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A Techno-economic Analysis of Wind Generation in Conjunction with Compressed Air Energy in the Integrated Single Electricity Market (Mechanical Project)

ABSTRACT:

The Integrated Single Electricity Market (I-SEM) is the proposed   wholesale electricity market for Ireland and it is intended to replace the current Single lectricity Market (SEM) by 2018.

Subsequently, substantial modifications will be required to the SEM and this has led to significant uncertainty for stakeholders. The SEM currently features no forecast risk for renewables such as wind and there isno concept of balance responsibility. Under the I-SEM, wind generation will be exposed to forecast risk and the equirement to be balance responsible.

The use of Compressed Air Energy Storage (CAES) could represent a better system configuration which would reduce the reliance on  expensive generation for system balancing and reduce the financial  risk to wind generation. Thus, the aim of this research was to estimate the economic performance of wind generation with and without CAES from a private investor’s perspective in the I-SEM.

More specifically, the Balancing Mechanism (BM) System Marginal  Prices (SMPs), total generation costs and CO2 emissions  were  estimated  from  a  systems perspective under the I-SEM.  The approach was to quantify the SMPs, total generation costs and CO2 emissions for each scenariousing a validated unit commitment and economic dispatch PLEXOS model of the Irish and  British lectricity markets under the  I-SEM structure.

The private Net Present Value of wind generation was then  evaluated using the collected financial and technical project data  and the electricity price and generation outputs from the I-SEM model for each scenario. The economic viability of CAES from a  systems perspective was then assessed using techno-economic data for the CAES plant and outputs from the I-SEM model. Results revealed that the SMPs increase between the day-ahead and BM markets for the both scenarios.

Moreover, the SMPs are most sensitive to the fuel and carbon prices, v while the remaining input parameters have a more modest impact. A comparison of the total generation costs revealed that the inclusion of the CAES plant in the I-SEM led to savings of €8 million over the year 2020.

The CO2 emissions were estimated for each scenario and a modest  emissions increase of 1% (0.1 MtCO2) between the BAU and BAU+CAES scenarios occurred due to the addition of the CAES plant.  The NPV of wind generation was estimated as €1.91bn and €2.01bn for the BAU and BAU+CAES scenarios, respectively. The CAES plant receives a positive net revenue of €21.6 million over the year and is considered economically viable given that it ecoversit costs from the revenue of selling energy to the I-SEM.

 LITERATURE REVIEW

Introduction:

This chapter first provides a brief history of global, European  and Irish energy policies. It then describes the current and  proposed Irish and  British electricity market structures. The global and national evolution of wind power and wind integration  is described in Sections 2.2 and 2.3. A review of modelling  software tools for power systems and electricity markets is provided in Section 2.4.Finally, a summary is provided of the current-state-of-the-art as it applies to the research area.

Wind Power:

This research is primarily concerned with the techno-economic  modelling of wind power integration and large scale energy storage on the Irish power system. The following subsections therefore provide an overview of the global and national evolution of wind power in terms installed wind capacity, growth of wind turbine sizes and the associated challenges with wind power integration.

Growth in Size of Wind Turbines Since 1980 and Possible Future Sizes.

Growth in Size of Wind Turbines Since 1980 and Possible Future Sizes.

Energy Storage Technologies:

This section provides a high level overview of the most common  energy storage technologies including the irtechnical and economic  characteristics. Energy  storage technologies can be classified  into four main categories based on the type of energy stored.They consist of mechanical, electrical, thermal and chemical energy storage technologies.

The available data such as power and energy rating, efficiency, capital cost, ifetime, response and charge time and maturity of each energy storage technology were collected  from literature and are summarised. Mechanical energy storage technologies can be achieved in forms of potential and  kinetic  energy. Potential energy storage consists of CAES and PHES, while the kinetic energy storage is in flywheels.

Layout of a PHES Plant

Layout of a PHES Plant.

Modelling Software Tools:

The key to performing reliable analyses of technologies such as energy storage in high renewable energy systems is the use of modelling software tools which can produce credible results when modelling a well-defined energy system.

The main proprietary modelling software tools used in different countries for power  systems and market modelling are PLEXOS, EMCAS, EnergyPLAN, WASP  and WILMAR.

THE COST OF WIND ENERGY

Introduction:

As wind energy becomes a more important source of electricity generation in global electricity markets, it is vital to identify the major trends and drivers of wind energy costs (i.e.capital  investment, operation and maintenance and financing costs).

A better understanding of the trends and cost drivers of the past, present and future cost of wind energy both in  Ireland and worldwide would help contribute to the national and global policy debate in relation to the development and deployment of wind energy, respectively.

Methodology:

The Sustainable Energy Authority of Ireland’s wind farm database containing installed capacity and year of connection for individual wind farms was used as a starting point to create a detailed database of installed wind energy projects in Ireland between
2007 and 2012..

Additional technical data were obtained from the  Irish Wind Energy Association (IWEA) including wind turbine make and model. Performance data such as full load hours and capacity factors were calculated based on aggregated county wind energy production data provided by Eirgrid.

Wind Project Features:

Onshore wind energy projects in Ireland are generally in the form  of clusters and range from 2 to 19 wind turbines. Since 2007, the average wind project size in Ireland has remained between 10 MW  and 17 MW.

The largest wind farms of between approximately 40 MW and 60 MW were installed between 2008 and 2011. The largest wind project size is 57 MW with 19 wind turbines. The average wind project size was largest in 2008 and 2009 with 17 MW and 15 MW, respectively.

