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.     

The impact of the North Atlantic Oscillation on electricity markets: A case study on Ireland

The North Atlantic Oscillation (NAO) is a large-scale atmospheric circulation pattern driving climate variability in north-western Europe. As the deployment of wind-powered generation expands on electricity networks across Europe, the impacts of the NAO on the electricity system will be amplified. This study assesses the impact of the NAO, via wind-power generation, on the electricity market considering thermal generation costs, wholesale electricity prices and wind generation subsidies. A Monte Carlo approach is used to model NAO phases and generate hourly wind speed time-series data, electricity demand and fuel input data. A least-cost unit commitment and economic dispatch model is used to simulate an island electricity system, modelled on the all-island Irish electricity system. The impact of the NAO obviously depends on the level of wind capacity within an electricity system. Our results indicate that on average a switch from negative to positive NAO phase can reduce thermal generation costs by up to 8%, reduce wholesale electricity prices by as much as €1.5/MWh, and increase wind power generators' revenue by 12%.     

The plunge in German electricity futures prices – Analysis using a parsimonious fundamental model

The German market has seen a plunge in wholesale electricity prices from 2007 until 2014, with base futures prices dropping by more than 40%. This is frequently attributed to the unexpected high increase in renewable power generation. Using a parsimonious fundamental model, we determine the respective impact of supply and demand shocks on electricity futures prices. The used methodology is based on a piecewise linear approximation of the supply stack and time-varying price-inelastic demand. This parsimonious model is able to replicate electricity futures prices and discover non-linear dependencies in futures price formation. We show that emission prices have a higher impact on power prices than renewable penetration. Changes in renewables, demand and installed capacities turn out to be similarly important for explaining the decrease in operation margins of conventional power plants. We thus argue for the establishment of an independent authority to stabilize emission prices.     

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.     

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.     

High penetration wind generation impacts on spot prices in the Australian national electricity market

This paper explores wind power integration issues for the South Australian (SA) region of the Australian National Electricity Market (NEM) by assessing the interaction of regional wind generation, electricity demand and spot prices over 2 recent years of market operation. SA's wind energy penetration has recently surpassed 20% and it has only a limited interconnection with other regions of the NEM. As such, it represents an interesting example of high wind penetration in a gross wholesale pool market electricity industry. Our findings suggest that while electricity demand continues to have the greatest influence on spot prices in SA, wind generation levels have become a significant secondary influence, and there is an inverse relationship between wind generation and price. No clear relationship between wind generation and demand has been identified although some periods of extremely high demand may coincide with lower wind generation. Periods of high wind output are associated with generally lower market prices, and also appear to contribute to extreme negative price events. The results highlight the importance of electricity market and renewable policy design in facilitating economically efficient high wind penetrations.     

Electricity wholesale market prices in Europe: Convergence?

This paper tests the hypothesis that the ongoing restructuring process in the European electricity sector has led to a common European market for electricity. Based on a Principal Component Analysis (PCA) of wholesale electricity prices in 2002–2006, we reject the assumption of full market integration. For several pairs of countries, the weaker hypothesis of (bilateral) convergence is accepted based on unit root tests (KPSS and ADF) and a convergence test based on filtered pairwise price relations. This indicates that the efforts to develop a single European market for electricity were so far only partially successful. We show that the daily auction prices of scarce cross-border transmission capacities are insufficient to explain the persistence of international price differentials. Empirically, our findings confirm the insufficiency of explicit capacity auctions as stated in the theoretical literature.     

Optimized Integration of Renewable Energy Technologies Into Jordan's Power Plant Portfolio

Jordan has experienced a significant increase of peak load and annual electricity demand within the last years due to economic development and population growth. The experienced growth rates are expected to continue during the next decades, making large investments in new power plant capacity necessary. Additionally, when gas supply from Egypt was interrupted several times and crude oil world market prices increased simultaneously, recent years have shown painfully that a power supply exclusively based on fossil fuel imports is subject to a very high risk and can have a strong negative impact on the national budget. Electricity-sector authorities are therefore looking for suitable solutions to keep up with the increasing electricity demand, to make Jordan more independent from fossil fuel imports, and to provide electricity at reasonable prices in the future. This paper presents a methodology for the optimized integration of renewable energy (RE) technologies into Jordan's existing power plant portfolio. The core of the methodology is the mixed integer linear optimization program REMix-CEM, developed at the German Aerospace Center (DLR), which optimizes capacity expansion and unit commitment of RE and conventional power generation technologies simultaneously. After describing Jordan's electricity sector and the available RE resources, the developed methodology and the results are presented. The paper shows that by the year 2022, Jordan could generate at least 47% of its electricity demand by a well-balanced mix of concentrating solar power, utility-scale photovoltaics, and onshore wind power. This scenario would maintain the security of electricity supply, absorb present growth rates of power generation costs, and make Jordan significantly more independent of fossil fuel imports.     

