Cycles in deregulated electricity markets: Empirical evidence from two decades

In this article, we discuss the “cycle hypothesis” in electricity generation, which states that the introduction of deregulation in an electricity system might lead to sustained fluctuations of over- and under-capacity. The occurrence of cycles is one of the major threats for electricity markets as it affects the security of supply, and creates uncertainty in both the profitability of electricity companies and in consumer prices. We discuss the background for these cycles using analogies with other capital-intensive industries, along with evidence from the analysis of behavioral simulation models as well as from experimental electricity markets. Using data from the oldest deregulated markets we find support for the hypothesis in the case of the English and Chilean markets, based on an autocorrelation analysis. Evidence from the Nordpool market is more ambiguous, although we might be observing the first half of a cycle in generation capacity. Comparing a simulation of the English market performed in 1992 with the actual performance we can observe that the qualitative behavior of the model is consistent with the actual evolution. Finally, we discuss possible mechanisms for damping cycles in electricity generation, such as mothballing, capacity payments, and reliability markets.     

The potential of demand-side management in energy-intensive industries for electricity markets in Germany

This paper investigates the technical and economic potential of energy-intensive industries to provide demand-side management (DSM) in electricity and balancing markets through 2030. Increasing shares of renewables will lead to a rising demand for ancillary services at the same time that less conventional plants will be available to provide these services. This paper makes projections on the extent to which DSM from industrial processes can provide economic benefits in electricity markets with renewables by providing tertiary reserve capacity. Different industrial processes and their specific technical and economic properties are investigated and compared with other storage devices and electricity generation technologies. Based on an extension of an existing European electricity market model, simulations are used here to make long-term forecasts for market prices, dispatch and investments in the electricity markets through linear optimization.     

Elecxit: The cost of bilaterally uncoupling British-EU electricity trade

The UK's withdrawal from the European Union could mean that it leaves the EU's Internal Energy Market for electricity (Elecxit). This paper develops methods to study the longer-term consequences of this electricity market disintegration, especially the end of market coupling. Before European electricity markets were coupled, different market closing times forced traders to commit to cross-border trading volumes based on anticipated market prices. Interconnector capacity was often under-used, and power sometimes flowed from high- to low-price areas. A model of these market frictions is developed, empirically verified on 2009 data (before French and British market coupling) and applied to estimate the costs of market uncoupling in 2030. A less efficient market and the abandonment of some planned interconnectors would raise generation costs by €700 m a year (2%) compared to remaining in the Internal Energy Market. This result is sensitive to how the British and French electricity systems develop over the coming decades. Economic losses are four times greater (€2700 m a year) if France retains substantial nuclear capacity due to its low marginal costs. Conversely, losses are reduced by two-thirds if UK weakens its decarbonisation ambitions, as lower carbon prices subsidise British fossil fuel generation, allowing electricity prices to converge with those in France. A Hard Elecxit would make British prices rise and French prices fall in three of our four scenarios, with the opposite movements in the fourth scenario.     

Statistical analysis of negative prices in European balancing markets

The presence of renewable power generation technologies increases the need for system flexibility due to their variable nature. The increasing share of variable renewables in European power systems create a downward adequacy problem, which deals with the ability of power systems to cope with periods of excess generation. The occurrence of negative prices on Central Western European electricity markets confirms the relevance of this issue, which is referred to as “incompressibility of power systems” and is assessed as a barrier for further renewable power integration. The objective of this article is to identify the main drivers of negative price periods in European balancing markets, by means of both an empirical and regression analysis. Results confirm a positive relation with the scheduled generation of renewables and inflexible base load, as well as a negative relation with the scheduled system load. Furthermore, the occurrence of negative prices is related to the positive and negative forecast error of renewable generation and demand, respectively. It is concluded that negative balancing market prices provide a market signal for investments in flexibility sources such as flexible generation, demand response, electricity storage, and interconnector capacity.     

