The effect of wind energy in the electricity system IESIS promotes the principle that, before proceeding with any policy for the electricity system, comprehensive.

Slides:



Advertisements
Similar presentations
Leaders in the design, implementation and operation of markets for electricity, gas and water. Portfolio Generation Investment Under Uncertainty Michael.
Advertisements

Transmission Capacity to Accommodate a Mixed Background of Generation Keith Bell and Dusko Nedic University of Strathclyde/TNEI Services Ltd. August 2007.
PERFECT COMPETITION Economics – Course Companion
Will CO2 Change What We Do?
Sensitivity Analysis In deterministic analysis, single fixed values (typically, mean values) of representative samples or strength parameters or slope.
Project Discovery Transmission Workstream, 4 March 2010 Ben Woodside.
Renewable Targets and Policy Linda Pooley Head of Renewable Energy Technology and Investment Scottish Governmnet.
22 April 2010 EWEC 2010 Warsaw2 Jesper Munksgaard Ph.D., Senior Consultant Merit Order Effect of Wind Power – Impact on EU 2020 Electricity Prices.
Bruce Mountain Director Market power and generation from renewables: the case of wind in the South Australian electricity market Presentation to IAEE 35.
Example 14.3 Football Production at the Pigskin Company
EPIDEMIOLOGY AND BIOSTATISTICS DEPT Esimating Population Value with Hypothesis Testing.
Electrical Billing and Rates MAE406 Energy Conservation in Industry Stephen Terry.
Methodologies for Quantifying Energy Security in the Power Sector William Blyth 24 th April 2005.
CHAPTER 6 Statistical Analysis of Experimental Data
Inference.ppt - © Aki Taanila1 Sampling Probability sample Non probability sample Statistical inference Sampling error.
Turning the wind into hydrogen: Long run impact on prices and capacity
Carbon Storage Mitigating Climate Change? Will this work? Is it too late?
Arnoud Kamerbeek CEO DELTA NV Dutch Energy Day 2015 Amsterdam, June 25th 2015 The decarbonisation of the power sector could and should be faster and cheaper.
Keith Tovey M.A., PhD, CEng, MICE Energy Science Director: Low Carbon Innovation Centre Marcus Armes CRed Climate Change; Renewable Energy: Hard Choices.
Johnthescone The IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation.
Financing new electricity supply in the UK market with carbon abatement constraints Keith Palmer 08 March 2006 AFG.
The impacts of hourly variations of large scale wind power production in the Nordic countries on the system regulation needs Hannele Holttinen.
SUSTAINABLE ENERGY REGULATION AND POLICY-MAKING FOR AFRICA Module 13 Energy Efficiency Module 13: SUPPLY-SIDE MANAGEMENT.
Electricity Co-operation in North America: Effect on Price Electricity Co-operation in North America: Effect on Price.
National Renewable Energy Laboratory Innovation for Our Energy Future * NREL July 5, 2011 Tradeoffs and Synergies between CSP and PV at High Grid Penetration.
McGraw-Hill/IrwinCopyright © 2009 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 9 Hypothesis Testing.
The Energy Challenge Farrokh Najmabadi Prof. of Electrical Engineering Director of Center for Energy Research UC San Diego November 7, 2007.
Electric Generation Reliability Remarks Before the Pennsylvania Public Utility Commission 2011 Summer Reliability Assessment Meeting June.
THE CHALLENGES OF EUROPEAN ENERGY SECURITY Jiří Feist, CEZ Group.
Results of Geothermal Power Survey of Electric G&T Cooperatives Robert Putnam, CH2M HILL Bob Gibson, NRECA Steve Lindenberg, Lindenberg Consulting.
1 Comparison of energy systems: On methods, parameters and system boundaries Leif Gustavsson Mid-Sweden University September.
