role of industrial district externalities in export and value added performance evidence from the population of italian firms becchetti l de panizza a and oropallo f 2007 role of industrial district externalities in export and value added performance evidence from the population of italian firms regional studies 41 601 621 the paper tries to shed light on the export and value added performance of industrial districts by integrating information on the population of italian firms from the asia database of the italian statistical institute with balance sheet data for all limited liability companies in selected manufacturing industries the findings show that firms located in industrial districts specialized or not in the leading manufacturing activity of the district export more and have higher added value than firms located elsewhere net of the impact of relevant controls the robustness check undertaken on the agglomeration performance nexus detects as expected a significant relationship between dichotomous district indicators and global and industry specific continuous measures of agglomeration and specializat

competition and coalition formation of renewable power producers we investigate group formations and strategic behaviors of renewable power producers in electricity markets these producers currently bid into the day ahead market in a conservative fashion because of the real time risk associated with not meeting their bid amount it has been suggested in the literature that producers would bid less conservatively if they can form large groups to take advantages of spatial diversity to reduce the uncertainty in their aggregate output we show that large groups of renewable producers would act strategically to lower the aggregate output because of market power to maximize renewable power production we characterize the trade off between market power and generation uncertainty as a function of the size of the groups we show there is a sweet spot in the sense that there exists groups that are large enough to achieve the uncertainty reduction of the grand coalition but are small enough such that they have no significant market power we consider both independent and correlated forecast errors under a fixed real time penalty we also consider a real time market where both selling and buying of energy are allowed we validate our claims using pjm and nrel data

optimal electricity market for wind power abstract this paper is about electricity market operation when looking from the wind power producers point of view the focus in on market time horizons how many hours there is between the closing and delivering the bids the case is for the nordic countries the nordpool electricity market and the danish wind power production real data from year 2001 was used to study the benefits of a more flexible market to wind power producer as a result of reduced regulating market costs from better hourly predictions to the market wind power producer would gain up to 8 more if the time between market bids and delivery was shortened from the day ahead elspot market hourly bids by noon for 12 36 h ahead an after sales market where surplus or deficit production could be traded 2 h before delivery could benefit the producer almost as much gaining 7

marshallian industrial districts in italy the end of a model or adaptation to the global economy this paper discusses the marshallian industrial district as it was rediscovered and further developed by italian economists before tracing the main changes in the market and institutional context in the wake of globalization it then focuses on some of the main transformations that have taken place in the italian districts since the 1990s after highlighting the important role still played by the districts in the italian economy the paper develops a framework for the evolutionary processes of the marshallian industrial district that would allow reproduction of the district in a manner suited to the era of globalisation

evaluating a stochastic programming based bidding model for a multireservoir system hydropower producers need to schedule when to release water from reservoirs and participate in wholesale electricity markets where the day ahead production is physically traded a mixed integer linear stochastic model for bid optimization and short term production allocation is developed and tested through a simulation procedure implemented for a complex real life river system the stochastic bid model sees uncertainty in both spot market prices and inflow to the reservoirs the same simulation procedure is also implemented for a practice based deterministic heuristic method similar to what is currently used for bid determination in the industry and the results are compared the stochastic approach gives improvements in terms of higher obtained average price and higher total value than the deterministic alternative it also performs well in terms of startup costs in the presence of river flow travel delay the practice based method is even more outperformed by the stochastic model

strategic offering for a wind power producer as a result of subsidies and technological maturity renewable electricity producers have grown in some jurisdictions to clearly dominant positions in the market under this context we propose an offering strategy for a wind power producer with market power that participates in the day ahead market as a price maker and in the balancing market as a deviator uncertainty pertaining to wind power production and balancing market price is represented through a set of correlated scenarios the proposed model is a stochastic mathematical program with equilibrium constraints mpec that can be recast as a tractable mixed integer linear programming milp problem which is solvable using available optimization software results from an illustrative example and two case studies show the effectiveness of the proposed model