Dynamic model for market-based capacity investment decision considering stochastic characteristic of wind power

This paper proposes a decentralized market-based model for long-term capacity investment decisions in a liberalized electricity market with significant wind power generation. In such an environment, investment and construction decisions are based on price signal feedbacks and imperfect foresight of future conditions in electricity market. System dynamics concepts are used to model structural characteristics of power market such as, long-term firms’ behavior and relationships between variables, feedbacks and time delays. For conventional generation units, short-term price feedback for generation dispatching of forward market is implemented as well as long-term price expectation for profitability assessment in capacity investment. For wind power generation, a special framework is proposed in which generation firms are committed depending on the statistical nature of wind power. The method is based on the time series stochastic simulation process for prediction of wind speed using historical and probabilistic data. The auto-correlation nature of wind speed and the correlation with demand fluctuations are modeled appropriately. The Monte Carlo simulation technique is employed to assess the effect of demand growth rate and wind power uncertainties. Such a decision model enables the companies to find out the possible consequences of their different investment decisions. Different regulatory policies and market conditions can also be assessed by ISOs and regulators to check the performance of market rules. A case study is presented exhibiting the effectiveness of the proposed model for capacity expansion of electricity markets in which the market prices and the generation capacities are fluctuating due to uncertainty of wind power generation.     

The future developments of the electricity prices in view of the implementation of the Paris Agreements: Will the current trends prevail,or a reversal is ahead?

We assess the impact on the European electricity market of the European Union “Clean energy for all Europeans” package, which implements the EU Nationally Determined Contribution in Paris COP 21. We focus on the year 2030, which is the year with defined climate targets. For the assessment, we employ a game-theoretic framework of the wholesale electricity market, with high technical detail. The model is applied to two core scenarios, a Base scenario and a Low Carbon scenario to provide insights regarding the future electricity capacity, generation mix, cross-border trade and electricity prices. We also assess three additional variants of the core scenarios concerning different levels of: a) fossil and CO₂ prices; b) additional flexibility provided by batteries; c) market integration. We find that the electricity prices in 2030 substantially increase from today's level, driven by the increase in fuel and CO₂ prices. The flexibility from batteries helps in mitigating the price peaks and the price volatility. The increased low marginal cost electricity generation, the expansion of non-dispatchable and distributed capacities, and the higher market integration further reduce the market power from producers in the electricity markets from today's level.     

Germany's nuclear power plant closures and the integration of electricity markets in Europe

This paper examines the potential implications of national policies that lead to a sudden increase of wind power in the electricity mix for interconnected European electricity markets. More specifically, it examines market integration before and after the closures of eight nuclear power plants that occurred within a period of a few months in Germany during 2011. The short- and- long run interrelationships of daily electricity spot prices, from November 2009 to October 2012, in: APX-ENDEX, BELPEX, EPEX-DE, EPEX-FR, NORDPOOL, OMEL and SWISSIX; and wind power in the German system are analysed. Two MGARCH (Multivariate Generalized Autoregressive Conditional Heteroscedasticity) models with dynamic correlations are used to assess spot market behaviour in the short run, and a fractional cointegration analysis is conducted to investigate changes in the long-run behaviour of electricity spot prices. Results show: positive time-varying correlations between spot prices in markets with substantial shared interconnector capacity; a negative association between wind power penetration in Germany and electricity spot prices in the German and neighbouring markets; and, for most markets, a decreasing speed in mean reversion.     

Market power in the European electricity market—The impacts of dry weather and additional transmission capacity

This paper uses a static computational game theoretic model of a fully opened European electricity market and can take strategic interaction among electricity-producing firms into account. The model is run for a number of scenarios: first, in the baseline under perfect competition, the prices differ due to the presence of various generation technologies and a limited ability to exchange electricity among countries. In addition, when large firms exercise market power, the model runs indicate that prices are the highest in countries where the number of firms is low. Second, dry weather would increase the prices in the hydro-rich Nordic countries followed by the Alpine countries. The price response would be about 20% higher with market power. Third, more transmission capacity would lower the prices in countries with high prices and it also reduces the impact of market power. Hence, more transmission capacity can improve market competitiveness.     

Financial optimization in the Turkish electricity market: Markowitz's mean-variance approach

Electricity constitutes the input into many products that produced by industry and used by people. Hence, it can be considered as a product or service that has vital importance in human life and economy. Since it has such special properties of instantaneous production and consumption obligation and unfeasible storage, electricity market is not like other markets. In a competitive electricity market, generation company faces price risks and delivery risks. So that risk management is an important part of a generation company and can deeply effect companies’ profitability. This paper focuses on electricity generation asset allocation between bilateral contracts, such as forward contracts, and daily spot market, considering constraints of generating units and spot price risks. The problem is to find the optimal portfolio based on known electricity generation total costs, bilateral contract prices, it employed Turkish historical balanced market hourly system marginal and day-ahead hourly market prices between of 2006 and 2011. There are limited studies about portfolio optimization in electricity markets in literature and this paper should be considered frontier study taking spot market's hourly prices separately as risky assets. Markowitz mean-variance optimization which is claimed to be the beginning of modern portfolio theory in financial sector is used to demonstrate this approach. Mean-variance optimization has been successfully applied to all cases that modeled for electricity market. Some suggestions for future work are also listed in this paper.     