Fundamentals of Data Analysis Lecture 4 Testing of statistical hypotheses.
ESPON Project TERRITORIAL TRENDS OF ENERGY SERVICES AND NETWORKS AND TERRITORIAL IMPACT OF EU ENERGY POLICY Álvaro Martins/Luís Centeno CEEETA Research.
Alliance for Rural Electrification 2008 EUROPEAN LPG CONGRESS LPG – RES: A Win-Win Partnership May, Milan, Italy.
TYNDP SJWS #3 Demand TYNDP – 3 rd SJWS 08 March 2012 ENTSOG offices -- Brussels.
CHAPTER 16: Inference in Practice. Chapter 16 Concepts 2  Conditions for Inference in Practice  Cautions About Confidence Intervals  Cautions About.
Shutting Down Nuclear Power Plants: Economic and Environmental Impacts 15 June 2011 Professor Paul Fischbeck Carnegie Mellon University
Ensuring the delivery of secure low carbon energy David Green Chief Executive, UKBCSE.
10.2 Tests of Significance Use confidence intervals when the goal is to estimate the population parameter If the goal is to.
Generation Portfolio Options Study Philip O’Donnell Manager, Generation Analysis 14 October 2009.
DO ELECTRICITY MARKETS INTERNALISE SUPPLY RISK? DAVID PEARCE.
Gile Sampling1 Sampling. Fundamental principles. Daniel Gile
Johnthescone The IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation UN Climate Change Conference June 2011 Bonn, Germany, 7.
Copyright © Cengage Learning. All rights reserved. 8 Introduction to Statistical Inferences.
Balanced Portfolio for Reliable Electricity System YES Inc. Brief Assessment.
Hypothesis Testing An understanding of the method of hypothesis testing is essential for understanding how both the natural and social sciences advance.
Johnthescone The IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation.
Overview Wind Energy is currently the fastest renewable power source within our reach. Through this form of energy, the wind’s kinetic force is transformed.
1 Open University Integrating Renewables Conference 24 January 2006 Wind power on the grid… What happens when the wind stops blowing? David Milborrow
The use of heat pumps in district heating systems Joe Grice Energy capital projects manager 24/11/2015.
Combined Heat and Power in Copenhagen Copenhagen’s CHP system supplies 97% of the city with clean, reliable and affordable heating and 15% of Denmark’s.
Copyright © 1998, Triola, Elementary Statistics Addison Wesley Longman 1 Assumptions 1) Sample is large (n > 30) a) Central limit theorem applies b) Can.
Economic Assessment of Implementing the 10/20 Goals and Energy Efficiency Recommendations – Preliminary Results Prepared for : WRAP, AP2 Forum Prepared.
SHP – Columbia University
Resource Analysis. Objectives of Resource Assessment Discussion The subject of the second part of the analysis is to dig more deeply into some of the.
EG, EPS, Rome, EU-wide studies on the integration of renewable energies in the electricity grid F. Wagner, IPP Greifswald 1 Exemplified first.
Fundamentals of Data Analysis Lecture 4 Testing of statistical hypotheses pt.1.
Are Government Attempts to Reduce the Impact of Climate Change Beneficial or Harmful to UK Firms? To see more of our products visit our website at
World Energy and Environmental Outlook to 2030
Chapter 9 -Hypothesis Testing
RENEWABLES AND RELIABILITY
GSR022: Review of Security and Economy Required Transfer Conditions
What is POWERBALANCE?.
Combined operation of different power plants PREPARED BY : Priyanka Grover Btech (EE) SBSSTC,FZR.
penetration of wind power
Additional clarifications on economic and adequacy running hours
How is 100% Renewable Energy in Japan Possible by 2020?
An integrated assessment model: the global CLEWS
The need for a systems approach
Jim Mcintosh Director, Executive Operations Advisor California ISO
Presentation transcript:

