecast the occurrence of extreme price events.

Semi-parametric forecasting of spikes in electricity prices

The occurrence of extreme movements in the spot price of electricity represents a significant source of risk to retailers. A range of approaches have been considered with respect to modelling electricity prices; these models, however, have relied on time-series approaches, which typically use restrictive decay schemes placing greater weight on more recent observations. This study develops an alternative, semi-parametric method for forecasting, which uses state-dependent weights derived from a kernel function. The forecasts that are obtained using this method are accurate and therefore potentially useful to electricity retailers in terms of risk management.

Az extrém ármozgások statisztikai jellemzői a magyar áramtőzsdén (The statistical characteristics of extreme price movements in the Hungarian power exchange)

2010. július 20-án megkezdte működését a magyar áramtőzsde, a HUPX. 2010. augusztus 16-án az első napokban tapasztalt 45-60 euró megawattórás ár helyett egyes órákban 2999 eurós árral szembesültek a piaci szereplők. A kiemelkedően magas árak megjelenése nem szokatlan az áramtőzsdéken a nemzetközi tapasztalatok szerint, sőt a kutatások kiemelten foglalkoznak az ún. ártüskék okainak felkutatásával, valamint megjelenésük kvantitatív és kvalitatív elemzésével. A cikkben a szerző bemutatja, milyen eredmények születtek a kiugró árak statisztikai vizsgálatai során a szakirodalomban, illetve azok következtetései hogyan állják meg a helyüket a magyar árak idősorát figyelembe véve. A szerző bemutat egy modellkeretet, amely a villamosenergia-árak viselkedését a hét órái szerint periodikusan váltakozó paraméterű eloszlásokkal írja le. A magyar áramtőzsde rövid története sajnos nem teszi lehetővé, hogy a hét minden órájára külön áreloszlást illeszthessünk. A szerző ezért a hét óráit két csoportba sorolja az ár eloszlásának jellege alapján: az ártüskék megjelenése szempontjából kockázatos és kevésbé kockázatos órákba. Ezután a HUPX-árak leírására felépít egy determinisztikus, kétállapotú rezsimváltó modellt, amellyel azonosítani lehet a kockázatos és kevésbé kockázatos órákat, valamint képet kaphatunk az extrém ármozgások jellegéről. / === / On 20th July, 2010 the Hungarian Power Exchange, the HUPX started its operation. On 16th August in certain hours the markets participants faced € 2,999 price instead of in the first days experienced 45-60 euros/mwh. According to the international experiences the appearance of the extremely high prices hasn’t been unusual in the power exchanges, the researches have focused exploring the causes of the so-called spikes and quantitative and qualitative analysis of those appearances. In this article the author describes what results were determined on statistical studies of outstanding prices in the literature, and how their conclusions stand up into account the time series of the Hungarian prices. The author presents a model framework which describes the behavior of electricity prices in the seven hours of periodically varying parameters. Unfortunately the brief history of the Hungarian Power Exchange does not allow to suit specific prices for each hour of week. Therefore the author classifies the hours of the week in the two groups based on the nature of price dispersion: according to the appearance of spikes to risky and less risky classes. Then for describing the HUPX prices the author builds a deterministic two-state, regime-changing model, which can be identified the risky and less risky hours, and to get a picture of the nature of extreme price movements.