Elsevier

Energy Policy

Volume 88, January 2016, Pages 613-627
Energy Policy

Time-varying convergence in European electricity spot markets and their association with carbon and fuel prices

https://doi.org/10.1016/j.enpol.2015.09.008Get rights and content

Highlights

  • Electricity market integration policies may have altered EU spot electricity prices.

  • LACF is used to assess the changing nature of electricity spot prices.

  • EU electricity spot prices show both stationary and non-stationary periods.

  • Carbon and fuel prices have greater impact on British spot prices.

  • In continental Europe, electricity prices have decoupled from fuel prices.

Abstract

Long-run dynamics of electricity prices are expected to reflect fuel price developments, since fuels generally account for a large share in the cost of generation. As an integrated European market for electricity develops, wholesale electricity prices should be converging as a result of market coupling and increased interconnectivity. Electricity mixes are also changing, spurred by a drive to significantly increase the share of renewables. Consequently, the electricity wholesale price dynamics are evolving, and the fuel–electricity price nexus that has been described in the literature is likely to reflect this evolution. This study investigates associations between spot prices from the British, French and Nordpool markets with those in connected electricity markets and fuel input prices, from December 2005 to October 2013. In order to assess the time-varying dynamics of electricity spot price series, localized autocorrelation functions are used. Electricity spot prices in the three markets are found to have stationary and non-stationary periods. When a trend in spot prices is observed, it is likely to reflect the trend in fuel prices. Cointegration analysis is then used to assess co-movement between electricity spot prices and fuel inputs to generation. The results show that British electricity spot prices are associated with fuel prices and not with price developments in connected markets, while the opposite is observed in the French and Nordpool day-ahead markets.

Introduction

In Europe, natural gas, coal and carbon prices have been found to be associated with electricity price movements (Aatola et al., 2013, Asche et al., 2006, Bollino et al., 2013, Castagneto-Gissey, 2014, Mjelde and Bessler, 2009), as the costs of generation are a large share of electricity prices. Most European states, however, have limited fossil fuel resources that can be used for electricity generation at the required scale. In recent years, concerns over the dependency on fuel imports have increased, despite growing shares of electricity from renewable energy sources (RES-E), as conventional back-up capacities are needed to secure supply. Depending on the strength of association between electricity and fuel prices, uncertainty about the latter could impair Europe's economic competitiveness, as the cost of electricity is an important input factor in almost every industry. In fact, electricity-intensive industries have already moved from the EU to regions where it is less costly (Reinaud, 2008).

In order to achieve cost-efficient electricity prices, a well-functioning internal European electricity market has been advocated. A pan-European electricity market implies regional integration, harmonization of trading rules, increased cross-border electricity transmission and trade (European Commission, 2013). Therefore, from the perspective of assessing electricity market integration in the EU, strong associations between fuel and electricity prices could affect electricity price convergence and vice versa.

The aim of this study is to link research on electricity market integration with studies of associations between electricity, fuel and carbon prices. A time-variant framework is adopted in order to understand dynamics that might have been neglected, possibly leading to the mixed findings reported in the literature. We examine long-run dynamics and convergence in three large European markets, where the reliance on fossil fuels for electricity generation varies: APX-UK (Britain), EPEX-FR (France) and Nordpool (Norway, Denmark, Sweden, Finland, Estonia, Latvia and Lithuania). Fig. 1 provides a summary of the electricity generation mix in these markets, as well as in Germany and Netherlands, whose markets are connected to at least two of the three main ones and are also considered in the analysis. A more detailed description of the generation mix is provided in Section 1.2.1. For assessing long-run dynamics, a two-stage analysis is developed: (1) stationary and non-stationary periods of electricity spot prices are identified via local autocorrelation functions (Cardinali and Nason, 2013), (2) convergence with fuel, carbon and other electricity markets is assessed in a cointegration analysis (Johansen, 1988, Johansen, 1991).

The paper is structured as follows. First, the literature on electricity market integration and assessments of fuel, carbon and electricity price associations is reviewed; the contextual framework is introduced, and the research question is outlined. Section 2 describes the methods and dataset used. Section 3 reports results, while findings are discussed in Section 4. Section 5 concludes the paper and outlines policy implications.

Within a growing literature on common long-run dynamics in energy markets, a subset of studies have focused on the integration of fossil fuel and electricity prices. In general, integration is demonstrated by establishing price convergence over time, which is then interpreted as efficiency gains obtained when the marginal costs of production are equal in different regions (Engle and Rogers, 2004). Related studies can be classified as follows: (1) investigations of electricity market integration, (2) assessments of electricity and fuel price convergence and (3) investigations of electricity and energy market integration. The next sub-sections review each category and their implications for the present investigation.