global trading versus linking architectures for international emissions trading abstract international emissions trading is widely seen as an indispensable policy pillar of climate change mitigation stern n 2007 the economics of climate change the stern review cambridge university press new york this article analyzes five different types of trading architectures classified into two top down unfccc driven and three bottom up driven by individual countries or regions approaches the two types of approaches are characterized by a trade off between environmental effectiveness and political feasibility respectively whereas their relative cost effectiveness depends on implementation details bottom up architectures constitute imperfect substitutes for top down architectures in terms of environmental effectiveness and thus remain mere fallback options however especially the formal linking architecture can act as complement in terms of cost effectiveness

geography industrial organization and agglomeration this paper makes two contributions to the empirical literature on agglomeration economies first the paper uses a unique and rich database in conjunction with mapping software to measure the geographic extent of agglomerative externalities previous papers have been forced to assume that agglomeration economies are club goods that operate at a metropolitan scale second the paper tests for the existence of organizational agglomeration economies of the kind studied qualitatively by saxenian 1994 this is a potentially important source of increasing returns that previous empirical work has not considered results indicate that localization economies attenuate rapidly and that industrial organization affects the benefits of agglomeration

games of climate change with international trade we analyse games of greenhouse gas emission reduction in which the emissions and the emission reduction costs of one country depend on other countries emission abatement in an analytically tractable model we show that international trade effects on costs and emissions can either increase or decrease incentives to reduce emissions and to cooperate on emission abatement in some specifications optimal emission reduction is unaffected by trade we therefore specify the model further calibrating it to larger models that estimate the costs of emission reduction trade effects and impacts of climate change if trade effects are driven by total emission reduction costs of other countries cooperation is slightly more difficult than in the case without trade effects if trade effects are determined by relative emission reduction efforts in other countries cooperation becomes easier carbon leakage does not affect our qualitative insights although it does change the numbers

intraday trading of wind energy in this paper we tackle the problem of a wind power producer participating in a short term electricity market that allows for the continuous but potentially illiquid intraday trading of energy considering the realistic case of a wind farm operating in the western danish price area of nord pool we build a simple but effective algorithm for the wind power producer to fully benefit from the elbas intraday market we then investigate the sensitivity of the obtained benefits to the maximum volume of energy the wind power producer is willing to trade in the intraday market the ultimate aim of the trade either to decrease energy imbalances or to increase profits and to the installed capacity of the wind farm our numerical results reveal that the wind power producer can substantially increase his revenues by partaking in the intraday market but with diminishing returns to scale a result that we attribute to the low liquidity of elbas

a convex model of risk based unit commitment for day ahead market clearing considering wind power uncertainty the integration of wind power requires the power system to be sufficiently flexible to accommodate its forecast errors in the market clearing process the scheduling of flexibility relies on the manner in which the wind power uncertainty is addressed in the unit commitment uc model this paper presents a novel risk based day ahead unit commitment ruc model that considers the risks of the loss of load wind curtailment and branch overflow caused by wind power uncertainty these risks are formulated in detail using the probabilistic distributions of wind power probabilistic forecast and are considered in both the objective functions and the constraints the ruc model is shown to be convex and is transformed into a mixed integer linear programming milp problem using relaxation and piecewise linearization the proposed ruc model is tested using a three bus system and an ieee rts79 system with wind power integration the results show that the model can dynamically schedule the spinning reserves and hold the transmission capacity margins according to the uncertainty of the wind power a comparison between the results of the ruc a deterministic uc and two scenario based uc models shows that the risk modeling facilitates a strategic market clearing procedure with a reasonable computational expense

intra and extra union flexibility in meeting the european union s emission reduction targets the eu has proposed four flexibility mechanisms for the regulation of greenhouse gas emissions in the period 2013 2020 1 the emissions trade scheme ets a permit market between selected companies 2 trade in non ets allotments between member states 3 the clean development mechanism cdm to purchase offsets in developing countries and 4 trade in cdm warrants between member states this paper shows that aggregate abatement costs fall as flexibility increases however limited flexibility creates rents so that increasing flexibility raises costs in some member states costs are reduced more by the cdm than by non ets trade the cdm warrants market reduces costs by a small amount only market power is a real issue however the warrants market is obsolete in case there is non ets trade the cdm leads to price convergence between the ets and non ets market there would be one price for carbon in the european union if the proposed limits on cdm access are relaxed slightly

