a transmission cost based model to estimate the amount of market integrable wind resources in the pursuit of the large scale integration of wind power production it is imperative to evaluate plausible frictions among the stochastic nature of wind generation electricity markets and the investments in transmission required to accommodate larger amounts of wind if wind producers are made to share the expenses in transmission derived from their integration they may see the doors of electricity markets closed for not being competitive enough this paper presents a model to decide the amount of wind resources that are economically exploitable at a given location from a transmission cost perspective this model accounts for the uncertain character of wind by using a modeling framework based on stochastic optimization simulates market barriers by means of a bi level structure and considers the financial risk of investments in transmission through the conditional value at risk the major features of the proposed model which is efficiently solved using benders decomposition are discussed through an illustrative example

forecasting energy markets using support vector machines abstract in this paper we investigate the efficiency of a support vector machine svm based forecasting model for the next day directional change of electricity prices we first adjust the best autoregressive svm model and then we enhance it with various related variables the system is tested on the daily phelix index of the german and austrian control area of the european energy exchange ee wholesale electricity market the forecast accuracy we achieved is 76 12 over a 200 day period

the dark side of the sun how solar power production affects the market value of solar and gas sources abstract using daily data for the italian wholesale day ahead power market over the period 2008 2013 we assess the impact of solar production on the market value of solar and gas sources defined using the concepts of value factor and unit revenues we find that on average solar generation negatively affects the solar source market value causing a departure from the grid parity condition and mining their competitiveness once public incentives are removed this negative relation is not constant over time and becomes stronger for increasing solar penetration in the energy mix interestingly the opposite is found when looking at gas while the relation between solar production and the gas market value is negative or not significant when the former is low it turns positive for higher levels of solar production this is the result of a change in gas producers bidding strategies indeed in the italian power market the highest hourly price has shifted from the peak daytime when solar production is concentrated to the off peak nighttime when solar is absent from the market and gas can exploit temporary market power

modeling and forecasting electricity prices with input output hidden markov models in competitive electricity markets in addition to the uncertainty of exogenous variables such as energy demand water inflows and availability of generation units and fuel costs participants are faced with the uncertainty of their competitors behavior the analysis of electricity price time series reflects a switching nature related to discrete changes in competitors strategies which can be represented by a set of dynamic models sequenced together by a markov chain an input output hidden markov model iohmm is proposed for analyzing and forecasting electricity spot prices the model provides both good predictions in terms of accuracy as well as dynamic information about the market in this way different market states are identified and characterized by their more relevant explanatory variables moreover a conditional probability transition matrix governs the probabilities of remaining in the same state or changing to another whenever a new market session is opened the model has been successfully applied to real clearing prices in the spanish electricity market

the impact of renewable energy forecast errors on imbalance volumes and electricity spot prices abstract this paper contributes to the general consideration of whether a policy of incentivising system operators to improve the quality and market availability of forecasts for renewable energy outputs would be beneficial using data from the german electricity market we investigate the effect of wind and solar energy forecasts errors on imbalance volumes and subsequent spot electricity prices we use ordinary least squares regression quantile regression and autoregressive moving averages to identify these relationships using variables that have a quarter hourly data granularity the results show that higher wind and solar forecast errors increase the absolute values of imbalance volumes and that these can pass through into higher spot prices we find that wind forecast errors in germany impact spot prices more than solar forecasting errors policy incentives to improve the accuracy and availability of renewable energy forecasts by the system operators should therefore be encouraged

energy market design for renewable resources imbalance settlements and efficiency robustness tradeoffs this paper examines optimal energy market bidding behavior for stochastic resources when energy imbalance payments are determined endogenously from market clearing conditions some electricity markets require wind producers to settle day ahead offers based on their real time energy production this is usually justified by economic and cost causation principles without considering the effects of these policies on curtailment and system balancing costs under these real time settlement requirements demand and wind forecast errors impact the effective penalty price so strategic behavior affects the penalty price paid by producers this paper formulates a two stage game where producers place energy bids in the day ahead market and then choose a curtailment level in real time and it derives the symmetric subgame perfect equilibrium strategy for producers it details how supply curve convexity and resource correlation can lead wind producers to bid conservatively even when they are not risk averse the results show that market based pricing mechanisms improve tradeoffs between system efficiency and mean squared bid error as compared to the case where penalty levels are determined by alternative policies suggesting additional benefits of market based penalty prices beyond those previously studied