The Law of One Price (Fetter, 1924) has been the core theoretical foundation in assessing common long-run dynamics in liberalized electricity markets. Following the initial evaluations (Bower, 2002; Boisseleau, 2004), several studies (e.g. Armstrong and Galli, 2005; Boeckers and Heimeshoff, 2012; Bunn and Gianfreda, 2010; Robinson, 2008; Zachmann, 2008; Pellini, 2012) have examined electricity price convergence in the EU. Their assessments suggest decreasing price differences in several cases, greater convergence in peak-load periods (with the exception of Bunn and Gianfreda (2010)). Interconnection and geographical distances between markets were found to be crucial for price convergence. Yet, several authors concluded that the integration of European electricity markets has “still a way to go” (Pellini, 2012:1). However, most studies on electricity market integration neglected the potential relevance of the electricity generation mix, which could impact on convergence. Studies assessing relationships between electricity and fuel prices are therefore reviewed in the following section.

Since seminal evaluations by Serletis and Herbert (1999), several studies addressed the associations between generation fuels (such as natural gas, coal, crude oil and uranium) and electricity prices. For example, Brown and Yücel (2008), Emery and Liu (2002), Mjelde and Bessler (2009), Nakajima and Hamori (2013) and Woo et al. (2006) analyzed different U.S. markets and observed positive correlation between natural gas and electricity prices, which was also more pronounced during peak periods.

In the specific case of European markets, Asche et al. (2006) analyzed the British market and used cointegration analysis for monthly crude oil, natural gas and electricity wholesale prices in the period from 1995 to 2002. Interestingly, the authors found an integrated energy market only during 1995 to 1998, when the natural gas market was deregulated, but not yet physically linked to continental Europe by an interconnector. They inferred that prices could have decoupled in the second period, because of an incomplete regulatory structure or insufficient transmission capacity. Bollino et al. (2013) reasoned that even if from a physical viewpoint the possibility to exercise arbitrage is limited, it is conceivable that fuel price information available at the strategic decision center of a big multinational electricity generation company can be shared throughout its subsidiaries in different markets, thus stimulating market integration.

Moutinho et al. (2011) used daily prices from 2002 to 2005 and established cointegration between the Spanish electricity spot and natural gas prices, as well as for coal prices, but not for oil prices. By contrast, Furió and Chuliá (2012), using data from 2005 to 2011 found full integration of fuel (oil and natural gas) and electricity prices in the month-ahead market. Their findings support Munoz and Dickey's (2009) claim that natural gas, coal and oil, in this order, were the main components of Spanish electricity prices. Bencivenga et al. (2010) linked the research conducted in the US and the EU by comparing the associations between crude oil, natural gas and electricity prices in both markets. Using daily data from 2001 to 2009, their results suggest differences in convergence behavior. The authors concluded that despite the efforts of the European Commission, integration in the EU was lower than in the US and attributed their finding to incomplete deregulation in the European market, exercise of market power and self-governing gas price behavior.

Simpson and Abraham's (2012) study added to the literature by assessing electricity market and energy sector decoupling (regulation) versus convergence (deregulation/liberalization). They compared the electricity and energy markets in several countries within OECD, Latin America and Asia from 2000 to 2011. They reason that the strength of the integrating relationship between fuel and electricity prices should be indicative of greater progress of electricity market liberalization. Their results showed that larger economies, whether developed or undeveloped, demonstrated stronger relationships between fuel and electricity prices. Thus a greater degree of liberalization was due to less price manipulation through monopolies. In addition, they suggested that heavy use of renewable sources and their regulatory cost reduced convergence.

Together these studies demonstrate that associations between fuel and electricity prices are relevant for long-run dynamics in electricity prices, and should therefore be considered when assessing electricity market integration.

Among evaluations of electricity market integration, few researchers have addressed dependencies with fuel prices. For example, Kalantzis and Milonas' (2010) analysis of eight EU electricity spot markets between 2006 and 2009 concluded that rising oil prices indirectly exert a positive impact on price convergence, due to substitution with indigenous energy sources. This effect is more pronounced during off-peak hours, when the interconnection capacity was not fully utilized and congestion was less frequent.

