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on Energy Economics |
| By: | Fabien A. Roques; William J. Nuttall; David M. Newbery; Richard de Neufville |
| Abstract: | High fossil fuel prices have rekindled interest in nuclear power. This paper identifies specific nuclear characteristics making it unattractive to merchant generators in liberalised electricity markets, and argues that non-fossil fuel technologies have an overlooked ‘option value’ given fuel and carbon price uncertainty. Stochastic optimisation estimates the company option value of keeping open the choice between nuclear and gas technologies. This option value decreases sharply as the correlation between electricity, gas, and carbon prices rises, casting doubt on whether private investors’ fuel-mix diversification incentives in electricity markets are aligned with the social value of a diverse fuel-mix. |
| Keywords: | Nuclear economics, stochastic optimisation, fuel-mix, diversification. |
| JEL: | C15 C61 L52 L94 |
| Date: | 2005–11 |
| URL: | http://d.repec.org/n?u=RePEc:cam:camdae:0555&r=ene |
| By: | Silvano Cincotti (University of Genoa DIBE); Eric Guerci |
| Abstract: | Since early nineties, worldwide production and distribution of electricity has been characterized by a progressive liberalization. The state-owned monopolistic production of electricity has been substituted by organized power exchanges (PEs). PEs are markets which aggregate the effective supply and demand of electricity. Usually spot-price market are Day Ahead Market (DAM) and are requested in order to provide an indication for the hourly unit commitment. This first session of the complex daily energy market collects and orders all the offers, determining the market price by matching the cumulative demand and supply curves for every hour of the day after according to a merit order rule. Subsequent market sessions (also online) operate in order to guarantee the feasibility and the security of this plan. The electric market is usually characterized by a reduced number of competitors, thus oligopolistic scenario may arise. Understanding how electricity prices depend on oligopolistic behavior of suppliers and on production costs has become a very important issue. Several restructuring designs for the electric power industry have been proposed. Main goal is to increase the overall market efficiency, trying to study, to develop and to apply different market mechanisms. Auction design is the standard domain for commodity markets. However, properties of different auction mechanism must be studied and determined correctly before their appliance. Generally speaking, different approaches have been proposed in the literature. Game theory analysis has provided an extremely useful methodology to study and derive properties of economic "games", such as auctions. Within this context, an interesting computational approach, for studying market inefficiencies, is the theory of learning in games. This methodology is useful in the context of infinitely repeated games. <BR> This paper investigates the nature of the clearing mechanism comparing two different methods, i.e., discriminatory and uniform auctions. The theoretical framework used to perform the analysis is the theory of learning in games. We consider an inelastic demand faced by sellers which use learning algorithms to understand proper strategies for increasing their profits. We model the auction mechanism in two different duopolistic scenario, i.e., a low demand situation, where one seller can clear all the demand, and a high demand condition, where both sellers are requested. Moreover, heterogeneity in the linear cost function is considered. Consistent results are achieved with two different learning algorithms |
| Keywords: | Agent-based simulation; power-exchange market; market power, reinforcement learning, electricity production costs |
| JEL: | C73 L1 L94 |
| Date: | 2005–11–11 |
| URL: | http://d.repec.org/n?u=RePEc:sce:scecf5:334&r=ene |
| By: | Manuel L. Costa; Fernando S. Oliveira (Operational Research and Systems Warwick Business School) |
| Abstract: | Electricity markets are being liberalised and open to private competition in several countries. These liberalized electricity markets are very complex as the interactions between demand and supply are subject to several technicalities arising from the commodity being traded: electricity. One of these technicalities is that generators cannot store electricity: this fact implies that it needs to generate its production real-time. A second problem with this market are the different generation technologies used at different levels of demand, which implies that at different times of the day different generation costs are supported to meet demand: due to ramp-rate constraints, capacity available, and fixed and start-up costs. In this paper we analyze the issue of investment and the electricity system’s long-term security in an industry where a regulator controls the short-term prices, imposing a perfect competition outcome for “low†demand hours and a price cap at times where load is shed. We look at the following research questions: a) How does the oligopolistic structure of the market interact with the value of the different technologies? b) How do players define their investment strategies? c) How do the regulatory policies affect the investment in generation? Do they work similarly under perfect competition and oligopoly? d) Can markets invest enough capacity to ensure the long run security of the market? The main results of our analysis are following: 1. The impact of a given investment on the market price is independent of the player investing. 