The effect of wind energy in the electricity system IESIS promotes the principle that, before proceeding with any policy for the electricity system, comprehensive independent assessments should be carried out. This would significantly reduce the risk of unsatisfactory outcomes This presentation explains the serious difficulties involved in introducing wind generation to the system. For more information about the IESIS stance on how policy for the electricity system should be formulated see:

It is being assumed that: (a) the increasing amounts of wind energy in the electricity system will be good for security of supply and (b) wind energy will be cheaper than from other sources. We show here that these assumptions are not valid. The effect of wind energy in the electricity system

Preliminary It is important to note that we avoid making any statement about what the electricity generation mix should be. We do say that that the technical complexity of the electricity system needs to be recognised and that whatever decisions are made about it should be based on the most reliable and comprehensive information that can be assembled.

This assumption is false because of the deeply intermittent nature of wind power generation. Some people assume that because of the increase in electricity generation capacity in Scotland, security of supply will not be a problem, and that we will have a surplus of electricity production that can be exported. Security of supply - is the risk that demand for electricity will exceed generation. We present evidence to support this conclusion. Security of supply

Synoptic chart at 0000UTC 25 July 2014 The chart shows the atmospheric pressure over Europe on 25 July 2014 When the isobars (lines of equal pressure) are close together the wind is strong. For example there were strong winds off the coast of Labrador. Over the whole of Europe the isobars were widely spaced. This indicates low wind speeds. There was very little ‘good wind’ in Europe at that time. This is not a rare occurrence Low wind across Europe It also happens in winter at times of peak demand

The diagram shows the generation used to meet peak demand on 7 th December Very low temperatures were experienced that day. The GB demand was met, but only just. The generation is expressed as a % of the installed capacity for that source. Other sources of power were working hard to meet peak demand. Wind was only producing 5% of its capacity. Low wind during a winter freeze-up

Probability density These are just two observations. One cannot draw general conclusions from a small sample. Probability analysis is needed. The argument which follows is rather technical but (1) the intermittency of wind power cannot be well understood in the absence of technical arguments, (2) it is not necessary to have a full understanding of probability density to follow the argument and (3) the basic theory of probability distribution is not rocket science. It is covered in high school curricula. This diagram shows the probability densities for wind (red), for demand (blue) and for thermal generation (black)

Thermal generators are mainly coal, gas and nuclear. Some oil generation is used at times of peak demand. Nuclear Coa l Gas Thermal generation

Probability density The black curve is the pdf for thermal generation The red curve is the pdf if the only generation available was 77 GW of wind power The horizontal axis of the diagram is power capacity for the GB electricity system with a maximum of 77 Gigawatts (GW) The blue curve is the pdf for demand The vertical axis represents the probability density function – the pdf. It is a probability rate - the probability per GW of power. It is based on data from a range of wind farms in the GB system The demand and the thermal generation curves are ‘normal distributions’ – the most common type of pdf

In other words, if there were only wind energy being generated, there would be a one in five chance that the lowest demand would be met. The probability of meeting the highest demands would be much lower. For example if you want to know the probability that the wind generation will be equal to or greater than 40 GW you calculate the area under the pdf from the 40 GW value to the right hand end of the curve – the hatched area shown. This gives a probability of about 20% Probability density

The rule for security of supply is that the generation curve must be mainly to the right of the demand curve. Problems with meeting demand arise where the curves overlap Therefore to improve security of supply you want to push the generation curve to the right. If you replace thermal with wind, the distribution for the combination will move to the left. This will increase the overlap and hence increase the risk of demand not being met. No one suggests that we should only have wind in the system but the diagram indicates the scale of the intermittency problem with wind. So how much thermal generation can be replaced by wind and still maintain security of supply? The answer is: very little.

Wind power is therefore deeply unreliable. The chance of it being at the level that you want, when you want it is very low. A glance at the diagrams of probability density confirms this. To maintain security of supply, reliable generation is essential. Thermal generation has the required degree of reliability and therefore must be available for security of supply. The pdfs for wind power vary around the country and from year to year but they all have the same basic shape - the most likely levels of generation are towards the low end of the range. Note that hydro power is very good for helping to meet spikes in demand but we do not have and cannot have enough to significantly replace thermal generation. Probability density

Cost of wind energy Wind energy is the main renewable source that is being used to ‘go green’ and therefore its cost is a critical factor in the price of electricity. Claims are being made that the cost of wind energy is coming down and will soon be competitive with conventional generation. This cannot be so.

Cost of wind energy The diagram here shows estimates of levelised cost for coal, nuclear, gas, onshore wind and offshore wind. Note that these are estimated costs and not estimated prices. The latter will be higher. Levelised cost is a method of estimating the cost of different generation types. It is not the best method but it gives an indication of the relative costs The estimate for onshore wind has a basic cost of £112/MWhr. This covers capital, operational costs, etc. The extra integration cost for onshore wind is estimated to be £74/MWhr giving a total estimate of £186 for or onshore wind.

Integration costs Where do the integration costs come from? We have already shown that wind generation should not displace thermal generation if security of supply is to be maintained. Having two sets of generators available when previously one set was needed cannot be anything other than expensive. This is backup generation that has corresponding backup cost. When thermal generators are used to to cope with intermittent input from renewables they do not operate efficiently. This also adds to cost. It is called balancing cost Also renewable generators are often installed in remote places needing extra transmission facilities. This adds extra transmission cost.