trading wind generation in short term energy markets even with state of the art forecasting methods the short term generation of wind farms cannot be predicted with a high degree of accuracy in a market situation these forecasting errors lead to commercial risk through imbalance costs when advance contracting this situation is one that needs to be addressed due to the steady increase in the amount of grid connected wind generation combined with the rise of deregulated market orientated electricity systems in the presence of imbalance prices and uncertain generation a method is required to determine the optimum level of contract energy to be sold on the advance markets such a method is presented here using markov probabilities for a wind farm and demonstrates substantial reductions in the imbalance costs the effect of market closure delays and forecasting window lengths are also shown

electricity prices large scale renewable integration and policy implications abstract this paper investigates the effects of intermittent solar and wind power generation on electricity price formation in germany we use daily data from 2010 to 2015 a period with profound modifications in the german electricity market the most notable being the rapid integration of photovoltaic and wind power sources as well as the phasing out of nuclear energy in the context of a garch in mean model we show that both solar and wind power granger cause electricity prices that solar power generation reduces the volatility of electricity prices by scaling down the use of peak load power plants and that wind power generation increases the volatility of electricity prices by challenging electricity market flexibility

joint price and volumetric risk in wind power trading a copula approach abstract this paper examines the dependence between wind power production and electricity prices and discusses its implications for the pricing and the risk distributions associated with contracts that are exposed to joint price and volumetric risk we propose a copula model for the joint behavior of prices and wind power production which is estimated to data from the danish power market we find that the marginal behavior of the individual variables is best described by arma garch models with non gaussian error distributions and the preferred copula model is a time varying gaussian copula as an application of our joint model we consider the case of an energy trading company entering into longer term agreements with wind power producers where the fluctuating future wind power production is bought at a predetermined fixed price we find that assuming independence between prices and wind power production leads to an underestimation of risk as the profit distribution becomes left skewed when the negative dependence that we find in the data is accounted for by performing a simple static hedge in the forward market we show that the risk can be significantly reduced furthermore an out of sample study shows that the choice of copula influences the price of correlation risk and that time varying copulas are superior to the constant ones when comparing actual profits generated with different models

minimization of imbalance cost trading wind power on the short term power market present power markets are designed for trading conventional generation for wind generation to participate in a short term energy market lengthy wind power production forecasts are required although wind speed forecasting techniques are constantly improving wind speed forecasts are never perfect and resulting wind power forecast errors imply imbalance costs for wind farm owners in this paper a new method for minimization of imbalance costs is developed stochastic programming is used to generate optimal wind power production bids for a short term power market a wind power forecast error is represented as a stochastic process the imbalance costs resulting from this strategy are then compared to the case when wind power production bids on a short term power market are based directly on a wind speed forecast

the impact of intermittently renewable energy on italian wholesale electricity prices additional benefits or additional costs abstract most studies of the literature find that the development of renewable energy sources determines a decrease in the wholesale prices some authors use this finding to state that the current subsidies for renewable technologies cannot be considered as excessive by carrying out a hybrid analysis both simulation and ex post empirical analyses of the case of photovoltaic energy in italy this article demonstrates that this result cannot be generalised under market power an increase in pv production can provide benefits in terms of a wholesale price decrease only beyond a specific threshold and especially if combined with other effects otherwise it is likely that pv development could imply an increase in prices therefore on the one hand caution is necessary when using the estimated change in wholesale prices to evaluate the net cost for consumers of the supporting policies for renewables either the simulation based models or the full empirical analyses may be misleading on the other hand if decarbonisation is the main objective the energy policies should be designed in order to assure a deep and balanced penetration of the clean technologies regardless of their estimated transitory impact on wholesale prices and in the meantime reviewing the organisation of power markets

hourly electricity prices in day ahead markets this paper focuses on the characteristics of hourly electricity prices in day ahead markets in these markets quotes for day ahead delivery of electricity are submitted simultaneously for all hours in the next day the same information set is used for quoting all hours of the day the dynamics of hourly electricity prices does not behave as a time series process instead these prices should be treated as a panel in which the prices of 24 cross sectional hours vary from day to day this paper introduces a panel model for hourly electricity prices in day ahead markets and examines their characteristics the results show that hourly electricity prices exhibit hourly specific mean reversion and that they oscillate around an hourly specific mean price level furthermore a block structured cross sectional correlation pattern between the hours is apparent