farsighted coalitional stability abstract i define the largest consistent set a solution concept which applies to situations in which coalitions freely form but cannot make binding contracts act publicly and are fully farsighted in that a coalition considers the possibility that once it acts another coalition might react a third coalition might in turn react and so on without limit i establish weak nonemptiness conditions and apply it to strategic and coalitional form games and majority rule voting i argue that it improves on the von neumann morgenstern stable set as it is usually defined but is consistent with a generalization of the stable set as in the theory of social situations journal of economic literature classification numbers c70 c71

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

offering strategy of wind power producer a multi stage risk constrained approach given the significant amount of installed generation capacity based on wind power and also due to current economic downturn the subsidies and incentives that have been widely used by wind power producers to recover their investment costs have decreased and are even expected to disappear in the near future in these conditions wind power producers need to develop offering strategies to make their investments profitable counting solely on the market this paper proposes a multi stage risk constrained stochastic complementarity model to derive the optimal offering strategy of a wind power producer that participates in both the day ahead and the balancing markets uncertainties concerning wind power productions market prices demands bids and rivals offers are efficiently modeled using a set of scenarios the conditional value at risk metric is used to model the profit risk associated with the offering decisions the proposed model is recast as a tractable mixed integer linear programming program solvable using available branch and cut algorithms results of a case study are reported and discussed to show the effectiveness and applicability of the proposed approach

hot air in kyoto cold air in the hague the failure of global climate negotiations abstract why did the climate negotiations in the hague fail our contribution is to argue that the conflict between the european union eu and the united states us stems mainly from disagreement on the cost issue we argue that the three main concerns promoted by the eu in the hague first a 50 national emission ceiling the supplementarity principle second the use of carbon sinks and third an international market control system these issues can be solved by removing all restrictions on free greenhouse gas ghg trade and by establishing the world trade organization as an international authority the us will face considerably higher costs than foreseen at the negotiations in kyoto and will have strong incentives to free ride our main hypothesis is that the eu proposal on supplementarity made the us turn to free riding thus to make the us stay in an international ghg emission trading scheme the eu must reconsider and acknowledge us claims for cheaper reduction options and the right to trade hot air this point is important if the us does not participate the increase in emissions will be much higher than the emission reduction following the eu supplementarity proposal

optimal intensity targets for greenhouse gas emissions trading under uncertainty uncertainty is an obstacle for commitments under cap and trade schemes for emission permits we assess how well intensity targets where each country s permit allocation is indexed to its future realized gdp can cope with uncertainties in international greenhouse emissions trading we present some empirical foundations for intensity targets and derive a simple rule for the optimal degree of indexation to gdp using an 18 region simulation model of a cooperative global cap and trade treaty in 2020 under multiple uncertainties and endogenous commitments we show that optimal intensity targets could reduce the cost of uncertainty and achieve significant increases in global abatement the optimal degree of indexation to gdp would vary greatly between countries including super indexation in some advanced countries and partial indexation for most developing countries standard intensity targets with one to one indexation would also improve the overall outcome but to a lesser degree and not in all individual cases although target indexation is no magic wand for a future global climate treaty gains from reduced cost uncertainty and the potential for more stringent environmental commitments could justify the increased complexity and other potential downsides of intensity targets

bringing wind energy to market wind energy is a rapidly growing source of renewable energy generation however the current extra market approach to its assimilation into the electric grid will not scale at deep penetration levels in this paper we investigate how an independent wind power producer might optimally offer its variable power into a competitive electricity market for energy starting with a stochastic model for wind power production and a model for a perfectly competitive two settlement market we derive explicit formulae for optimal contract offerings and the corresponding optimal expected profit as wind is an inherently variable source of energy we explore the sensitivity of optimal expected profit to uncertainty in the underlying wind process we also examine the role of forecast information and recourse markets in this setting we quantify the role of reserves in increasing reliability of offered contracts and obtain analytical expressions for marginal profits resulting from investments in improved forecasting and local auxiliary generation the formulae make explicit the relationship between price signals and the value of such firming strategies