Cross-border effects in interconnected electricity markets - an analysis of the Swiss electricity prices

Electricity markets in Europe become increasingly interconnected due to new grid connections and market coupling regulations. This paper examines the interdependencies between the Swiss electricity market and those of neighbouring countries. The Swiss market serves as a good example for a smaller electricity market which is increasingly affected by developments in the large neighbouring countries. To study these cross-border effects, especially those on Swiss electricity prices, we apply two different methodologies, an econometric and a Nash-Cournot equilibrium model.The analyses show that the Swiss electricity price correlates strongly with the German electricity price in the summer, but tends to follow the French electricity price in the winter. Another finding is that gas prices and the electricity load of neighbouring countries have a significant influence on prices. In particular, the load of France and Italy is driving up Swiss prices in the winter, while the German electricity demand and renewable energy generation have a larger influence on Swiss prices in the summer.     

Grid parity analysis of solar photovoltaic systems in Germany using experience curves

The paper starts with experience curve analysis in order to find out the future prices of solar photovoltaic (PV) modules. Experience curves for 75-90% progress ratio are extrapolated with the help of estimated future growth rate for PV installation worldwide and current module price data until year 2060. A kWh PV electricity generation cost has been calculated for coming decades with the help of local market parameters and module prices data from extrapolated experience curve. Two different prices for grid electricity - wholesale electricity price and end user electricity price - are separately analyzed. Household electricity consumption profile and PV electricity generation profile for Cologne, Germany, have been analyzed to find out the possibility for PV electricity consumption at the time of its generation. This result is used to calculate the real grid parity year - which lies somewhere between grid parity years calculated for wholesale electricity price and end user electricity price.     

Electricity market price volatility: The case of Ontario

Price volatility analysis has been reported in the literature for most competitive electricity markets around the world. However, no studies have been published yet that quantify price volatility in the Ontario electricity market, which is the focus of the present paper. In this paper, a comparative volatility analysis is conducted for the Ontario market and its neighboring electricity markets. Volatility indices are developed based on historical volatility and price velocity concepts, previously applied to other electricity market prices, and employed in the present work. The analysis is carried out in two scenarios: in the first scenario, the volatility indices are determined for the entire price time series. In the second scenario, the price time series are broken up into 24 time series for each of the 24 h and volatility indices are calculated for each specific hour separately. The volatility indices are also applied to the locational marginal prices of several pricing points in the New England, New York, and PJM electricity markets. The outcomes reveal that price volatility is significantly higher in Ontario than the three studied neighboring electricity markets. Furthermore, comparison of the results of this study with similar findings previously published for 15 other electricity markets demonstrates that the Ontario electricity market is one of the most volatile electricity markets world-wide. This high volatility is argued to be associated with the fact that Ontario is a single-settlement, real-time market.     

Integrating Real Options Analysis with long-term electricity market models

In liberalized electricity markets, the investment postponement option is deemed decisive for understanding the addition of new generating capacity. Basically, it refers to the possibility for investors to postpone projects for a period while waiting for the arrival of new and better information about the market evolution. When such development involves major uncertainties, the generation business becomes riskier, and the investors' “wait-and-see” behavior might limit the timely addition of new power plants. In that sense, the literature provides solid empirical evidence about the occurrence of construction cycles in the deregulated electricity industry. However, the strategic flexibility inherent to the option to defer new power plants has not yet been rigorously incorporated to investment signals in existing market models. Therefore, this paper proposes a novel methodology to assess the long-term development of liberalized power markets based on a more realistic approach for valuing generation investments. The work is based on a stochastic dynamic market model, built upon System Dynamics simulation approach. The decision-making framework considers that the addition of new capacity is driven by the economic value of the strategic flexibility associated with deferring investments under uncertainties. Thus, the value of the postponement option is quantified in monetary terms through Real Options Analysis. Simulations confirm the cyclical behavior of the energy-only market in the long run, as suggested by the empirical evidence found in the literature. In addition, sensitivity analysis regarding some relevant exogenous variables depicts an even more fluctuating evolution of the capacity due to the combination of strong demand growth rates with large volatilities. Finally, the model validity is assessed through a formal procedure according to the scope of System Dynamics modeling approach.     