2. The impact of an investment on price is a function of the technology in which the investment takes place and of the cycle to which the price refers to. 3. The impact of price caps on the evolution of the market structure is non-linear, it cannot be too low or too high. 4. An oligopolistic electricity market fails to deliver the needed investment unless the regulators intervene. 5. The higher the reserve margin the higher the total investment. However, this instrument by itself was not able to provide the incentive needed to ensure the long-term security of the system, as in any of the experiments analyzed the peak demand is not completely satisfied. 6. Even a slight increase in demand, due to the reserve margin, leads to important changes on the relative value of the different technologies. 7. The main task of the regulatory authorities is to define a level of capacity payments that give the necessary incentive to investment, at the minimum cost: Capacity Payments are very important in shaping the generation structure. 8. Uncertainty reduces the value of Peak plants: this result clearly contradicts any common sense in these matters, as one would expect the presence of price uncertainty to be beneficial to Peak plants. The proportion invested in baseload plants increases with uncertainty of the energy price, decreasing the investment in shoulder plant. |
| Keywords: | agent-based, electricity markets, evolution, investment, regulation, simulation |
| JEL: | C73 D43 L11 |
| Date: | 2005–11–11 |
| URL: | http://d.repec.org/n?u=RePEc:sce:scecf5:430&r=ene |
| By: | Deddy Koesrindartoto (Economics Iowa State University); Junjie Sun |
| Abstract: | In April 2003 the U.S. Federal Energy Regulatory Commission proposed the Wholesale Power Market Platform (WPMP) for common adoption by all U.S. wholesale power markets. The WPMP is a complicated market design envisioning day-ahead, real-time, and ancillary service markets maintained and operated by an independent system operator or regional transmission organization. Variants of the WPMP have been implemented or accepted for implementation in several regions of the U.S. However, strong opposition to the WPMP still persists in many regions due in part to a perceived lack of adequate reliability testing. This presentation will report on the development of an agent-based computational laboratory for testing the economic reliability of the WPMP market design. The computational laboratory incorporates several core elements of the WPMP design as actually implemented in March 2003 by the New England independent system operator (ISO-NE) for the New England wholesale power market. Specifically, our modeled wholesale power market operates over a realistically rendered AC transmission grid. Computationally rendered generator agents (bulk electricity sellers) and load-serving entity agents (bulk electricity buyers) repeatedly bid into the day-ahead and real-time markets using the same protocols as actual ISO-NE market participants. In each trading period the agents use reinforcement learning to update their bids on the basis of past experience. We are using our agent-based computational laboratory to test the extent to which the core WPMP protocols are capable of sustaining efficient, orderly, and fair market outcomes over time despite attempts by market participants to gain individual advantage through strategic pricing, capacity withholding, and induced transmission congestion. This presentation will report on some of our initial experimental findings. |
| Keywords: | Agent-based computational economics; Wholesale power market design; Learning agents |
| JEL: | L1 L5 L94 C6 C7 |
| Date: | 2005–11–11 |
| URL: | http://d.repec.org/n?u=RePEc:sce:scecf5:50&r=ene |
| By: | Ian Sue Wing (Geography Boston University) |
| Abstract: | In the U.S., the bulk of CO2 abatement induced by carbon taxes comes from electric power. This paper incorporates technology detail into the electricity sector of a computable general equilibrium model of the U.S. economy to characterize electric power’s technological margins of adjustment to carbon taxes and to elucidate their general equilibrium effects. Compared to the top-down production function representation of the electricity sector, the technology-rich bottom-up specification produces less abatement at a higher welfare cost, suggesting that bottom-up models do not necessarily generate lower costs of abatement than top-down models. This result is shown to be sensitive to the elasticity with which technologies’ generating capacities adjust to relative prices |
| JEL: | C68 |
| Date: | 2005–11–11 |
| URL: | http://d.repec.org/n?u=RePEc:sce:scecf5:21&r=ene |
| By: | Jian Zhang (EEE programme UNESCO, FEEM) |