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 wind generation on wholesale electricity prices in the hydro rich pacific northwest extant literature documents that wind generation can reduce wholesale electricity market prices by displacing conventional generation but how large is the wholesale price effect of wind generation in an electricity market dominated by hydroelectric generation we explore this question by analyzing the impact of wind generation on wholesale electricity prices in the pacific northwest region of the united states this hydro rich system tends to be energy limited rather than capacity constrained with its marginal generation during the hydro runoff season often a hydro unit instead of a natural gas fired unit we find that increased wind generation reduces wholesale market prices by a small but statistically significant amount while a hydro rich system can integrate wind generation at a lower cost than a thermal dominated region the direct economic benefits to end users from greater investment in wind power may be negligible

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

optimal bidding of a group of wind farms in day ahead markets through an external agent in deregulated electricity markets producers offer their energy to the day ahead market as the subsidies for renewable producers are becoming lower and lower they have to adapt to market prices this paper models the energy trading in the day ahead market for wind power producers different strategies are proposed for this purpose 1 several wind farms offering their energy separately to the day ahead market 2 the same strategy as in 1 but compensating the imbalance among different wind farms and 3 a joint offer involving several wind farms through an external agent in order to minimize the imbalances between the offer and the final power generation the strategies are modeled with stochastic mixed integer linear programming and conditional value at risk is used to consider the risk assessment the expected profit including risk aversion is maximized for each wind power producer and for the set of wind power producers in the case of a joint offer a comparison of the different cases is described in detail in a case study and relevant conclusions are provided

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

a statistical model for wind power forecast error and its application to the estimation of penalties in liberalized markets the problem of accurately forecasting wind energy has garnered a great deal of attention in recent years there are always some errors associated with any forecasting methodology although it is sometimes assumed that the forecast errors are normally distributed it is a special case arising from the geographical dispersion of wind resources as shown in this paper the distribution of the forecast error needs to be examined individually for every wind farm to determine the impact of this error on trading energy in electricity markets this paper addresses the problem of modeling the distribution of the forecast errors associated with persistence forecasts at the level of a single wind farm and develops a novel mixed distribution based model to approximate the distribution of these errors the model is then used to estimate the penalties for imperfectly forecast energy injections in the short term markets the results from the application of this model to trading are further used to assess the feasibility of energy storage in hedging against imperfect forecasts

pareto improvement through a reallocation of carbon emission quotas abstract this article presents a methodology that discusses a reallocation of carbon emission quotas based on the zsg dea model also introduces the process of solving the zsg dea model in extensive detail and derives theorems 1 and 2 theorem 1 shows the equivalence in competition and the cooperation case while theorem 2 indicates the correlation between quota adjustment and efficiency change through this zsg dea model the determination of carbon emission quotas is no longer subjective and reasonable carbon emission quotas among countries can be obtained the reallocation of carbon emission quotas can not only ensure that all countries have 100 efficiencies but also help all countries gain through pareto improvement the conclusions of this paper are that most developed countries should increase their carbon emission quotas and that most less developed countries need to reduce theirs including the two most populous countries of china and india the reallocation process should be paid by selling the quotas of low efficient countries so that they can obtain funds to support their development while at the same time high efficient countries can produce more due to relaxation of environmental constraints thus achieving global pareto improvement

wind power offering strategy in day ahead markets employing demand response in a two stage plan this paper deals with wind power offering strategies in day ahead markets a new plan is proposed in which a wind power producer participates in the day ahead market while employing demand response dr to smooth its power variations in this context a new dr scheme is presented through which the wind power producer is able to achieve dr by establishing various dr agreements with dr aggregators the proposed offering plan involves two stages the first stage clears on the day ahead market the wind power producer decides on day ahead offers as well as dr agreements with the aggregator the second stage takes place on the balancing market in a successive approach the wind power producer determines its energy trading for each period until the whole day is covered additionally proper dr agreements for each period are confirmed here the proposed plan is formulated in a stochastic programming approach where its validity is assessed on a case of the nordic market