Cost of wind energy Based on an index value for the levelised cost of coal, nuclear and gas as 1, the wind cost estimates are very roughly: Generation Index Coal, nuclear, gas 1 Onshore wind (basic) 2 Onshore wind + integration 3 Offshore wind + integration 4 The basic costs are in general agreement with those from other reports. We know of no other estimates of integration costs for wind power for the GB system and therefore cannot make a comparison. The integration cost estimates presented here are based on 28 GW of wind capacity in the GB system.

Double whammy of intermittency on cost of wind energy The main reason why the basic cost of wind energy is high is because wind generators operate with low load factors. The load factor is the ratio of the energy produced by the turbine over a period (normally one year) and the amount of energy it would produce if it ran continuously at its maximum capacity for that period. The load factors for onshore wind turbines tend to be less than 30% and for offshore a bit over 30%. Thermal generators are capable of having load factors in the range 70% to 85%. The low load factor for wind generation is due to intermittency of the input power. Intermittency of wind power Causes low load factors Causes basic costs to be high Makes it unsuitable for addressing security of supply Causes integration costs to be high

Double whammy of intermittency on cost of wind energy The intermittency of wind causes the need for backup power and balancing power that are major contributors to the cost of integration. Intermittency of wind power Causes low load factors Causes basic costs to be high Makes it unsuitable for addressing security of supply Causes integration costs to be high

Cost of wind energy Important conclusions that we can draw from these estimates are: (a) The cost of wind energy will not come down, it can only go up. (b) Having cheap electricity from wind energy does not appear to be achievable using existing technology. (c) The need to carry out cost estimates for the electricity system using the most reliable methods available is evident.

Reduction in CO 2 emissions When thermal generators are used to maintain security of supply to cater for wind intermittency, they operate inefficiently. Therefore they use more fuel and emit more emissions than they would otherwise Therefore as well as extra costs to the system, there are system emissions due to wind power intermittency. These are not easy to calculate and we are not aware of any report that provides estimates of them for the GB system. Calculations for other countries indicate that they can be important.

Conclusion There are many unintended consequences of introducing renewable energy in general, and wind energy in particular, to the mix of electricity generation. Having high cost electricity that is unreliable is bad for industry, bad for business, bad for everyone. When introducing any type of generation to the system it is important to do it with open eyes.

What should be done? The fundamental problem in planning for the electricity system to reduce CO 2 emissions - this is a worldwide problem - is that decisions are being made without investigating their unintended consequences. A professional approach to electricity planning would be: 1.Decide on a standard for security of supply - e.g. that the risk of supply not meeting demand would only occur 4 times in 100 years. Seek to ensure that any planned mix of generation would be in accord with the standard. 2.Consider a range of options for the generation mix and develop information about all their expected positive features and all their expected negative features. Compare the options against a set of criteria that would include cost, green objectives, health and safety, etc. 3.Then make informed decisions. Would that be a sensible way forward?

PDFs for wind GB and Scotland

The pdf for wind for Scotland is only marginally less unsatisfactory than the GB pdf. Low wind speeds often correlate across the whole of GB but strong winds do not. The bigger the area considered the less the high winds will correlate. Scotland is a smaller country and does have higher winds especially in the Outer Isles and the Northern Isles. But that does not add up to the wind being a good resource for meeting any demand in Scotland.

PDFs for wind GB and Scotland This chart shows the pdfs for wind and a pdf that one can get with thermal generation. For security of supply this is the needed probability distribution.

Risk to GB Security of Supply

This chart shows the an estimate of risk to security of supply prepared by Colin Gibson. Pre-privatisation the acceptable level of risk was considered to be 4% i.e. that in 4 years out of one hundred there would be a failure to meet demand, This estimate shows that the present risk is double that level and that by 1924 it would be 40% i.e. there might be failures to meet demand in 2 out every five years. It is not necessary to have this level of risk. The technology exists to keep to an acceptable level.

Winds speed and turbine characteristics

This diagram show why wind turbines have low load factors. It is based on wind speed data from airports across GB. Just when the turbines need good wind speeds to produce better power output is where the likelihood of having that starts to significantly decline.