| Abstract: | A global multi-sectoral, multi-regional computational general equilibrium model is employed to assess carbon taxes under perfect competition and monopoly. We found that regional studies of carbon taxation maybe inaccurate due to the carbon emission spillover effects. Emission taxes have stronger impacts on the economy in monopoly rather than on perfect competition in terms of magnitude. Carbon emission tax policy analysis which is based on perfect competition may also underestimate the losses of welfare compared with the case in imperfect competition. |
| Keywords: | environmental taxation, imperfect competition, Computable General Equilibrium |
| JEL: | D43 D58 L13 |
| Date: | 2005–11–11 |
| URL: | http://d.repec.org/n?u=RePEc:sce:scecf5:213&r=ene |
| By: | Seung-Rae Kim (Woodrow Wilson School Princeton University) |
| Abstract: | How is the design of efficient climate policies affected by the potentials for induced technological change and for future learning about key parameter uncertainties? We address this question using a new integrated climate-economy model incorporating endogenous technological change to explore optimal technological portfolios against global warming in the presence of uncertainty and learning. We explicitly consider the interplays between induced innovation, the stringency of environmental policies, and possible environmental risks within the general equilibrium framework of probabilistic integrated assessment. We find that the value of resolving key scientific uncertainties would be non-trivial in the face of binding climate limits, but at the same time it can significantly decrease with induced innovation and knowledge spillovers that might otherwise be absent. The results also show that scientific uncertainties in climate change could justify immediate mitigation actions and accelerated investments in new energy technologies, reflecting risk-reducing considerations. |
| Keywords: | Uncertainty; Learning; Optimal technological portfolios; Endogenous technological change; Stochastic growth model; Probabilistic integrated assessment; Carbon-free technology; Expected value of information |
| JEL: | Q28 D81 O33 |
| Date: | 2005–11–11 |
| URL: | http://d.repec.org/n?u=RePEc:sce:scecf5:54&r=ene |
| By: | Hannes Egli (Institute of Economic Research (WIF), Swiss Federal Institute of Technology Zurich (ETH)) |
| Abstract: | In recent years, extensive literature on the Environmental Kuznets Curve lead- ing to optimistic policy conclusions has attracted great attention. However, the underlying cross-section estimations are not very reliable. Accordingly, this contribution uses time series data for a single country with dependable data quality : Germany. The results of the traditional reduced-form specification do not support the EKC hypothesis. However, with a specification in the tradi- tion of error correction models, which are more appropriate in the presence of non-stationary time series, it is found that the typical EKC pattern can be confirmed. |
| Keywords: | Environmental Kuznets Curve, Error Correction Model, Time Series Data |
| JEL: | Q00 Q20 |
| Date: | 2004–09 |
| URL: | http://d.repec.org/n?u=RePEc:eth:wpswif:03-28&r=ene |
| By: | Simone Valente (Institute of Economic Research, ETH Zurich) |
| Abstract: | Conflicts between optimality and sustainability are typical in the literature on sustainable development. Using the 'capital-resource' growth model, Pezzey and Withagen (1998) have proved that if natural resources are exhaustible, the time-path of consumption is single-peaked, declining from some point in time onwards. This paper extends the model to include technical progress, resource renewability, extraction costs and population growth. The main result is that, for any constant returns to scale technology, optimal paths can be sustainable only if the social discount rate does not exceed the sum of the rates of resource regeneration and augmentation. The development of resource-saving techniques is crucial for sustaining consumption per capita in the long run, whereas capital depreciation and extraction costs are neutral with respect to this sustainability condition. |
| Keywords: | Optimal Growth, Renewable Resources, Sustainable Development, Technological Progress |
| JEL: | Q20 O11 O30 |
| Date: | 2004–04–08 |
| URL: | http://d.repec.org/n?u=RePEc:rtv:ceisrp:54&r=ene |
| By: | Lucas Bretschger (Institute of Economic Research (WIF), Swiss Federal Institute of Technology Zurich (ETH)); Sjak Smulders (Tilburg University, Department of Economics) |
| Abstract: | Traditional resource economics has been criticised for assuming too high elasticities of substitution, not observing material balance principles and relying too much on planner solutions to obtain long-term growth. By analysing a multi-sector R&Dbased endogenous growth model with exhaustible natural resources, labour, and knowledge capital as inputs, the present paper addresses this critique. We study transitional dynamics and the long-term growth path and identify conditions under which firms keep spending on research and development so that growth is sustained. We demonstrate that long-run growth can be sustained under free market conditions even when elasticities of substitution between man-made inputs and resources are low. |
| Keywords: | Growth, non-renewable resources, substitution, investment incentives, endogenous technological change, sustainability |
| JEL: | Q20 Q30 O41 O33 |
| Date: | 2004–06 |
| URL: | http://d.repec.org/n?u=RePEc:eth:wpswif:03-26&r=ene |