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

maximizing profit of a wind genco considering geographical diversity of wind farms uncertainty and geographical diversity of wind speeds create risk for a wind power generation company wgenco to make the maximum profit from power market trading a probabilistic approach is proposed to estimate the profit of a wgenco considering geographical diversity and uncertainty of wind speeds and market prices the objective of the optimization problem is to assist a wgenco to do the optimal bidding in market trading in order to make the maximum profit under various market and wind speed uncertainties the point estimate method pem has been improved to facilitate stochastic modeling of the aggregated power output of wind turbine generators in different locations in the problem formulation the principal component analysis pca is used to manage correlated wind speeds

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

international emissions trading with endogenous allowance choices abstract this paper compares endogenous choices of tradable and non tradable emission allowances by non cooperative countries i find that the cost savings of trading do not necessarily lead to less pollution in particular environmentally more concerned countries usually choose less allowances if these are tradable but this may be offset by the choice of more allowances on the side of environmentally less concerned countries moreover if the establishment of a trading system requires the unanimous approval of all countries there may be no agreement on trading even if it were to lead to less pollution overall conversely a trading system may find unanimous approval even if it induces more pollution

on international equity weights and national decision making on climate change abstract estimates of the marginal damage costs of carbon dioxide emissions require the aggregation of monetised impacts of climate change over people with different incomes and in different jurisdictions implicitly or explicitly such estimates assume a social welfare function and hence a particular attitude towards equity and justice we show that previous approaches to equity weighting are inappropriate from a national decision maker s point of view because domestic impacts are not valued at domestic values we propose four alternatives sovereignty altruism good neighbour and compensation with different views on concern for and liability towards foreigners the four alternatives imply radically different estimates of the social cost of carbon and hence the optimal intensity of climate policy

balancing power and variable renewables three links abstract balancing power is used to quickly restore the supply demand balance in power systems the need for this tends to be increased by the use of variable renewable energy sources vre such as wind and solar power this paper reviews three channels through which vre and balancing systems interact the impact of vre forecast errors on balancing reserve requirements the supply of balancing services by vre generators and the incentives to improve forecasting provided by imbalance charges the paper reviews the literature provides stylized facts from german market data and suggests policy options surprisingly while german wind and solar capacity has tripled since 2008 balancing reserves have been reduced by 15 and costs by 50

competitive energy storage in the presence of renewables a large fraction of new distributed generation will use renewable sources and cannot be treated as conventional generators due to high variability energy storage is a natural mechanism for absorbing variability and hence minimizing costly reliance on generator reserves we consider a simple scenario in which energy imbalances are allocated to energy storage representing either cooperation with a renewable producer or competitive operation in markets the optimal storage scheduling strategy is shown to be an inventory control like policy which through mild approximation yields affine relationships with the state variables we develop and numerically evaluate suboptimal policies that approximately incorporate the effects of correlation further approximation enables us to characterize the nash equilibria arising between generation and storage which we use to analyze strategic effects specifically we find that inefficient storage can lead to non socially optimal behavior

fairness in a tradeable permit treaty for carbon emissions reductions in europe and the former soviet union this paper evaluates the distributional implications of alternative permit allocations in a tradeable permit regime for carbon emissions reductions 20 below baseline in 2010 for a region consisting of europe and the states of the former soviet union fsu participation in such a regime is expected to hinge on the fairness of the distributional consequences we find that initial permit allocations by populationand or gdp are unlikely to induce participation by most countries of eastern europe and fsu because of the net costs involved we identify a set of initial allocations that would at least compensate these countries a fair treatment of the countries in western europe we is here one which equalizes net costs pergdp for a wide set of cost functions for carbon emission reductions the cost gains that we would reap from a tradeable permit system relative to unilateral reductions by we as a group are found to be on the order of 85 percent this would imply among other things a significant increase in we scapacity to make further emissions reductions

pricing electricity in pools with wind producers this paper considers an electricity pool that includes a significant number of wind producers and is cleared through a network constrained auction one day in advance and on an hourly basis the hourly auction is formulated as a two stage stochastic programming problem where the first stage represents the clearing of the market and the second stage models the system operation under a number of plausible wind production realizations this formulation co optimizes energy and reserve and allows deriving both pool energy prices and balancing energy prices these prices result in both cost recovery for producers and revenue reconciliation a case study of realistic size is used to illustrate the functioning of the proposed pricing scheme