renewable generation and electricity prices taking stock and new evidence for germany and austria abstract economic theory predicts that the increase of renewable electricity production should reduce the price of electricity in the short run which is also known as the merit order effect although the merit order effect is only one of several consequences of renewable production on the electricity system it is crucial to determine its size for the economic evaluation of renewable energies in this paper we present a comprehensive overview of relevant past research results on the price effect of renewables additionally we conduct a new empirical analysis of the price effect of renewable production for the austrian german region a market that clearly qualifies for a merit order effect analysis given its characteristics based on the review and our own analysis we show that the merit order effect varies depending on the region and the assessment method chosen we also find that the size of this effect is less dispersed throughout different markets than previously suggested by the literature

short term load forecasting methods an evaluation based on european data this paper uses intraday electricity demand data from ten european countries as the basis of an empirical comparison of univariate methods for prediction up to a day ahead a notable feature of the time series is the presence of both an in traweek and an intraday seasonal cycle the forecasting methods considered in the study include arima modeling periodic ar modeling an extension for double seasonality of holt winters exponential smoothing a recently proposed alternative exponential smoothing formulation and a method based on the principal component analysis pca of the daily demand profiles our results show a similar ranking of methods across the 10 load series the results were disappointing for the new alternative exponential smoothing method and for the periodic ar model the arima and pca methods performed well but the method that consistently performed the best was the double seasonal holt winters exponential smoothing method

on the market impact of wind energy forecasts this paper presents an analysis of how day ahead electricity spot prices are affected by day ahead wind power forecasts demonstration of this relationship is given as a test case for the western danish price area of the nord pool s elspot market impact on the average price behaviour is investigated as well as that on the distributional properties of the price by using a non parametric regression model to assess the effects of wind power forecasts on the average behaviour the non linearities and time variations in the relationship are captured well and the effects are shown to be quite substantial furthermore by evaluating the distributional properties of the spot prices under different scenarios the impact of the wind power forecasts on the price distribution is proved to be considerable the conditional price distribution is moreover shown to be non gaussian this implies that forecasting models for electricity spot prices for which parameters are estimated by a least squares techniques will not have gaussian residuals hence the widespread assumption of gaussian residuals from electricity spot price models is shown to be inadequate for these model types the revealed effects are likely to be observable and qualitatively similar in other day ahead electricity markets significantly penetrated by wind power

trend shifts in the forward premium and the predictability of excess returns in currency markets abstractthis article provides evidence that the forward premium involves structural changes in the trend function which might affect the predictability of currency excess returns to be dependent on the choice of the sample period accounting for the shifts in trend for the forward premium reveals that currency excess returns for the canadian dollar swiss franc euro and pound against the us dollar are significantly predictable irrespective of the sample period selected another advantage of detrending the forward premium is that we can obtain more consistent slope coefficient estimates in the predictive regression which enables us to make more consistent dependable inferences about the excess return predictability

on the effectiveness of the anti gaming policy between the day ahead and real time electricity markets in the netherlands in this paper we study the linkage between two related markets for electricity in the netherlands the day ahead market and the real time market the dutch regulator wants to prevent trading across these two markets and has set up a dual pricing system for this purpose in this paper we test the effectiveness of this policy by studying the ex post profitability of trading strategies spanning the two markets over various time segments our results show that profits generated by these strategies are rarely positive on average and always characterized by very large potential losses which dwarf the mean profit when the latter is positive

empirical analysis of the merit order effect and the missing money problem in power markets with high res shares an on going debate in the energy economics and power market community raises the question if energy only power markets are increasingly failing due to growing feed in shares from subsidized renewable energy sources res the argument being essentially that the merit order effect of res production depresses day ahead spot market prices which in turn creates a situation where power plant owners cannot recover investment costs missing money problem we argue in short that energy only power markets are not failing in principle but are rather facing several market distortions that hinder proper market functioning namely 1 the gap between the electricity volume actually traded at day ahead spot markets versus the overall electricity consumption and 2 the regulatory assumption that variable res generation i e wind and photovoltaic pv truly has zero marginal operation and grid integration costs in this paper we show that both effects over amplify the well known merit order effect of res power feed in and indirectly also the missing money problem beyond a level that is explainable by underlying physical realities we empirically analyze the impacts of wind and pv power feed in on the day ahead market for the epex german austrian market zone a region that is already today experiencing significant feed in tariff fit subsidized res power feed in ca 20 fit share our analysis shows that if necessary regulatory adaptations are taken i e increasing the spot market s share of overall load demand and using the true marginal costs of res units in the merit order energy based power markets remain functional despite high res power feed in

