Modelling Wind in the Electricity Sector

We represent hourly, regional an wind data and transmission constraints in an investment planning model calibrated to the UK and test sensitivities of least cost expansions to fuel and technology prices. Thus we can calculate the value of transmission expansions to the system. We represent limited public acceptance of wind and regional network constraints by maximum built rates per region and year. Thus we calculate the marginal value of improved planning and grid connection regimes. It is likely that some constraints will remain. Market designs that do not allow for regional differentiation to reflect transmission and planning constraints can increase overall costs to consumers

Implications of intermittency and transmission constraints for renewables deployment

We represent hourly, regional wind data and transmission constraints in an investment planning model calibrated to the UK and test sensitivities of least cost expansions to fuel and technology prices. Thus we can calculate the value of transmission expansions to the system. We represent limited public acceptance of wind and regional network constraints by maximum built rates per region and year. Thus we calculate the marginal value of improved planning and grid connection regimes. It is likely that some constraints will remain. Market designs that do not allow for regional differentiation to reflect transmission and planning constraints can increase overall costs to consumers.Investment planning model, wind power, constraint land, Network constraints.

Operational and Investment Response to Energy Prices in the OECD Manufacturing Sector

This paper estimates the vintage capital model of energy demand and examines operational and investment responses to energy prices at disaggregate level using data from five OECD manufacturing industries. Applying the model to less aggregate level data helps avoiding the distortions from exogenous structural shifts and measurement errors. The results confirm the previous findings that including capital stock vintages significantly improves the econometric model's goodness of fit. Estimated own-price elasticities of energy demand vary between 0.26 and 1.00 and are economically sound. Estimated own-price investment elasticities of energy efficiency of capital stock vary between 0.03 and 0.9. The investment response to energy prices thus varies significantly across manufacturing industries, being significant in some of them and negligible in other. The results of policy simulations for the U.K. petrochemical industry (the most energy-intensive industry in the sample) indicate that total (operational and investment) own-price elasticity of energy demand is close to one

Space and Time: Wind in an Investment Planning Model

Investment planning models inform investment decisions and government policies. Current models do not capture the intermittent nature of renewable energy sources, restricting the applicability of the models for high penetrations of renewables. We provide a methodology to capture spatial variation in wind output in combination with transmission constraints. The representation of wind distributions with stochastic approaches or an extensive historic data set would exceed computational constraints for real world application. Hence we restrict the amount of input data, and use boot-strapping to illustrate the robustness of the results. For the UK power system we model wind deployment and the value of transmission capacity

Nutzung von Pflanzenextrakten zur Kontrolle der Krautfäule (P. infestans) im ökologischen Kartoffelbau

Der Befall mit dem Erreger der Kraut- und Knollenfäule (P. infestans) hat durch frühzeitigen Verlust der Assimilationsfläche regelmäßig erhebliche Ertragsverluste im Ökologischen Kartoffelbau zur Folge. Neben einer Reihe von vorbeugenden Maßnahmen, inbesondere Wahl toleranter Sorten und Vorkeimen des Pflanzgutes (KARALUS 1995, MEINCK 1999), sind zur direkten effizienten Kontrolle derzeit nur Kupferverbindungen zugelassen. Ein weitgehend unerforschtes Potential zur Kontrolle dieses Oomyceten liegt in der Nutzung von Pflanzenextrakten, diese Wirkung wurde in Feldversuchen untersucht

Network-constrained models of liberalized electricity markets: the devil is in the details

Numerical models for electricity markets are frequently used to inform and support decisions. How robust are the results? Three research groups used the same, realistic data set for generators, demand and transmission network as input for their numerical models. The results coincide when predicting competitive market results. In the strategic case in which large generators can exercise market power, the predicted prices differed significantly. The results are highly sensitive to assumptions about market design, timing of the market and assumptions about constraints on the rationality of generators. Given the same assumptions the results coincide. We provide a checklist for users to understand the implications of different modelling assumptions

Network-constrained models of liberalized electricity markets: the devil is in the details

Numerical models for electricity markets are frequently used to inform and support decisions. How robust are the results? Three research groups used the same, realistic data set for generators, demand and transmission network as input for their numerical models. The results coincide when predicting competitive market results. In the strategic case in which large generators can exercise market power, the predicted prices differed significantly. The results are highly sensitive to assumptions about market design, timing of the market and assumptions about constraints on the rationality of generators. Given the same assumptions the results coincide. We provide a checklist for users to understand the implications of different modelling assumptions.Market power, Electricity, Networks, Numeric models, Model comparison

A Review of the Monitoring of Market Power The Possible Roles of TSOs in Monitoring for Market Power Issues in Congested Transmission Systems

The paper surveys the literature and publicly available information on market power monitoring in electricity wholesale markets. After briefly reviewing definitions, strategies and methods of mitigating market power we examine the various methods of detecting market power that have been employed by academics and market monitors/regulators. These techniques include structural and behavioural indices and analysis as well as various simulation approaches. The applications of these tools range from spot market mitigation and congestion management through to long-term market design assessment and merger decisions. Various market-power monitoring units already track market behaviour and produce indices. Our survey shows that these units collect a large amount of data from various market participants and we identify the crucial role of the transmission system operators with their access to dispatch and system information. Easily accessible and comprehensive data supports effective market power monitoring and facilitates market design evaluation. The discretion required for effective market monitoring is facilitated by institutional independence