ESTIMATION OF CASH FLOWS VOLATILITY FOR RISK ANALYSIS
OF A NEW LIGNITE POWER PLANT
Leszek Jurdziak, PhD, Inst. of Mining Eng., Wroclaw Univ. of Technology, Poland, 48713206830, leszek.jurdziak@pwr.wroc.pl
Justyna Wiktorowicz, MSc, Inst. of Mining Eng., Wroclaw Univ. of Tech., Poland, 48713206851, justyna.wiktorowicz@pwr.wroc.pl
Overview
Liberalization and structural changes on electric energy markets as well as forced by politics and environmentalists regulations
regarding CO2 emissions pricing through emission trading schemes (ETS) together with the global financial crisis cause that
the production of electricity is becoming a very risky business. In atmosphere of radical requirements to ban new coal power
plants without carbon capture and storage (CCS) installations finding the finance for developing a new pit or building a new
power plant based on lignite is extremely difficult. Lack of money in banking systems due to financial crisis additionally
worsens the situation. It is especially true in Poland where electricity production is based mainly on hard coal (60%) and lignite
(35%). In effect this cheapest source of electricity must compete with other alternative sources and its profitability and safety of
investments in this new conditions have to be proved.
In this paper the authors concentrate only on power sector based on lignite (including mining), which in comparison to hard
coal sector, in his whole history in Poland never use taxpayers money in the form of government aid or donation due to it was
always profitable and has made his recent investments (e.g. development of “Szczerców” deposit or new blocks in Bełchatów
or ZE PAK power plants) based on own money and commercial credits secured by future cash flows estimates. Due to the
situation is going to be worse in next years e.g. since the year 2020 the whole decreasing limit of CO2 emission allowances will
have in Poland to be purchased on auctions it is wise to develop methodology which can estimate future cash flows volatility
from selling electricity produced from a new lignite based power plant taking into account all uncertain and risky conditions to
show how they influence the profitability and risk of such investments.
Poland has several billion tons of lignite in undeveloped resources (e.g. “Legnica” and “Gubin” deposits), which can guarantee
security of electric energy sector for over one hundred years, but it is necessary to find funds on new investments. Otherwise
existing, developed deposits will be exhausted about 2040 and Poland will loose its independency in electric energy supply.
Methods
Results of recent research (Jurdziak, 2007) has shown that in order to maximise profits from electric energy production it is
necessary to optimise joint activity of a lignite mine supplying fuel together with a nearby power plant (Jurdziak, 2008c).
Otherwise both sides of a bilateral monopoly could realise the solution, which could not be optimal in Pareto sense (Jurdziak,
2008b). New lignite mine and a power plant investment should be conducted by the vertically integrated firm due to integration
brings also other valuable benefits, which additionally can increase profitability of the whole operation (Jurdziak, 2008a).
The analysis of the future investment should start from lignite deposit evaluation, resources classification and identification of
mineable lignite reserves. As early as on this stage it has to be taken into account that joint operation and not only a mining part
of it should be considered (Jurdziak & Kawalec, 2008). Lignite price has no influence on joint profits (Jurdziak, 2007)
therefore it is difficult to depict optimal reserves and their location in 3D space based on it. Instead the influence of electric
energy price on lignite reserves should be taken into account. It is therefore necessary to design the lignite price formula which
could show its net value from the point of view of particular power plant (or rather its boilers) e.g. it should take into account
lignite productivity resulting from its quality and costs connected with environment protection (e.g. costs of ashes utilization,
SO2 removing etc.) in order to properly value any deviations from the reference lignite required by the power plant. It is more
important to properly value the differences in lignite quality than to establish the proper price level due to blending of lignite
from different faces and levels can add value to joint operations. Such formula should be used to build the value model of the
deposit which together with 3D lignite quality model should be used for designing of the optimal pit maximizing joint profits
and preparation of the optimal schedule of lignite excavation maximizing NPV of future cash flows from the sale of electric
energy. On each stage of this value creation chain of optimal ultimate energy production from lignite there are several uncertain
parameters, which can cause the variability of future cash flows increasing the risk of not attaining the required level of
profitability (Jurdziak & Wiktorowicz, 2008b).