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

unilateral regulation of bilateral trade in greenhouse gas emission permits this paper considers the coordination of domestic markets for tradable emission permits where countries determine their own emission reduction targets using a two country model linking such schemes is beneficial to both countries but may cause the exporting country to decrease its emission reduction target and export more permits this in turn would not only reduce the costs for both countries as less emissions have to be reduced but it also lowers the environmental benefits of the importing country one price instrument tariff and two quantity instruments discount quota to prevent the exporting country from issuing more permits are examined each instrument restricts trade and alters the terms of trade for the two countries the importing country and regulator prefers an import tariff and an import quota to a carbon discount if the exporting country releases additional permits the importing country should not try to keep total emissions constant as that would be ineffective and maybe even counterproductive instead the importing country should aim to keep the total import constant this would impose costs on the exporting country that are independent of the policy instrument an import quota would be the cheapest option for the importing country an import quota would also stress the idea of supplementary of the flexible mechanism as it increases the share of emissions reduced domestically compliance and liability issues constrain the market further however both the importing and the exporting country would prefer that the permit seller is liable in case of non compliance as sellers liability would less constrain the market

intangible resources tobin s q and sustainability of performance differences this paper tests empirically the hypothesis that the greater the intangibility of a firm s resources the greater the sustainability of its competitive advantage resource intangibility is measured by 1 tobin s q and 2 the predicted value from a hedonic regression of q on several accounting measures of intangibles sustainability is measured by the persistence of firm specific profits using a dynamic panel data regression model i find that intangibles play an effective role in sustaining a firm s competitive advantage as predicted by the resource based view of the firm however the results suggest that intangibles can also lock firms into persistent disadvantages

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

transitional restricted linkage between emissions trading schemes linkages between emissions trading systems are deemed an important element of the future climate policy landscape they are however difficult to agree and remain few and far between temporary restrictions on permit trading have potential to facilitate and gradually approach unrestricted full linkage we compare the relative merits of several link restrictions in this respect namely quantitative transfer limits border taxes on transfers exchange and discount rates and unilateral linkage to this end we develop a simple model to have a unifying framework which in conjunction with lessons we draw from real world experiences serves as a basis for a broader policy oriented discussion while quantitative restrictions seem to be the natural route to full linkage they can lead to uncertain distributional effects and weaken price signals these aspects are mitigated under a border permit tax but this policy seems harder to implement exchange rates have potential to adjust for programmes stringencies and raise ambition over time but can be challenging to select as experience corroborates unilateral linkage can be a convenient approach

wind power bidding strategy in the short term electricity market abstract this paper presents an analytical trading electricity model for wind power producers wpps in the short term electricity market in the u s this model addresses four specific uncertainties real time rt wind power generation day ahead da locational marginal prices lmps rt lmps and deviation penalty rates the model is designed to find the optimal bidding strategy to maximize the expected revenue under these uncertainties in addition this paper shows that advanced forecasting techniques could be used with the proposed bidding strategy to help wpps trade energy in short term markets a case study is presented to illustrate the effectiveness of this proposed bidding strategy and advanced forecasting techniques using a set of real data taken from a wind farm in the pjm electricity market

rolling optimization of wind farm and energy storage system in electricity markets intraday energy markets have been established in some power markets mainly because of large scale wind power integration inspired by the spanish power market this paper proposes a modified market design which contains day ahead and intraday energy bidding sections to better accommodate stochastic wind energy then coordinated operation of the wind farm wf and energy storage system ess is studied rolling stochastic optimization formulations for day ahead intraday biddings and real time operations are put forward to obtain the optimal bidding strategy of wf ess union in each bidding section to maximize its overall profit case studies and sensitivity analyses are carried out on a union of wfs and a pumped storage plant psp simulation results show that the proposed rolling optimization method can effectively utilize the updated wind power forecast data and regulation capability of ess and thus increase profit for the union prominently