energy models for demand forecasting a review abstract energy is vital for sustainable development of any nation be it social economic or environment in the past decade energy consumption has increased exponentially globally energy management is crucial for the future economic prosperity and environmental security energy is linked to industrial production agricultural output health access to water population education quality of life etc energy demand management is required for proper allocation of the available resources during the last decade several new techniques are being used for energy demand management to accurately predict the future energy needs in this paper an attempt is made to review the various energy demand forecasting models traditional methods such as time series regression econometric arima as well as soft computing techniques such as fuzzy logic genetic algorithm and neural networks are being extensively used for demand side management support vector regression ant colony and particle swarm optimization are new techniques being adopted for energy demand forecasting bottom up models such as markal and leap are also being used at the national and regional level for energy demand management

the regulating power market on the nordic power exchange nord pool an econometric analysis abstract what differentiates the structure of nord pool from other power exchanges around the world is the way the balance from the spot market is maintained until the actual physical delivery takes place via the regulating power market in norway this paper reveals the pattern of the prices on the regulating power market by analysing the cost of being unable to fulfil the commitments made on the spot market some power producers with unpredictable fluctuations e g wind will need to buy regulation services the disclosed pattern implies that these producers must pay a limited premium of readiness in addition to the spot price this premium is independent of the amount of regulation the level of the premium of readiness for down regulation is shown to be strongly influenced by the level of the spot price on the other hand it is demonstrated that the premium for up regulation is less correlated to the spot price furthermore it is found that the amount of regulation affects the price of regulating power for up regulation more strongly than it does for down regulation the disclosed cost of using the regulating power market is a quadratic function of the amount of regulation this asymmetric cost may encourage bidders with fluctuating production to be more strategic in their way of bidding on the spot market by using such strategies the extra costs for example wind power needed to counter unpredictable fluctuations may be limited

trading wind generation from short term probabilistic forecasts of wind power due to the fluctuating nature of the wind resource a wind power producer participating in a liberalized electricity market is subject to penalties related to regulation costs accurate forecasts of wind generation are therefore paramount for reducing such penalties and thus maximizing revenue despite the fact that increasing accuracy in spot forecasts may reduce penalties this paper shows that if such forecasts are accompanied with information on their uncertainty i e in the form of predictive distributions then this can be the basis for defining advanced strategies for market participation such strategies permit to further increase revenues and thus enhance competitiveness of wind generation compared to other forms of dispatchable generation this paper formulates a general methodology for deriving optimal bidding strategies based on probabilistic forecasts of wind generation as well as on modeling of the sensitivity a wind power producer may have to regulation costs the benefits resulting from the application of these strategies are clearly demonstrated on the test case of the participation of a multi mw wind farm in the dutch electricity market over a year

retrospective modeling of the merit order effect on wholesale electricity prices from distributed photovoltaic generation in the australian national electricity market in electricity markets that use a merit order dispatch system generation capacity is ranked by the price that it is bid into the market demand is then met by dispatching electricity according to this rank from the lowest to the highest bid the last capacity dispatched sets the price received by all generation ensuring the lowest cost provision of electricity a consequence of this system is that significant deployments of low marginal cost electricity generators including renewables can reduce the spot price of electricity in australia this prospect has been recognized in concern expressed by some coalfired generators that delivering too much renewable generation would reduce wholesale electricity prices in this analysis we calculate the likely reduction of wholesale prices through this merit order effect on the australian national electricity market we calculate that for 5 gw of capacity comparable to the present per capita installation of photovoltaics in germany the reduction in wholesale prices would have been worth in excess of a 1 8 billion over 2009 and 2010 all other factors being equal we explore the implications of our findings for feed in tariff policies and find that they could deliver savings to consumers contrary to prevailing criticisms that they are a regressive form of taxation

simulating the impact of wind production on locational marginal prices this paper analyzes the impact of wind production on the locational marginal prices of a fully competitive pool based electricity market wind productions are modeled as negative loads and characterized by historical data records the analysis pertains to the structural relationship between wind production and locational marginal prices and disregards the collateral effect of strategic offering the study presented allows a statistical characterization of locational marginal prices as a function of the statistical data of the wind plants and the structure of the considered electric energy system