Wind Project Performance

The wind resource in Ireland is considered to be one of the best in the world making it a key location for wind project investment and development. The full-load hours and capacity factors for wind projects installed from 2007 to 2012.

These are based on the  performances in 2013 of all projects built in each of the years 2007–2012. The 2013 wind production output data were corrected  using a production index which normalized 2013 output to take  account of the wind resource and wind project outage characteristics for that year.

Investment Costs:

The capacity-weighted average investments costs of Irish wind projects ranged from €990/kW to €1,658/kW (2012 prices) between 2007 and 2012. Overall the cost trend was upwards over the period, although in 2011 average costs fell. It did not prove possible to obtain a breakdown of the individual cost components of wind projects investment costs.

However, empirical evidence from the  Irish wind energy industry suggests that wind turbine and civil works costs(i.e. due to reduced demand in Irish construction market) may be declining, resulting in an overall decrease in investment costs.

Operations and Maintenance Costs:

There is very limited published data on the operation and maintenance (O&M) costs of wind projects in Ireland and it did not prove possible to obtain reliable O&M costs for individual wind projects.

Average annual fixed O&M costs for Irish wind projects were obtained from several sources including financial reports from the Irish Companies Registration Office(i.e. annual returns containing operating cost data as cost of sales and administration costs),wind industry experts, wind plant O&M providers, and literature.

Financing costs:

During the period 2007–2012, there were a limited number of active lenders for wind projects in Ireland as a result of the great recession and a national financial crisis. Due to the financial  crisis, lenders have been very selective in the project types and  project developers they have financed. There is limited published data on financing costs for Irish wind projects and it did not prove possible to obtain these costs for individual projects.

BASE MODEL

Introduction:

In this chapter, the methodology implemented for the 2012 PLEXOS base case model is presented, which aligns with steps three and  four of the research methodolog. Initially a representation of the SEM and BETTA market in 2012 was created in PLEXOS as the base year model given that detailed data were available for that year.

PLEXOS as outlined is an integrated energy software tool used for power and gas market modelling worldwide. PLEXOS has been used  extensively by industry and academia for policy analysis and  development in both Ireland and the UK.

Base Model Description:

A number of publicly available sources were used for the creation  of the 2012 PLEXOS base model. The CER validated forecast model of 2011-2012 was used as a starting point from which the 2012 PLEXOS model for this analysis was developed.

The 2012 model was populated with the individual generator technical and commercial characteristics which have signed agreements and confirmed dates to connect to the SEM.

I-SEM MODEL

Introduction:

This chapter presents the methodology implemented for the 2020 PLEXOS I-SEM model, which aligns with step five ofthe research  methodology. The validated 2012 PLEXOS base model from used as a starting point from which the 2020 I-SEM model for the analysis in this thesis was developed. The validated 2012 base model was  extended to 2020 given that detailed representative data were available for that year. This provided some certainty regarding  the model assumptions and scenarios.

The BETTA market design in the 2020 model was kept the same as in the 2012 model but with a projected generation portfoliofor 2020.  Two model scenarios are considered; Business as Usual (BAU) and BAU+CAES containing a CAES plant as an additional generator,  which are setup in the I-SEM model. A number of model sensitivities are also carried out. The following subsections describe the I-SEM model, model assumptions, model scenarios, CAESplant representation and model sensitivities.

RESULTS AND DISCUSSION

This chapter presents and discusses the main results for this  research, which aligns with the specific research objectives as outlined. The 2020 I-SEM model described was used to simulate the main results presented in this chapter. Two model scenario results  are presented; Business as Usual (BAU) and BAU+CAES containing a CAES plant as an additional generator in the I-SEM. The generation output mix, wind curtailment, system marginal rices, total generation costs and CO2 emissions are initially presented and discussed.

The NPV of wind generation is then assessed using cost data from as well as SMP and generation outputs from the I-SEM model for each scenario. An economic assessment of the CAES plant from systems perspective is  also  presented. Finally, sensitivity analysis  results for the key I-SEM  model input parameters are presented.  The following sections present and discuss the results in more detail.

CONCLUSIONS

The requirement for the I-SEM has arisen due to the Europeannion’s Third Energy Package. The current SEM requires substantial modifications to implement the proposed I-SEM design. The detailed I-SEM design is currently ongoing, which has the potential to cause increased uncertainty for certain stakeholders. Under the I-SEM, wind generation will be exposed to forecast risk and the requirement to be balance responsible.

The use of a CAES plant could represent a bettery stem configuration which would reduce the reliance on expensive generation for system balancing and reduce the financial risk to wind generation.

A review of current literature revealed that very limited up to  date technical and financial data for Irish wind energy projects currently exists and no extensive analyses of the I-SEM design have been conducted to date. This research collected and analysed the technical and financial data from Irish wind energy projects.

Furthermore, the economic performance of wind generation with respect to balance responsibility in the I-SEM with and with out CAES from a private investor’s perspective was evaluated using the collected data and the I-SEM model.

More specifically, the system marginal prices, total generation costs and operational CO2 emissions were estimated from a system’s perspective using the I-SEM model. The main trend observed for Irish wind projects based on the collected data was the increase in wind turbine capacity rating coinciding with increased rotor diameter and hub heights between 2007 and 2012.

However, based on a capital cost of €733/kW for the CAES plant and annual net revenues of €21.6 million; the simple payback period is less than 10 years. It would be a private investor’s ecision if the investment exposure period of 10 years is acceptable and it remains for further research to study the additional revenue to be gained from the DS3 systemservices and CRMpayments.

Source: Dublin Institute of Technology
Author: Brendan Cleary

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