Modeling long-term dynamics of electricity markets

In the last decade, many countries have restructured their electricity industries by introducing competition in their power generation sectors. Although some restructuring has been regarded as successful, the short experience accumulated with liberalized power markets does not allow making any founded assertion about their long-term behavior. Long-term prices and long-term supply reliability are now center of interest. This concerns firms considering investments in generation capacity and regulatory authorities interested in assuring the long-term supply adequacy and the stability of power markets. In order to gain significant insight into the long-term behavior of liberalized power markets, in this paper, a simulation model based on system dynamics is proposed and the underlying mathematical formulations extensively discussed. Unlike classical market models based on the assumption that market outcomes replicate the results of a centrally made optimization, the approach presented here focuses on replicating the system structure of power markets and the logic of relationships among system components in order to derive its dynamical response. The simulations suggest that there might be serious problems to adjust early enough the generation capacity necessary to maintain stable reserve margins, and consequently, stable long-term price levels. Because of feedback loops embedded in the structure of power markets and the existence of some time lags, the long-term market development might exhibit a quite volatile behavior. By varying some exogenous inputs, a sensitivity analysis is carried out to assess the influence of these factors on the long-run market dynamics.     

Economic and environmental implications of different approaches to hedge against wind production uncertainty in two-settlement electricity markets: A PJM case study

This paper examines the economic and environmental outcomes of four two-settlement electricity market clearing designs. The first design corresponds to a Deterministic Market Clearing (DMC) similar to the mechanism currently used in organized wholesale electricity markets in the United States. The other three designs account for the day-ahead (DA) wind power production uncertainty into the DA market mechanisms either implicitly or explicitly. An Augmented Deterministic Market Clearing (ADMC) design introduces DA ramp-capability products. These products ensure adequate and ramp-feasible electricity generation capacity commitments in the DA stage to cope with the real-time realization of wind power generation. A Hybrid Deterministic Market clearing (HDMC) design augments ADMC by explicitly integrating a characterization of wind power production uncertainty into the residual unit commitment (RUC) process, which is run after the DA market is closed, using stochastic programming. The last design, referred to as stochastic market clearing (SMC), uses stochastic optimization to explicitly account for wind power production uncertainty in the DA market clearing mechanisms (i.e. DA unit commitment and economic dispatch).The four market clearing designs are assessed by simulating the electricity market operations of a test system and comparing their results in terms of operating costs, prices, costs and revenues of different types of producers, consumer's payments, integration of wind power, and air emissions. The test system has 12% of the capacity of PJM's fossil-fired power generation fleet, and uses data on coincident demand and wind power production from the Bonneville Power Administration (BPA) system during years 2010–2014. The simulations are performed hourly for a whole year.Results show that SMC is superior as its costs reductions are more than two times the improvements attained by ADMC and HDMC. Also, SMC results in electricity prices that are better aligned with operation costs, cuts the spread between the day-ahead and real-time prices by >40%, reduces out-of-market short-term revenue sufficiency payments by 58%, reduces CO₂ emissions by 3.52%, and decreases power plants' cycling. HDMC is a distant second-best market design. Relative to DMC, it achieves a reduction in total costs that is less than half the reduction achieved by SMC, a reduction in out-of-market payments that is 80% of the reduction attained by SMC, and an increase in wind power integration that is <10% the improvement obtained under SMC.     

Electricity markets for energy,flexibility and availability — Impact of capacity mechanisms on the remuneration of generation technologies

Increased shares of Renewable Energy Sources (RES) to fulfill ambitious European policy targets, mothballing or decommissioning of existing units, and absent investments lead to concerns about the system and market adequacy. To restore market adequacy, capacity mechanisms (CMs) are widely discussed and implemented in various types. They are intended to provide sufficient and clearly perceivable long-term price signals for available capacity. As integral part of the market, CMs interact with the other markets. Markets like day-ahead markets are used to trade energy. Imbalance markets or reserve requirements are examples for markets for flexibility. Among others, green certificates are in place to value emission-neutral injection from RES. Resulting altered prices and shifting remuneration have effects on all generation technologies. CMs may affect participating technologies by imposing a capacity demand. A resulting change in the generation mix may also have an impact on non-participating technologies. Two gaps can be identified in the discussion and modeling of CMs in the literature. First, proposed game-theoretic equilibrium models fall short in representing the distinctive features of different types of CMs. Second, most models incorporating CMs found in the literature only focus on the interaction with the energy-based market. Valid assessments of CM need to consider the interaction of remuneration for available capacity and flexibility, and the indirect interaction with the remuneration for emission-neutral RES. Two formulations of a game-theoretic market equilibrium model are proposed which represent specific CMs with its distinctive features, in particular a market-wide centralized capacity market (cCM) and targeted strategic reserves (SRs). Moreover, the equilibrium models explicitly combine the CMs with markets for flexibility and indirect with remuneration for RES. We contribute to the discussion of CMs by quantifying the interactions and shifting shares of remuneration. Based on the interaction between CMs and remuneration for emission-neutral injection, the effect of CMs on non-participating RES is described. We conclude based on the case study results that targeted mechanisms, like SRs, implemented with the single purpose of ensuring availability introduce large inefficiencies in the system by missing on the interaction between availability and flexibility. In contrast, a market-wide cCM provides a beneficial outcome for all technologies. At the same time, it yields a sufficient high reserve margin at lowest cost. It provides clear signals for the different values of energy-output, flexibility, availability and emission-neutral injection.     