new issues in the uruguay round and beyond the general agreement on tariffs and trade gatt is a treaty establishing a framework of rules and principles for policies affecting merchandise trade it also provides a forum in which sovereign states periodically engage in reciprocal trade liberalisation and rule making 2 as a result of substantial reductions in tariffs through periodic rounds of multilateral negotiations rule making has gradually become as if not more important than liberalisation per se starting with the kennedy round i964 7 but especially in the tokyo i973 9 and uruguay i986 rounds an increasing number of agenda items involved the negotiation of rules and disciplines for specific trade related domestic policies rather than further reductions in tariffs and other border measures rules pertaining to product standards subsidies and government procurement were prominent items on the agenda of the tokyo round the uruguay round further expanded the multilateral negotiating agenda by adding trade related investment measures trims trade related intellectual property rights trips and measures affecting the contestability of service markets the trend for multilateral trade negotiations to address domestic policies shows no sign of abating calls for a post uruguay round negotiation have identified issues such as competition policy foreign direct investment fdi regulations innovation policies and the interaction between trade and environmental policies as possible topics for discussion 3 in part the steady agenda expansion reflects changes in the structure of the global economy the managerial and technological innovations of the last decade such as just in time inventory management and the increased tradeability of services created pressures for greater specialisation and geographical splintering of production this in turn made regulations pertaining to services fdi transfer of technology and protection of intangible assets more important for both governments and firms flows associated with services fdi and intellectual property ip are smaller than merchandise trade but are quite substantial table i reveals that global merchandise trade in i990 was 3 5 trillion while world trade in commercial services was about 820 billion global receipts for ip were some 33 billion and income flows

stochastic factor model for electricity spot price the case of the nordic market this paper presents a stochastic factor based approach to mid term modeling of spot prices in deregulated electricity markets the fundamentals affecting the spot price are modeled independently and a market equilibrium model combines them to form spot price main advantage of the model is the transparency of the generated prices because each underlying factor and the dynamics between factors can be modeled and studied in detail paper shows realistic numerical examples on the forerunner scandinavian electricity market the model is used to price an exotic electricity derivative

has renewable energy induced competitive behavior in the spanish electricity market abstract recent energy policy has favored a massive introduction of renewable energy sources on electricity markets which has greatly impacted their performance first the electricity price has decreased as a consequence of the so called merit order effect another relevant effect is associated to the intermittent nature of renewable energy which has increased the cost of ancillary services a third and important aspect less addressed in the literature is the induced change in the strategic behavior of the conventional electricity producers in principle the entry of new generators in a concentrated market would make it more competitive and change the strategic behavior of the incumbents we test this hypothesis for the spanish wholesale market while we find no significant change in behavior for nuclear hydropower and coal a change is observed in combined cycle bidding strategies after the entry of renewable generators our analysis shows that the massive entry of renewable energy sources made other generators behavior more competitive in the short run but the effect was not persistent

the plunge in german electricity futures prices analysis using a parsimonious fundamental model abstract 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

lower electricity prices and greenhouse gas emissions due to rooftop solar empirical results for massachusetts abstract monthly and hourly correlations among photovoltaic pv capacity utilization electricity prices electricity consumption and the thermal efficiency of power plants in massachusetts reduce electricity prices and carbon emissions beyond average calculations pv utilization rates are highest when the thermal efficiencies of natural gas fired power plants are lowest which reduces emissions of co 2 and ch 4 by 0 3 relative to the annual average emission rate there is a positive correlation between pv utilization rates and electricity prices which raises the implied price of pv electricity by up to 10 relative to the annual average price such that the average mwh reduces electricity prices by 0 26 1 86 per mwh these price reductions save massachusetts rate payers 184 million between 2010 and 2012 the current and net present values of these savings are greater than the cost of solar renewable energy credits which is the policy instrument that is used to accelerate the installation of pv capacity together these results suggest that rooftop pv is an economically viable source of power in massachusetts even though it has not reached socket parity

the impact of renewables on electricity prices in germany an update for the years 2014 2018 abstract increasing electricity prices for private consumers manifested the idea of price boosting renewable energy sources in germany s public opinion literature however widely concurs that wind and photovoltaics have a reducing effect on spot market electricity prices the underlying merit order effect led to historically low exchange prices in the past years to quantify this effect this study analyses historic demand and supply curves from the german day ahead market to reconstruct electricity prices without the feed in of wind and photovoltaics from 2014 to 2018 results show that renewable energy sources considerably reduced electricity prices by between 2 89 ct kwh in 2014 to 8 89 ct kwh in 2017 this allowed german end consumers to save a total of 40 billion from 2014 to 2018 additionally wind and pv contributed significantly to security of supply demand could not have been met by domestic conventional and nuclear generation capacities in up to 424 hours in 2018 the study highlights the necessity to further speed up the expansion of wind and photovoltaics