Market integration among electricity markets and their major fuel source markets

Dynamic price information flows among U.S. electricity wholesale spot prices and the prices of the major electricity generation fuel sources, natural gas, uranium, coal, and crude oil, are studied. Multivariate time series methods applied to weekly price data show that in contemporaneous time peak electricity prices move natural gas prices, which in turn influence crude oil. In the long run, price is discovered in the fuel sources market (except uranium), as these prices are weakly exogenous in a reduced rank regression representation of these energy prices.     

Do producers apply a capacity cutting strategy to increase prices? The case of the England and Wales electricity market

Promoting competition among electricity producers is primarily targeted at ensuring fair electricity prices for consumers. Producers could, however, withhold part of production facilities (i.e., apply a capacity cutting strategy) and thereby push more expensive production facilities to satisfy demand for electricity. This behavior could lead to a higher price determined through a uniform price auction. Using the case of the England and Wales wholesale electricity market we empirically analyze whether producers indeed did apply a capacity cutting strategy. For this purpose we examine the bidding behavior of producers during high- and low-demand trading periods within a trading day. We find statistical evidence for the presence of capacity cutting by several producers, which is consistent with the regulatory authority's reports.     

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.     

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.     

The cannibalization effect of wind and solar in the California wholesale electricity market

Increasing penetration of zero marginal cost variable renewable technologies cause the decline of wholesale electricity prices due to the merit-order effect. This causes a “cannibalization effect” through which increasing renewable technologies’ penetration undermines their own value. We calculate solar and wind daily unit revenues (generation weighted electricity prices) and value factors (unit revenues divided by average electricity prices) from hourly data of the day-ahead California wholesale electricity market (CAISO) for the period January 2013 to June 2017. We then perform a time series econometric analysis to test the absolute (unit revenues) and relative (value factors) cannibalization effect of solar and wind technologies, as well as the cross-cannibalization effects between technologies. We find both absolute and relative cannibalization effect for both solar and wind, but while wind penetration reduces the value factor of solar, solar penetration increases wind value factor, at least at high penetration and low consumption levels. We explore non-linearities and also find that the cannibalization effect is stronger at low consumption and high wind/solar penetration levels. This entails that wind and (mainly) solar competitiveness could be jeopardized unless additional mitigation measures such as storage, demand management or intercontinental interconnections are taken.     

Vertical integration and market power: A model-based analysis of restructuring in the Korean electricity market

An agent-based simulation model is developed using computational learning to investigate the impact of vertical integration between electricity generators and retailers on market power in a competitive wholesale market setting. It is observed that if partial vertical integration creates some market foreclosure, whether this leads to an increase or decrease in market power is situation specific. A detailed application to the Korean market structure reveals this to be the case. We find that in various cases, whilst vertical integration generally reduces spot prices, it can increase or decrease the market power of other market generators, depending upon the market share and the technology segment of the market, which is integrated, as well as the market concentrations before and after the integration.     

Storage and Demand Side Management as power generator’s strategic instruments to influence demand and prices

Classic storage utilisation is mainly based on charging/discharging strategies enabling a power generation company to generate revenues by buying electricity in low-price periods and selling it at higher prices. Within this paper another feasible way to gain arbitrage in storage utilisation is considered: Strategically increasing demand disregarding existing market prices. This means, charging electricity for storage is not only bought in low price periods, but in all periods where storage charging could influence demand so that market prices increase. This idea is expanded by focussing on another frequently discussed topic which could serve utilities for the same purpose: Automated Demand Side Management (DSM). By using data from Ontario’s electricity market and applying a particular storage and DSM strategy it is analysed to which extent a non-regulated dominant power generation company could influence hourly demand and corresponding prices. It turns out that both strategies analysed derive additional revenues for the dominant power generation company compared to a Business-as-Usual (BAU) case. The results provide an indicator of potential threats for misuse from particular storage or DSM utilisation. Therefore, especially in countries where DSM and/or storage applications are still in its fledgling stages, appropriate market surveillance has to be guaranteed.     