In order to quantify this uncertainty it is proposed to use several techniques to forecast future cash flow variability including
application of conditional simulation (CS) of equally probably 3D lignite deposit models, application of Geo-Risk Assessment
(GRA) during optimal scheduling of lignite excavation and usage of Monte Carlo simulations (MCs) of economic conditions of
future electric energy production and sale including uncertainty connected with required amount and prices of allowances on
CO2 emissions under ETS (Jurdziak&Wiktorowicz, 2008). The integrated risk evaluation method has been described in
(Jurdziak & Wiktorowicz, 2008). Now this approach is presented based on the example data of the planned “Legnica” mine
supplying fuel to the proposed power station within the Foresight Project “Scenarios of the Technological Development for the
Lignite Mining and Process Industry” sponsored by the EU.
Results
Results from conditional simulation (CS) conducted in Datamine Studio 3 program and Geo-Risk Assessment (GRA) processes
build in version 4 of NPVScheduler software together with other parameters from the “Legnica-West” prospective lignite
deposits and selected distributions have been used as inputs to Crystal Ball and &Risk models created in the Excel spreadsheet.
They allowed on estimation of future cash flows (CFs) on the year-by-year basis from electricity production in proposed power
plant and its sale on liberalized energy market. Excel models contained the build in solution for the bilateral monopoly of a
mine and a power plant described in the paper (Jurdziak, 2004) and in the monograph (Jurdziak, 2007). Then several thousands
of simulations have been performed showing variability of cash flows (CFs) in each year of the optimal long-term excavation
schedule (Life of Mine plan) what allowed on the proper selection of risk adjusted discount rate (RADR) to determine the
resulting histogram of NPV. Both CFs and NPV histogram where used to estimate such measures of risk as Cash Flows at Risk
and VAR as well as probability of loss and sensitivity analysis of outputs upon changes in chosen parameters. Such results gave
much more information about risk of the analysed investment than standard statistics as expected NPV and its .
The obtained results have shown that uncertainty connected both with prices of CO2 emission allowances as well as with their
required amount substantially increases the risk of profitable energy production from lignite and decreases the size of optimal
pit lowering utilization of the lignite deposit.
Conclusions
Risk analysis of energy production from lignite should be based on the worked out solution for the bilateral monopoly model of
lignite mine and power plant (Jurdziak, 2004,2007) and observation of forecasted CFs volatility
Estimation of CFs variability can be done in an appropriate software environment allowing on exchange and integration of data.
CS together with GRA in open pit optimisation program appeared to be the objective tools, which can be used for proper
preparation of input data to Monte Carlo simulation in order to attain variability estimates of annual CFs in the optimal longterm mining schedule.
Optimisation of joint activity and preparation of strategy for long-term development of a lignite mine and a power plant allows
on substantial risk reduction.
Increase of carbon dioxide allowances prices and decrease of their limits decreases the profitability of energy production from
lignite lowering utilization of the lignite deposits.
All mentioned software is available at the Institute of Mining Engineering at Wroclaw University of Technology for
educational and consultancy purposes.
References
Jurdziak L., 2004: Tandem: lignite opencast mine & power plant as a bilateral monopoly, Proceeding of the Mine Planning and
Equipment Selection 2004, A.A Balkema Publishers, Taylor & Francis Group.
Jurdziak L., 2007: Economic evaluation of a lignite mine and a power plant operations with application of a bilateral monopoly
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logistics, competition and environment. 31st Conference of the International Association for Energy Economics. IAEE'08.
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production of electric energy out of lignite, IV Int. Conference Coal in Belgrade.
Jurdziak L., Wiktorowicz J., 2008d: Risk analysis during evaluation of profitability of energy production from lignite, IAEE
Conference in Istanbul, Turkey.
Publication sponsored by the Polish Ministry of Science and Higher Education - project N524 010 32/2086 "Economic
analysis of a lignite mine and a power plant operation in condition of uncertainty with application of bilateral monopoly
model, pit optimisation methods, game theory and real options".