opportunity cost bidding by wind generators in forward markets analytical results wind generation must trade in forward electricity markets based on imperfect forecasts of its output and real time prices when the real time price differs for generators that are short and long the optimal forward strategy must be based on the opportunity costs of charges and payments in real time rather than a central estimate of wind output we present analytical results for wind s optimal forward strategy in the risk neutral case the optimal strategy is determined by the distribution of real time available wind capacity and the expected real time prices conditioned on the forward price and wind out turn our approach is simpler and more computationally efficient than formulations requiring specification of full joint distributions or a large set of scenarios informative closed form examples are derived for particular specifications of the wind price dependence structure in the usual case of uncertain forward prices the optimal bidding strategy generally consists of a bid curve for wind power rather than a fixed quantity bid a discussion of the risk averse problem is also provided an analytical result is available for aversion to production volume risk however we doubt whether wind owners should be risk averse with respect to the income from a single settlement period given the large number of such periods in a year

managing volumetric risk of long term power purchase agreements abstract a negative dependence between wind power production and electricity spot price exists this is an important fact to consider for risk management of long term power purchase agreements ppas in this study we investigate this dependence by constructing a joint model using constant as well as time varying copulas we propose to use score driven models as marginal model for the spot price of electricity as these are more robust to extreme events compared to arma garch models we apply the new model to pricing and risk management of ppas and benchmark it against the arma garch specification our comparison shows that the score driven model results in a statistically significant improvement of predicting the value at risk var which is of high importance for risk management of long term ppas further comparing constant and time varying copulas we find that all time varying copulas are significantly better than their constant counterparts at predicting the var hence time varying copulas should be used in risk management of ppas

a combined modeling approach for wind power feed in and electricity spot prices abstract wind power generation and its impacts on electricity prices has strongly increased in the eu therefore appropriate mark to market evaluation of new investments in wind power and energy storage plants should consider the fluctuant generation of wind power and uncertain electricity prices which are affected by wind power feed in wpf to gain the input data for wpf and electricity prices simulation models such as econometric models can serve as a data basis this paper describes a combined modeling approach for the simulation of wpf series and electricity prices considering the impacts of wpf on prices based on an autoregressive approach thereby wpf series are firstly simulated for each hour of the year and integrated in the electricity price model to generate an hourly resolved price series for a year the model results demonstrate that the wpf model delivers satisfying wpf series and that the extended electricity price model considering wpf leads to a significant improvement of the electricity price simulation compared to a model version without wpf effects as the simulated series of wpf and electricity prices also contain the correlation between both series market evaluation of wind power technologies can be accurately done based on these series

revitalising the wind power induced merit order effect to reduce wholesale and retail electricity prices in australia this paper investigates the effect of increasing the number of wind turbine generators on wholesale spot prices in the australian national electricity market s nem given the existing transmission grid from 2014 to 2025 we use a sensitivity analysis to evaluate the effect of five different levels of wind power penetration on prices ranging from scenario a no wind to scenario e that includes existing and planned wind power sufficient to meet australia s original 2020 41twh large scale renewable energy target lret we find divergence in prices between states and similar prices for nodes within states this supports the garnaut climate change review assessment on the prevalence of gold plating the intrastate transmission network and underinvesting in interstate connectivity we find that increasing wind power penetration decreases wholesale spot prices but that retail prices have increased in deregulated south australia and queensland similarly in victoria we argue that there is a pressing need to split the large generator retail companies into separate retail and generator companies and to reassess regulatory rules more generally interconnector congestion limits the potential for wind power to further reduce wholesale prices across the nem so the need for a high capacity transmission backbone in the nem is becoming clearer and will become pressing when australia moves beyond its current 2020 lret

the market value of variable renewables the effect of solar wind power variability on their relative price this paper provides a comprehensive discussion of the market value of variable renewable energy vre the inherent variability of wind speeds and solar radiation affects the price that vre generators receive on the market market value during windy and sunny times the additional electricity supply reduces the prices because the drop is larger with more installed capacity the market value of vre falls with higher penetration rate this study aims to develop a better understanding on how the market value with penetration and how policies and prices affect the market value quantitative evidence is derived from a review of published studies regression analysis of market data and the calibrated model of the european electricity market emma we find the value of wind power to fall from 110 of the average power price to 50 80 as wind penetration increases from zero to 30 of total electricity consumption for solar power similarly low value levels are reached already at 15 penetration hence competitive large scale renewable deployment will be more difficult to accomplish than as many anticipate

