پویایی های نظام سوئیچینگ و بین روزی در شکل گیری قیمت برق
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|15415||2008||22 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Energy Economics, Volume 30, Issue 4, July 2008, Pages 1776–1797
This paper analyses the complex, non-linear effects of spot price drivers in wholesale electricity markets: their intra-day dynamics and transient irregularities. The context is the UK market, after the reforms introduced in March 2001, analysed with an original set of price drivers reflecting economic, technical, strategic, risk, behavioural and market design effects. Models are estimated separately as daily time-series of the 48 half-hourly trading periods. All coefficients exhibit substantial intra-day variation, relating to the heterogeneity of operating plants and market design aspects. This reveals a market responding to economic fundamentals and plant operating properties, with learning and emergent financial characteristics, as well as some strategic manipulation of capacity, most effectively exercised by the more flexible plants. Using regime-switching parameters, the effects of capacity margin and inter-day capacity adjustment are elucidated, suggesting rent-seeking behaviour, despite the relatively low prices at the time. Overall, high-frequency, aggregate fundamental price models can usefully uncover critical aspects of market performance, evolution and agent behaviour.
Price formation in spot electricity markets is a complex process posing substantial modelling challenges. This is due to a convolution of factors, including: i) the instantaneous nature of the commodity, ii) the shape of the supply function, which, in the presence of diverse plant technologies, is intrinsically steeply increasing, discontinuous and convex, iii) the exercise of market power, which results from oligopolistic structures, agents' asymmetries and the negligible demand elasticity to price in the short-term, iv) complex market designs due to real-time balancing, and v) substantial agents learning through daily-repeated auctions, but subject to frequent regulatory interventions and market structure changes. Various stochastic models have been proposed for the idiosyncratic price dynamics that arise (e.g. Escribano et al., 2002, de Jong and Huisman, 2003, Knittel and Roberts, 2005 and Geman and Roncoroni, 2006). To serve the needs of derivatives pricing, one focus has been upon autoregressive, stylised specifications, which replicate essential price properties, such as mean-reversion, seasonality, jump occurrence, and volatility clustering, but provide limited explanatory insights on price formation. In contrast, clarifying the degree to which prices reflect economic, technical, strategic, risk, or behavioural factors across intra-day trading periods and over time may reveal the degree of market efficiency, the subtleties of agent behaviour and the market attractors in particular situations. Such insights are important for regulators, in their market monitoring as well as to market agents, in order to understand their risk exposures. In addition, price models based on market fundamentals are appealing for short-term forecasting and scenario construction, as they allow agents to incorporate specific expectations about future market conditions and hence convert private information to possible strategic advantage. A purely statistical model cannot create such agent-specific, conditional expectations. Nevertheless, existing fundamental models for electricity prices exhibit a number of limitations. Firstly, they are primarily constrained to autoregressive effects and the price responses to demand, fuel prices or weather conditions, such as temperature, precipitation and wind (e.g. Nogales et al., 2002, Kanamura and Ohashi, 2004, Vehvilainen and Pyykkonen, 2004, Kosater, 2006, Rambharat et al., 2005 and Huisman, 2007). In competitive electricity markets, such effects need to be complemented with: i) aspects of plant dynamics, as suggested by technical and economic arguments, ii) measures of risk, as implied by Longstaff and Wang (2004), iii) market design and market structure effects (e.g. Wolak, 2000 and Bower and Bunn, 2001), iv) agent learning and iv) strategic behaviour. Although market power has been documented extensively in market assessments as well as in competition models (e.g. Wolfram, 1999, Borenstein et al., 1999, Green and Newbery, 1992 and Day et al., 2002), relevant indicators do not appear in econometric price models. Secondly, many specifications tend to refer to daily average prices, whilst intra-day patterns of trading display distinct price profiles, reflecting the daily variation of demand and operational constraints. In this context, profitability may be selectively achieved by agent strategies across the day. Nevertheless, only a few high-frequency studies1 have appeared in the literature (e.g. Huisman et al., 2007). Finally, existing formulations generally assume constant effects, over time, but this disregards the evolution of agents' behaviour to changing market conditions. Motivated by the above issues, this paper proposes fundamental price models – linear and regime-switching regressions – to clarify the determinants of prices and in particular, the size, intra-day variation and transient irregularities of various effects. Our context is the British2 electricity market, over the first year after the 2001 reforms, which transformed the compulsory day-ahead power pool, operating since 1990, into a fully liberalised, continuous, voluntary trading process. Among our principal objectives is to identify the extent to which prices in the new market were cost-reflective, in terms of economic fundamentals, or manifested, despite their low levels during this period, some forms of strategic pricing. As various countries restructure their electricity markets and introduce further liberalising reforms, the inferences derived from the British market can have significant implications. To elucidate the fine aspects of electricity price formation, econometric modelling is undertaken on an original, high-frequency data set. After defining a variety of potential price drivers, models are estimated across the 48 trading periods of the day. These specifications reveal a substantial, systematic component in prices as well as considerable diurnal heterogeneity in price formation. Subsequently, as spot electricity prices exhibit recurrent, fast-reverting spikes, of unpredictable magnitude and timing, which induce severe financial risks, and auction theory predicts the existence of multiple equilibria (Green and Newbery, 1992 and von der Fehr and Harbord, , 1993), an appealing hypothesis to be tested is whether the price formation process itself exhibits regime shifts. Thus, economic fundamentals could dictate pricing in normal states, whereas strategic effects could prevail in abnormal spiky states. These non-linear models allow a more precise assessment of extreme price risks. Whether the magnitude of extreme prices is arbitrary, given that various sources can induce irregularities, or whether it still obeys some fundamental relationship, thereby indicating a systematic agent reaction to favourable market conditions, is an issue that had not been previously addressed. Overall, these econometric specifications, applied to the British market over 2001–2002, reveal a market responding to economic fundamentals and plant operating constraints to a certain extent, with learning and emergent financial characteristics, but still some strategic manipulation of capacity. The latter becomes more intense during trading periods of peak demand and during temporal market irregularities. The presence of strategic effects in pricing could be perceived as a natural response to the removal of capacity payments in the reformed market and also, consistent, to a certain extent, with a reform objective to reward flexible plant more efficiently. Nevertheless, the magnitude, diurnal persistence and cyclical pattern of these effects implies that, despite the substantial decline in wholesale prices, market power was being systematically exercised, and most effectively by the flexible plants. The paper is organised as follows. Section 2 describes the reformed market design introduced in March 2001 and comments on the decline of wholesale prices at the time. Section 3 specifies the expected price properties after the reforms and defines potential price drivers of spot electricity prices. In Section 4, a regression specification, estimated across the 48 trading periods of the day, clarifies the intra-day dynamics of price formation. Section 5 uncovers temporal irregularities in price formation through Markov regime-switching. Section 6 concludes.
