Short-term CO₂ abatement in the European power sector

This paper focuses on the possibilities for short term abatement in response to a CO2 price through fuel switching in the European power sector. The model E-Simulate is used to simulate the electricity generation in Europe as a means of both gaining insight into the process of fuel switching and estimating the abatement in the power sector during the first trading period of the European Union Emission Trading Scheme. Abatement is shown to depend not only on the price of allowances, but also and more importantly on the load level of the system and the ratio between natural gas and coal prices. Estimates of the amount of abatement through fuel switching are provided with a lower limit of 35 million metric tons in 2005 and 19 Mtons in 2006

Considerations on the backup of wind power: Operational backup

The introduction of wind power into an electricity-generation system on a large scale brings about challenges for the evolution and operation of this system: backup for wind power becomes a necessity. This paper defines various elements that come into play when considering backup for electricity generation from wind power. The backup is split up in capacity backup and operational backup. The focus is set on the short-term, operational aspects of the backup provision. The effects of several short-term operation related parameters are defined and analysed. Most relevant parameters for the operation and needs for wind power backup are the load profiles, the wind power output profiles and the total amount of installed wind power. These are analysed by means of a Mixed Integer Linear Programming (MILP) model through two different methods for operational backup provision, comparing the incremental cost, generated by both methods. The first method applies wind power backup through a 100% provision of additional spinning reserves. The second method does not foresee any spinning reserve and relies on the balancing by the Transmission System Operator (TSO). Both methods result in different additional charges that are being affected by the said parameters. Both the wind profile and the total amount of installed wind power are positively related to the relative cost increase. The load profile is negatively correlated to this increase. The relationship between these parameters and the development of the incremental cost provides an understanding that allows finding better equilibria in the operational backup of wind power.Wind power Backup Operational Electricity-generation system Short run MILP

Impact of large amounts of wind power on the operation of an electricity generation system: Belgian case study

Wind power can have considerable impacts on the operation of electricity generation systems. Energy from wind power replaces other forms of electricity generation, thereby lowering overall fuel costs and greenhouse gas (GHG) emissions. However, the intermittency of wind power, reflected in its variability and relative unpredictability restrains the full potential benefits of wind power. The variable nature of wind power requires power plants to be ready for bridging moments of low wind power output. The occurrence of forecast errors for wind speed necessitates sufficient reserve capacity in the system, which cannot be used for other useful purposes. These forecast errors inevitably cause efficiency losses in the operation of the system. To analyse the extent of these impacts, the Belgian electricity generation system is taken as a case and investigated on different aspects such as technical limitations for wind power integration and cost and GHG emissions' reduction potential of wind power under different circumstances.Wind power Operational cost reduction Greenhouse gas Technical barriers

Impact of wind power on natural gas markets : inter market flexibility

Date of conference: 23-25 June 2010The introduction of massive amounts of intermittent wind power raises challenges for the proper balancing of the power system. For a number of reasons combined cycle gas turbines are the back-up technology of consequence. Therefore, the flexibility needs of the power generation market are actually transferred to the gas market. A first step is proposed towards a model to quantitatively study this inter market flexibility. Results of our stylised model show that wind power intermittency causes CCGT production to become very variable. Line-pack flexibility appears to be the best suited instrument to respond to this variability both in size and in frequency. More accurate power and gas systems need to be modelled to obtain practically useful results, though

SHORT-TERM CO2 ABATEMENT IN THE EUROPEAN POWER SECTOR: 2005–2006

This paper provides an estimate of short-term abatement of CO2 emissions through fuel switching in the European power sector in response to the CO2 price imposed by the EU Emissions Trading Scheme (EU ETS) in 2005 and 2006. The estimate is based on the use of a highly detailed simulation model of the European power sector in which abatement is the difference between simulations of actual conditions with and without the observed CO2 price. We estimate that the cumulative abatement over this period was about 53 million metric tons. The paper also explains the complex relationship between abatement and daily, weekly, and seasonal variations in load, relative fuel prices, and the price of CO2 allowances.CO2 abatement, electricity generation simulation, European Union Emission Trading Scheme, fuel switching

Signals from the deep: Spatial and temporal acoustic occurrence of beaked whales off western Ireland - Fig 4

<p><b>Mean Cuvier’s beaked whale detections per recording day bubble plot (right) and with standard error bars (left) for stations 1 (SE = ±0.70), 2 (SE = ±0.59), 3 (SE = ±2.61), 4 (SE = ±4.48), 5 (SE = ±1.08), 6 (SE = ±1.38), 7 (SE = ±1.35), and 8 (SE = ±1.26) off western Ireland from May to Dec 2015 (stations 1–4) and Mar to Nov 2016 (stations 3 and 5–8).</b> Results of Kruskall-Wallis tests are given and results from Tukey-Kramer multiple comparisons tests are represented by coloured means (left) with different colours denoting a statistically significant difference. *Station 8 differs from 7, but not from 3, 5, and 6.</p