how renewable production depresses electricity prices evidence from the german market abstract the urgency of climate change has led several countries to develop renewable energy in order to reduce co2 emissions through the means of various subsidies in the electricity sector one drawback of such policies is the negative impact on electricity prices known as the merit order effect this paper aims at assessing how intermittent renewable production depresses electricity prices in germany which has experienced a significant increase of its renewable capacity over the last two decades to do so we use a two regime markov switching model that enables to disentangle the impact of wind and solar generation depending on the price being high or low we find as expected that renewable production induces a negative marginal effect which is stronger in regimes of relatively high prices in addition we show that both wind and solar productions have a significant impact on the distribution of prices and in particular on the frequency and expected duration of each regime this has implications in terms of market design security of supply and support mechanisms for renewables

the merit order effect of wind and solar power volatility and determinants abstract the investment in renewable energy sources power generation is coming into a stall in face of the removal of incentives in most of the european countries the technological maturity of wind and solar power generation is the justification basis and market integration of extensive amounts of renewable energy is seen with concern by electricity systems stakeholders given the low marginal cost of renewable power generation the available load in the spot electricity market for conventional and dispatchable power plants is diminishing the so called merit order effect in this study we estimate the value of the merit order effect due to wind and solar power generation in the iberian electricity market with historical bid supply and demand offers from 2008 to 2017 the estimated values are then used to value determinants and volatility through garch econometric modelling results demonstrate that the merit order effect in iberia is influenced negatively by the residual load and positively by demand wind power and solar power additionally the high merit order effect volatility found mirrors the behavior of spot electricity market

wind power and electricity prices at the pjm market increased deployment of wind power generation is changing the landscape of power supply around the world when integrated with electricity markets wind power is also widely known to influence the prices cleared at the market this paper examines the effect of wind power generation on the day ahead market prices in the pjm electricity market using robust econometric models and statistical inference results show that the quantified expected benefits to wholesale market participants may be substantial despite the relatively low wind power penetration levels still observed within the pjm jurisdiction relative to other markets the quantified unitary benefits outweigh by a great margin the renewable energy credits given to qualifying wind farms across the market when benefits outweigh the costs incurred to generate them welfare is accrued to this end benefit allocation mechanisms are proposed which may contribute to the continued development of wind power on the roadmap to a cleaner power industry of the future

pool strategy of a price maker wind power producer we consider the problem of a wind power producer trading energy in short term electricity markets the producer is a price taker in the day ahead market but a price maker in the balancing market and aims at optimizing its expected revenues from these market floors the problem is formulated as a mathematical program with equilibrium constraints mpec and cast as a mixed integer linear program milp which can be solved employing off the shelf optimization software the optimal bid is shown to deliver significantly improved performance compared to traditional bids such as the conditional mean or median forecast of wind power distribution finally sensitivity analyses are carried out to assess the impact on the offering strategy of the producer s penetration in the market of the correlation between wind power production and residual system deviation and of the shape of the forecast distribution of wind power production

does renewable energy generation decrease the volatility of electricity prices an analysis of denmark and germany although variable renewable energy vre technologies with zero marginal costs decrease electricity prices the literature is inconclusive about how the resulting shift in the supply curves impacts price volatility because the flexibility to respond to high peak and low off peak prices is crucial for demand response applications and may compensate for the losses of conventional generators caused by lower average prices there is a need to understand how the penetration of vre affects volatility in this paper we build distributed lag models with danish and german data to estimate the impact of vre generation on electricity price volatility we find that in denmark wind power decreases the daily volatility of prices by flattening the hourly price profile but in germany it increases the volatility because it has a stronger impact on off peak prices our analysis suggests that access to flexible generation capacity and wind power generation patterns contribute to these differing impacts meanwhile solar power decreases price volatility in germany by contrast the weekly volatility of prices increases in both areas due to the intermittency of vre thus policy measures for facilitating the integration of vre should be tailored to such region specific patterns