Including renewables (wind electricity production and water reservoir levels) in their assessment of convergence between fuel and electricity prices, Ferkingstad et al. (2011) investigated dynamics between Nordpool and German electricity prices, major fuel sources (oil, natural gas and coal), from 2002 to 2008. Similar to single-market studies, their findings confirmed strong correlation between natural gas and electricity prices, whereas the price of coal did not play an important role. Bosco et al. (2010) found strong evidence of common long-run dynamics between electricity and natural gas prices in four European markets between 1999 and 2007. Bollino et al. (2013) could not find any association with oil prices, concluding instead that natural gas, the common marginal generation source, prevails in the determination of long-run relationships of electricity prices in the UK, Germany, Austria and France.

The introduction of the EU Emissions Trading Scheme (EU ETS) in 2005 marked an important change in EU energy policy. Several researchers (e.g. Fezzi and Bunn (2010), Sjim et al. (2006) and Pinho and Madaleno (2011)) analyzed how carbon costs are linked to electricity prices. Pinho and Madaleno (2011) used monthly data from 2005 to 2009 and examined associations between carbon, electricity and fuel prices in Germany, France and Nordpool by means of a Vector Error Correction Model. They found the impact of carbon prices to depend on the countries' energy mixes. Aatola et al. (2013) assessed the effect of carbon prices on the integration of European electricity markets using Granger causality, correlation and cointegration analysis. Comparing three sub-periods, their findings support the association with energy mixes, but also indicate that there is variation with time and plant technology. They observed that carbon prices had a positive but uneven effect on electricity market integration.

In summary, the reviewed literature mainly focuses on one aspect of price convergence either with prices in other electricity markets, or with generation input costs. Despite possible associations between these aspects, a link between the papers does not appear to have been formally established. Since assessments of electricity market integration found more convergence during peak-load periods, when conventional gas/coal generation are likely to be needed, some convergence of electricity wholesale prices could therefore have been driven indirectly by fuel prices.1

Furthermore, the findings reported above indicate that convergence should be time-varying, as associations depend on the local electricity mix, the degree of regulation and the size of the market. Cointegration analysis was broadly applied to assess convergence and was at most employed to three sub-periods to capture changes in time (Aatola et al., 2013). Cointegration analysis requires non-stationarity of the time series; in order to meet this criterion researchers either aggregated the data (e.g. Bosco et al. (2010), Ferkingstad et al. (2011) and Mjelde and Bessler (2009)) or employed price indices, such as consumer prices (e.g. Simpson and Abraham (2012)). The present study addresses potential implications for and from electricity market integration that have been neglected in earlier assessments, in a time-varying framework.

The local electricity mix is likely to be relevant for electricity market integration because of the price setting mechanism and the possibility for arbitrage in case of complementary generation portfolios (Teusch, 2012). The bid of a conventional electricity generator to the exchange reflects the variable cost of the fuel that is used for production and the carbon price. This is the case even if the allowances are granted for free as they represent opportunity costs (Sjim et al., 2006).

The system operator dispatches the generators with the lowest marginal generation cost and then moves up the dispatch curve, calling on generators with higher marginal costs until demand is satisfied. Thus, if there were no constraints in transmission lines, the electricity spot price is set by the marginal producer. In a cost-reflective market, input prices in electricity generation should at least be partially reflected in electricity prices and, for markets with a large share of a specific marginal fuel in its electricity mix, associations are expected to be stronger (Furió and Chuliá, 2012).

Fig. 1 and Table 1 present gross electricity generation between 2005 and 2012 in the five markets (France, Britain, Germany, Nordpool and the Netherlands) considered here. The French electricity mix is characterized by the highest share of nuclear generation among these markets. The share fluctuated between 76% and 80% between 2005 and 2012. In 2012, 11% of the domestic electricity was generated by hydro, 4% by gas, followed by wind and coal-generated electricity (3% each). In Britain, large but declining quantities of gas were used to generate electricity between 2005 and 2012. The share of coal on the other hand increased from 30% in 2011 to 40% in 2012. Nuclear generation contributed around one fifth of gross electricity output between 2005 and 2012. The largest component in the German electricity mix is coal, with a share of 45% in 2012. More than 16% of the local electricity mix in 2012 consisted of nuclear, which declined from 167 TWh in 2006 to 100 TWh in 2012. This decrease is due to the implementation of Atomgesetz.2 The implementation of EEG3 (Renewable Energy Sources Act) in 2000 has led to rapid growth in renewables, especially biomass, photovoltaics and wind.

Nordpool has a large share of seasonal hydro-generated electricity, about 130 TWh hydro capacity, of which 63% is installed in Norway, 26% in Sweden and 11% in Finland (NordpoolSpot, 2013).In the Netherlands, gas and coal have the highest shares in the local electricity mix, which vary over time.