On the long run effects of market splitting: Why more price zones might decrease welfare

In liberalized electricity markets we observe different approaches to congestion management. While nodal pricing is implemented in Canada and some markets in the United States, European markets are split up into a limited number of price zones with uniform prices, in order to at least partially realize the benefits of regional price differentiation. Zonal boundaries often coincide with national borders, but some countries are also split into multiple zones. In this paper we shed light on possible negative welfare effects of market splitting that arise in a model where investment incentives in new generation capacity are taken into account if zones are misspecified. We show that standard approaches to configure price zones – on the basis of projected nodal price differences or congested transmission capacity – may fail to suggest reasonable zone specifications. Also an adjustment of Available Transfer Capacities (ATCs) between zones or a switch to flow-based market splitting does not ensure positive welfare effects. Our analysis suggests that a careful and detailed evaluation of the system is needed to ensure a reasonable zone configuration.     

Optimal generation and reserve dispatch in a multi-area competitive market using a hybrid direct search method

With restructuring of the power industry, competitive bidding for energy and ancillary services are increasingly recognized as an important part of electricity markets. It is desirable to optimize not only the generator’s bid prices for energy and for providing minimized ancillary services but also the transmission congestion costs. In this paper, a hybrid approach of combining sequential dispatch with a direct search method is developed to deal with the multi-product and multi-area electricity market dispatch problem. The hybrid direct search method (HDSM) incorporates sequential dispatch into the direct search method to facilitate economic sharing of generation and reserve across areas and to minimize the total market cost in a multi-area competitive electricity market. The effects of tie line congestion and area spinning reserve requirement are also consistently reflected in the marginal price in each area. Numerical experiments are included to understand the various constraints in the market cost analysis and to provide valuable information for market participants in a pool oriented electricity market.     

Did residential electricity rates fall after retail competition? A dynamic panel analysis

A key selling point for the restructuring of electricity markets was the promise of lower prices. There is not much consensus in earlier studies on the effects of electricity deregulation in the U.S., particularly for residential customers. Part of the reason for not finding a consistent link with deregulation and lower prices was that the removal of transitional price caps led to higher prices. In addition, the timing of the removal of price caps coincided with rising fuel prices, which were passed on to consumers in a competitive market. Using a dynamic panel model, we analyze the effect of participation rates, fuel costs, market size, a rate cap and switch to competition for 16 states and the District of Columbia. We find that an increase in participation rates, price controls, a larger market, and high shares of hydro in electricity generation lower retail prices, while increases in natural gas and coal prices increase rates. We also find that retail competition makes the market more efficient by lowering the markup of retail prices over wholesale costs. The effects of a competitive retail electricity market are mixed across states, but generally appear to lower prices in states with high participation rates.     

How does market power affect the impact of large scale wind investment in 'energy only' wholesale electricity markets?

In the short run, it is well known that increasing wind penetration is likely to reduce spot market electricity prices due to the merit order effect. The long run effect is less clear because there will be a change in new capacity investment in response to the wind penetration. In this paper we examine the interaction between capacity investment, wind penetration and market power by first using a least-cost generation expansion model to simulate capacity investment with increasing amounts of wind generation, and then using a computer agent-based model to predict electricity prices in the presence of market power. We find the degree to which firms are able to exercise market power depends critically on the ratio of capacity to peak demand. For our preferred long run generation scenario we show market power increases for some periods as wind penetration increases however the merit order counteracts this with the results that prices overall remain flat. Returns to peakers increase significantly as wind penetration increases. The market power in turn leads to inefficient dispatch which is exacerbated with large amounts of wind generation.