industrial districts district effect and firm size the italian evidence the paper analyses the transformations that occurred in the italian industrial districts ids by empirically estimating the role of the district effect on firm performance over recent decades given their ability to manage upper level and size related business practices medium sized firms emerge as local players best able to exploit their embeddedness in the districtual system and leverage districtual assets however these effects are only present in firms belonging to the industrial specialization of the district an additional result of the empirical analysis shows that the leading role of medium sized firms is critical in younger districts where medium sized firms lead the renewal of the id and its adaptation to the changes of the competitive environment as most italian ids are specialized in traditional sectors this evidence contributes to understanding the mechanisms connecting the competitiveness of the traditional industry and its localised organizational structure the paper also provides a discussion of the future of ids including the relevance of the evolutionary stage of the district on the performance of affiliated firms and their reproducibility over time

a regional dynamic general equilibrium model of alternative climate change strategies outcomes and noncooperative equilibria this study finds that cooperative policies show much higher levels of emissions reductions than do noncooperative strategies that there are substantial differences in the levels of controls in both the cooperative and the noncooperative policies among different countries and that high income countries may be the major losers from cooperation jel h41 q4 q2 q20

wind power trading under uncertainty in lmp markets this paper presents a new model for optimal trading of wind power in day ahead da electricity markets under uncertainty in wind power and prices the model considers settlement mechanisms in markets with locational marginal prices lmps where wind power is not necessarily penalized from deviations between da schedule and real time rt dispatch we use kernel density estimation to produce a probabilistic wind power forecast whereas uncertainties in da and rt prices are assumed to be gaussian utility theory and conditional value at risk cvar are used to represent the risk preferences of the wind power producers the model is tested on real world data from a large scale wind farm in the united states optimal da bids are derived under different assumptions for risk preferences and deviation penalty schemes the results show that in the absence of a deviation penalty the optimal bidding strategy is largely driven by price expectations a deviation penalty brings the bid closer to the expected wind power forecast furthermore the results illustrate that the proposed model can effectively control the trade off between risk and return for wind power producers operating in volatile electricity markets

operational strategies for a portfolio of wind farms and chp plants in a two price balancing market in this paper we explore the portfolio effect of a system consisting of a combined heat and power chp plant and a wind farm the goal is to increase the overall profit of the portfolio by reducing imbalances and consequently their implicit penalty in a two price balancing market for electricity we investigate two different operational strategies which differ in whether the chp plant and the wind farm are operated jointly or independently and we evaluate their economic performance on a real case study based on a chp wind system located in the western part of denmark we present a comprehensive mathematical model for describing the different heat and power production units of the chp plant and suggest different ways of determining its operation in a setup with two trading floors a day ahead market and a balancing market we build a simulation framework that runs in a rolling horizon fashion so that forecasts for heat demand wind power production and market prices are updated at each iteration we conclude that the portfolio strategy is the most profitable due to the two price structure of the balancing market this encourages producers to handle their imbalances outside the market

planning carbon emission trading for beijing s electric power systems under dual uncertainties in this study a full infinite interval stochastic mixed integer programming fimp method is developed for planning carbon emission trading cet under dual uncertainties fimp has advantages in uncertainty reflection and policy analysis particularly when the input parameters are provided as crisp and functional intervals as well as probabilistic distributions the developed fimp is applied to a real case study for managing carbon dioxide co2 emissions with trading scheme of beijing s electric power system eps electric power industry is one of the major sources of co2 emission in china it is essential to accumulate relevant experience to provide a reliable basis for establishing a regional or national cet market so as to prepare for docking with the international market this is the first attempt to introduce cet scheme into beijing s eps to mitigate co2 emissions the solutions for energy supply electricity generation carbon quota allocation and capacity expansion are obtained they cannot only be used for formulating co2 reduction policies and assessing the associated economic implications in purchasing emission permits or bearing economic penalties but also facilitate analyzing various policies when pre regulated electricity generation plans and pre defined co2 emission schemes are violated