In summary, we observe changing electricity mixes and significant differences across countries, reflecting local and EU energy policies that aim at decarbonizing the electricity sector and increasing the share of RES-E.

In addition to decarbonizing the electric system, some electricity markets have become integrated via coupling, which is the use of implicit auctioning involving two or more power exchanges. For example, the Trilateral Market Coupling couples the Belgian, Dutch and French electricity markets since November 2006. The Interim Tight Volume Coupling links the Belgian, Dutch, French and German electricity markets with Nordpool since November 2010. The British market, though interconnected with three other markets, was not coupled to any other European market in the period covered by this study.

Different levels of interconnectivity are also reflected in Fig. 2, where the ratio of imports to total electricity generation and exports to total electricity generation from 2005 to 2012 are depicted. The Netherlands is a major electricity transit country and this can be seen in the values of import and export shares of the total Dutch electricity generation, which reached almost 32% and 15% respectively. In the German and Nordpool markets, imports and exports fluctuated around 10% of the overall generated electricity between 2005 and 2012. In France, exports ranged between 9% and 13% in the same period, however imports were much smaller with the highest value of only 4% in 2009 and 2010. The British market stands out as the one with the lowest shares of imports and exports expressed as a share of total domestic electricity generation: exports were less than 1% and imports at most 3% between 2005 and 2012.

Electricity spot prices have often been found to be stationary mean-reverting processes (e.g. Escribano et al. (2002), Haldrup and Nielsen (2006), De Jong and Huisman (2002) and Huisman and Mahieu (2003)), unlike most fuel price series that tend to follow trends. Mean reversion implies stationarity. With each successive movement away from the long-run average, the likelihood that the next price movement will be toward the average increases (Marshall, 2000). One aim of electricity market integration is to increase the speed of mean reversion of prices, which would indicate greater market resilience against unexpected supply or demand shocks. A quick speed of mean reversion or strong stationary behavior implies robustness and flexibility of the electric system, in the sense that additional capacities are brought online quickly and prices revert to their normal levels as expensive plants are swiftly replaced. By contrast, persistent prices indicate that shocks are less easily overcome.

Any assessment of price convergence via standard cointegration analysis (Johansen, 1988, Johansen, 1991), requires that the time series are at least integrated of order one (I(1)). This long-run price behavior contradicts the aim of electricity market integration, which implies faster mean reversion. With increasing market integration, long-run behaviors of electricity spot prices could be changing: from non-stationarity due to associations with mainly non-stationary fuel prices towards increasing periods of mean-reversion facilitated by the availability of local and neighbor market capacities.

All in all, the differences in local electricity mixes and cross-border flows suggest that fuel, carbon and electricity prices in neighboring markets may differ in relevance for price dynamics and convergence in the markets described. This study therefore revisits the question “How do fuel and carbon prices associate with electricity prices?”, within the context of the integration of electricity markets and, therefore, attempts to link the different streams of literature.

Section snippets

Analysis procedure

Prior to the empirical analysis, outliers are replaced with the average over a four-week period. An outlier is defined as a value exceeding three standard deviations of the mean average over a four-week window. The time series behavior is then summarized and assessed for stationarity and trends, via unit root tests and estimates of the order of integration. The methods are described in Section 2.1.1. Serial correlation of the electricity spot price time series are examined via estimates of the

Tests for integration and fractional integration

The p-values of the PP and ADF unit root tests are reported in rows two to five of Table 2 for each time series and its first difference. The optimal lag lengths l used in the tests are reported in brackets behind the test statistics. The tests for the series strongly reject the hypothesis of a unit root for all electricity base- and peak-load as well as natural gas prices. The coal and carbon price series, on the other hand, are non-stationary since their p-value is larger than.05. The ADF and

Discussion

In the first part of the analysis, whilst electricity spot and natural gas prices were found to be fractionally integrated mean reverting processes in the long-run, coal and carbon prices follow trends. The LACF estimates confirmed that electricity spot prices in the three markets (Britain, Nordpool and France) are time-varying processes. Periods that appeared highly persistent were tested for a local trend; peak- and base-load price periods are similar in all three markets. LACF estimates are

Conclusion and policy implications

Our results showed that electricity spot prices in all markets have a time-varying behavior, with periods of longer mean reversion, during which there may be stronger associations with fuel and carbon prices. In addition, where there is stronger interconnection or market coupling, there is greater association with neighboring markets for some periods. Consequently, local electricity mix and market integration are relevant for spot price formation. The results support the reasoning that Europe's

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