نتیجه گیری انگلیسی
Due to the idiosyncratic nature of wholesale electricity markets, spot price formation is a complex stochastic process posing substantial modelling challenges. This paper focuses on the complex non-linear characteristics of spot price drivers, in particular the intra-day dynamics and transient irregularities of their effects. First, an original, diverse set of potential influential factors is defined, motivated by the existing literature as well as market intuition. In order to clarify the elements of price variation at a high-frequency level, linear regression specifications are estimated across the 48 trading periods of the day. Subsequently, regime-switching parameters are introduced, in periods where such non-linearities arise, in order to uncover how agents react during transient market irregularities and how prices are altered as a result. This fundamental econometric analysis, undertaken for the first time at this level and frequency, reveals subtle aspects of pricing and agent behaviour. Such insights are important for regulators, in their market monitoring as well as to market agents, in order to model their risk exposures. Firstly, spot prices are influenced by a mixture of factors including economic fundamentals, plant constraints, strategic behaviour, perceived risk, trading inefficiencies, learning, and market design implications. The intensity of these effects across markets is expected to depend on the specific market configuration. Secondly, all effects exhibit substantial intra-day variation, in terms of magnitude and significance, which reflects the diurnal heterogeneity of scheduled plants as well as market design aspects. This variation would be of interest both to regulators and market participants. Thirdly, transient pricing irregularities, manifested as spikes, exhibit an interesting property; on these occasions, strategic factors appear to be significant and much more influential, whereas the impact of cost-fundamentals is constrained compared to the normal pricing regime. Hence, the magnitude of spikes, despite the diversity of underlying causes, is not arbitrary. Instead, it demonstrates a recurrent and co-ordinated generators' reaction to scarcity, whenever this arises and irrespectively of its exact source. Overall, the real-time balancing of demand and supply, inherent in electricity markets, implies a particular sensitivity of spot prices to contemporaneous market fundamentals. Clarifying these sensitivities is revealing of the degree of market efficiency and the subtleties of agent behaviour. Implications for price forecasting may also be significant. In the presence of market power and significant asymmetries across agents, which arise due to dissimilarities in their size, plant portfolio, and degree of vertical or horizontal integration, critical information on future market fundamentals may not be reflected in forward electricity prices, but be instead available to a subset of market participants, e.g. the dominant generators or integrated companies. Fundamental price models, such as those developed in this paper, would allow agents or regulatory authorities to incorporate their heterogeneous expectations about future market conditions and hence, convert their private information to a strategic advantage. A purely statistical model which does not invoke market fundamentals cannot exploit such agent-specific expectations. In terms of volatility patterns, the linear regression models allow for intra-day variations in volatility, along with the impacts of the various fundamentals, while the regime-switching regressions allow for discontinuous transitions between regular or excessive pricing, within a given trading period. Regarding the British electricity market, despite the low price era, and its fundamental explanation relating to overcapacity and reduced generation concentration, the daily price dynamics revealed substantial effects that were not truly “cost-reflective”. More specifically, our modelling reveals a market responding to economic fundamentals and plant operating constraints to a certain extent, with learning and emergent financial characteristics, but still some strategic manipulation of capacity. The latter appears more intense during trading periods of peak demand and during temporal market irregularities. The presence of strategic effects in pricing could be perceived as a natural response to the abolishment of capacity payments and consistent, to a certain extent, with the regulatory objective to reward flexibility. Nevertheless, the magnitude, diurnal persistence and cyclical pattern of these effects implies that, despite the substantial decline in wholesale prices, market power was being systematically exercised, and most effectively by the flexible plant. Still, market power was not exercised to its full potential. Although prices were particularly sensitive to margin levels and inter-day capacity adjustments, as a result of generators' bidding behaviour, they still remained at fairly low levels. This could be partially attributed to restrictions posed by underlying fundamentals, such as the overcapacity issue, the lower concentration in the generation sector and the declining path of fuel prices. An alternative conjecture is that the low wholesale price regime was being favoured by the vertically-integrated players as a convenient focal point after the removal of the cap on retail prices. To the extent that retail customers are not price sensitive, the vertically-integrated players could retain any loss of income from lower wholesale prices in their retail businesses. Just as the compulsory uniform price auction of the Pool created misleading signals for over-investment in baseload capacity, the post-Neta market may have been offering rather excessive rewards for a combination of flexible technologies and vertical integration. As various countries are currently restructuring their electricity markets or introducing further reforms, towards less centralised market regimes, the inferences derived from the reformed British market can have significant implications. Overall, high-frequency, aggregate fundamental price models can usefully uncover critical aspects of market performance, evolution and agent behaviour.