Generators' bidding behavior in the NYISO day-ahead wholesale electricity market

This paper proposes a statistical and econometric model to analyze the generators' bidding behavior in the NYISO day-ahead wholesale electricity market. The generator level bidding data show very strong persistence in generators' grouping choices over time. Using dynamic random effect ordered probit model, we find that persistence is characterized by positive state dependence and unobserved heterogeneity and state dependence is more important than unobserved heterogeneity. The finding of true state dependence suggests a scope for economic policy intervention. If NYISO can implement an effective policy to switch generators from higher price groups to lower price groups, the effect is likely to be lasting. As a result, the market price can be lowered in the long-run. Generators' offered capacity is estimated by a two-stage sample selection model. The estimated results show that generators in higher-priced groups tend to withhold their capacity strategically to push up market prices. It further confirms the importance of an effective policy to turn generators into lower price groups in order to mitigate unexpected price spikes. The simulated market prices based on our estimated aggregate supply curve can replicate most volatility of actual DA market prices. Applying our models to different demand assumptions, we find that demand conditions can affect market prices significantly. It validates the importance of introducing demand side management during the restructure of electricity industry.     

Impacts of day-ahead versus real-time market prices on wholesale electricity demand in Texas

The somewhat recent nodal market structure in Texas impacts wholesale day-ahead market (DAM) and real-time market (RTM) prices. However, comparative insights on consumer responses to both these prices have not received attention. This paper attempts to fill this void by developing a system-wide demand response model to better understand price elasticities under DAM and RTM pricing. These insights may also assist grid operators to develop improved short-term forecasts of electricity demand. Using a large dataset from the Electric Reliability Council of Texas and a hierarchical Bayesian population model, we offer new insights on how DAM and RTM pricing shapes demand for electricity, and the related consequences for maintaining a reliable electricity market.     

Effects of regulatory reforms in the electricity supply industry on electricity prices in developing countries

Electric power sector reforms in the electricity supply industry have had an impact on industrial and household prices in developing countries in Latin America, the former Soviet Union, and Eastern Europe. Using original panel data for 83 countries during the period from 1985 to 2002, we examine how each policy instrument of the reform measures influenced electricity prices for countries in the above regions. We found that variables such as entry of independent power producers (IPP), unbundling of generation and transmission, establishment of a regulatory agency, and the introduction of a wholesale spot market have had a variety of impacts on electricity prices, some of which were not always consistent with expected results. The research findings suggest that neither unbundling nor introduction of a wholesale pool market on their own necessarily reduces the electric power price. In fact, contrary to expectations, there was a tendency for the price to rise. However, coexistent with an independent regulator, unbundling may work to reduce electricity prices. Privatization and the introduction of foreign IPP and retail competition lower electricity prices in some regions, but not all.     

Solar PV electricity and market characteristics: two Canadian case-studies

To determine whether solar electricity (that is, electricity generated by photovoltaics) is, on an average, more valuable—in market terms—than the electricity generated in power systems as a whole, this article investigates the extent to which solar resource availability in two Canadian locations is associated with peak electricity market demand and peak electricity market price. More specifically, solar radiation and electricity market data for the period 1 May 2002 to 30 April 2004 are examined for Calgary, Alta. and Guelph, Ont. A variety of visual and statistical investigations reveal that solar radiation values coincide closely with peak electricity market demand and, though to a somewhat lesser extent, peak electricity market prices during the summertime in each location. While more detailed investigation is needed in order to determine the specific impact of different levels of PV penetration upon provincial electricity markets, the article provides ample encouragement for further research. The article also shows how different techniques can be used—in any location—to investigate the relationship among solar electricity potential, system-wide demand and market prices. With electricity industries being restructured around the world, it continues to be important for solar energy proponents to participate in discussions regarding economic costs and benefits. Techniques used in this article can help them advance the solar electricity case more effectively and thus catalyse the deployment of photovoltaics in markets around the world.     

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.