spatial dependencies of wind power and interrelations with spot price dynamics abstract wind power has seen strong growth over the last decade and increasingly affects electricity spot prices in particular prices are more volatile due to the stochastic nature of wind such that more generation of wind energy yields lower prices therefore it is important to assess the value of wind power at different locations not only for an investor but for the electricity system as a whole in this paper we develop a stochastic simulation model that captures the full spatial dependence structure of wind power by using copulas incorporated into a supply and demand based model for the electricity spot price this model is calibrated with german data we find that the specific location of a turbine i e its spatial dependence with respect to the aggregated wind power in the system is of high relevance for its value many of the locations analyzed show an upper tail dependence that adversely impacts the market value therefore a model that assumes a linear dependence structure would systematically overestimate the market value of wind power in many cases this effect becomes more important for increasing levels of wind power penetration and may render the large scale integration into markets more difficult

is green energy expensive empirical evidence from the spanish electricity market abstract renewable energy promotion and its cost are at the heart of the energy policy debate in many countries the question from an economic perspective is how expensive the promotion of renewable sources through price based incentive schemes is this paper addresses this issue empirically we analyze the spanish electricity market during the period 2008 2012 where renewable energy production rose by 57 to determine how expensive it was we first measure the savings due to the spot price reduction driven by the merit order effect and second we compute the amount paid as incentives to green energy by the electricity system the difference between the two is the net cost of green energy to the electricity markets we present aggregate results for renewable sources as a whole as well as individual results for each technology we show that at the initial stages when renewable capacity was low green energy promotion paid for itself 2008 2009 however from 2010 on when renewable production reached a relatively high level it started to impose a positive net cost on the system finally we found substantial differences among technologies wind energy implied the lowest net cost while solar photovoltaic was the most expensive

evaluating the effect of technology transformation on the electricity utility industry abstract the technology shift from fossil fuelled systems to renewable energies has been promoted by governments with the purpose of decarbonising the power industry however rapid technology progress has prompted disruptive changes that transformed market structures incumbent electricity utilities particularly those based on fossil fuel plant are shifting from their stable and predictable situation to confront challenges from those that offer alternative energy services in this new environment the industry will benefit from mid to long term sector foresight the paper studies the potential impact of renewable energy sources res on electricity systems specifically on the generation and distribution businesses for this purpose a fairly detailed and integrated supply and demand based system dynamics model has been built to quantify the extent of their potential impact the model disaggregates the household sector which may generate a significant part of its electricity using rooftop solar energy this is illustrated by examining a utility engaged in the generation and distribution businesses in the colombian electricity market through simulation runs this paper concludes that subject to policy and all other things remaining equal solar rooftop generation is a major threat for utilities while the generation business is most affected in the short term the distribution business is the one most impacted in the long term and jointly they may induce the utility death spiral

economic and environmental implications of different approaches to hedge against wind production uncertainty in two settlement electricity markets a pjm case study abstract 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

dynamic analysis of the german day ahead electricity spot market abstract this paper analyzes the dynamic behavior of day ahead spot prices in the german electricity spot market due to positive structural shocks in wind and solar power it uses a dynamic structural vector autoregressive model to estimate the related structural impulse response functions the estimates suggest that wind power shocks have a more prolonged negative effect on spot prices than solar power shocks significant autocorrelations of wind power for larger lags indicate these results the total negative merit order effect of a solar power shock is larger when using a reasonable model specification one reason might be that solar power shocks coincide with demand peaks however results regarding the relation of the effects of wind and solar should be dealt with carefully because these results do not hold for all specifications past static estimates show differences in the total average negative merit order effects these estimates might be overstated if wind and solar power dynamics are transferred to the merit order effects

the merit order effect of wind and photovoltaic electricity generation in germany 2008 2016 estimation and distributional implications abstract generation from renewable energy sources in germany has experienced a considerable uptake in recent years mainly responsible for this development is the german renewable energy sources act erneuerbare energien gesetz eeg this paper considers redistributive implications of the eeg for different electricity consumers using time series regression analysis we show that electricity generation by wind and pv has reduced spot market prices considerably by 6 mwh in 2010 rising to 10 mwh in 2012 we use these results to build a near term forecasting tool for merit order effects projected to reach 14 16 mwh in 2016 on the other hand the costs of the eeg are passed forward to consumers in the form of a surcharge our findings highlight significant redistributive transfers under the current design of the eeg in particular some energy intensive industries are benefiting from lower wholesale electricity prices whilst being largely exempted from contributing to the costs of the scheme we also highlight implications of our results for other areas for reform of the eeg such as adequate remuneration mechanisms that ensure efficient operation and investment decisions are made under the scheme more generally these findings suggest that policy makers need to integrate distributional assessments into policy design and implementation