markets are facing three challenges:
with more cross-border trade, especially of electricity,
Integration of large amounts of
variable, only partly predictable renewable energy with low marginal
Investors are confronted with higher
risk and uncertainty, partly as a consequence of market liberalisation
and partly because of the two above mentioned issues.
Moreover, the Danish Government has a
long-term target of abandoning the use of fossil fuels. Altogether, these
issues point to a future energy system that will be significantly different
from the present. Over the next 10-20 years, Danish investments in new
technologies and systems will amount to billions of kroner, and wrong
decisions may be fatal for companies and society.
Therefore, to perform proper analyses and
give sound recommendations, methods and models describing energy systems
need development and improvement. This project focuses on methods and models
related to electricity demand and supply. However, as electricity is part of
the total energy system, models, methods and analyses need to integrate
other parts of the energy system. Further, analyses include incentives and
policy related issues.
By means of statistical analyses and
econometrics, hourly electricity demand and production such as wind power
production are analysed and modelled. Along the same lines, possibilities
for hourly demand response are identified and wind power forecasts are
improved. Using stochastically varying forecasts for demand and wind power
production as input, models for both operation and investment under
uncertainty are developed. The methodology relies on stochastic programming
modelling and real options analysis. Analysis of incentives and policy
instruments are based on economic theory. Finally, overall energy systems
and markets are analysed using scenario-analyses.
objective is to develop and improve methods and models used for energy
systems analysis and planning to better reflect the large changes in future
energy systems and to use the models to analyse technical options, economic
incentives, and policies related to both demand and supply of electricity.
In particular, the models are used to address the challenges of a fossil
free energy system.
The main results of the project
decision support tools for operation scheduling and investment
planning under uncertainty.
interactions between uncertainty in electricity demand and renewable
power production and electricity system flexibility.
recommendations for an efficient future electricity system design.
Models and analyses
of hourly demand for electricity.
representation of stochastic variations of wind power production in
energy system models.
programming and real options models for operation scheduling and
investment planning under uncertainty.
incentives and policies for deployment of renewable energy.
Economic and system
evaluation of alternative power market designs.
At least 20 articles
published in international peer-reviewed journals.
meetings, a seminar, and at least 10 presentations at inter-national
Innovative value, impact and relevance of the
With increases in
deployment of renewable energy, extended electricity system flexibility,
additions to international transmission capacity and power market
expansions, the future electricity system will differ significantly from the
current. To cope with the differences, it is necessary to extend existing
and develop new models, firstly for prediction of electricity demand and
renewable power production, and, secondly for decision support in operation
scheduling and investment planning. These models are suitable for analysis
of incentives, policies and market design and for developing scenarios for
future electricity systems. New contributions include electricity demand
forecasts with an hourly resolution, stochastic variations in both demand
and supply forecasts, the development of short-term and long-term stochastic
decision support tools that take into account uncertainty, demand
flexibility, flexible production technologies, timing of investments and
finally the analysis of market design under such conditions. The aim is an
ability to assist in real-life operation and planning and to have a proper
basis for technology and policy recommendations. The target group is the
Danish Energy Authority, the Danish TSO, and power producers participating
in the power market.
The projectís methodology and results
project is divided into six scientific work packages (WP's) shown in the
WP1 seeks to model electricity demand with
an hourly resolution. This is required for analyses of demand flexibility
and has become possible with the introduction of hourly metering. WP2 aims
to forecast stochastic variations in both demand and renewable supply. WP3
and WP4 consider short-term and long-term challenges regarding operation and
investment within a future energy system taking into account uncertainties
and stochastic variations in demand and supply and taking both a social and
a company perspective. WP5 analyses incentives, markets, and policy
instruments for consumers, investors, and producers of electricity. Finally,
WP6 links the electricity system and other parts of the energy system in
hourly electricity demand
This WP is based on Adam/Emma and data for
hourly consumptions by categories of consumers. Emma is an econometric
state-of-the-art model linked to the macro-economic model Adam and is used
by the Danish Energy Authority and Energinet.dk for projections and energy
planning. Emma gives annual forecasts of energy consumption by categories of
consumers and types of energy.
From hourly meters, the Danish Energy
Association collects data for hourly electricity consumption by categories
of consumers. By using these data the project will develop hourly
consumption profiles, quantiles and peak demand and use econometrics to
analyse consecutive hourly demands by categories of consumers. Finally,
demand from neighbouring countries will be analysed using hourly data from
the Nord Pool and German power exchanges.
variation in wind, solar production and power loads
Today several methods for reliable and
accurate forecasts of the wind and solar power exist. Existing methods focus
on the point forecast, and the performance is typically measured using
normalized root mean square errors. This is contradictory to the fact that a
reliable knowledge of the forecast uncertainty is of similar value as the
value of a state-of-the-art system for point forecasting.
In order to provide optimal methods for
scenario analysis in both operation and investment, the methods should focus
on a full description of the stochastic variation of the forecast and the
correlation in time of the forecast errors. The correlation in time of the
forecast errors is important for systems with start/stop costs, heat
storage, and/or 'implicit' storage that arise by allowing the hydropower
production to be exchanged with wind power production.
This WP considers methods for forecasting of
wind power, solar power, power load, district heating load and natural gas
load with a focus on modelling the full stochastic variations of forecasts
and forecast errors.
system operation and investment under uncertainty
WP3 addresses short-term operation
scheduling and long-term investment planning under uncertainty and from a
and investment of independent power producers under uncertainty
In continuation of WP3, the focus of WP4 is
operation scheduling and investment planning under uncertainty and from the
perspective of a single agent.
Radical new energy systems will require
development of new markets structures and new national incentives, perhaps
even internationally harmonized incentive schemes.
WP6 has the role of gathering results from
other WPs and testing the modelling approach. Furthermore, a number of
future scenarios will be developed taking into account already existing
scenarios, e.g. from the DSF-project CEESA and the Danish Commission on
The projectís international dimension
changes towards integration of renewable power production, increases in
demand flexibility, grid expansions and international exchange are
objectives of utmost importance all over Europe. Moreover, policy
instruments are usually either international or at least internationally
coordinated. Clearly, it is of both national and international interest to
understand how energy systems and markets as well as independent power
producers and investors are affected by the changes. For this reason, the
methodology of the project will be generally applicable to various energy
systems and markets in spite of individual opportunities for integration of
renewable energy, varying potentials for flexible demand and different
possibilities for grid expansion.
The international experts involved in the
project are highly recognized in each of their research fields and bring
valuable knowledge regarding national priorities and frontiers in
international research into the project. The international experts will
co-supervise and host PhD students for 3-6 months and possibilities for
exchanging PhD students and guest researchers will be explored.
Publication and promotional strategy and
exploitation of results
exploitation of results include the following initiatives:
A public homepage
describing the project and presenting methods, models and results
international peer reviewed journals. The project is expected to
generate more that 20 submitted articles during the project period.
international conferences in order to get feedback from the
international research community. Examples of relevant conferences are
the International Association for Energy Economics (IAEE) conferences,
the IEEE Power and Energy society general meetings, the International
conferences on Probabilistic Methods Applied to Power Systems (PMAPS)
and the European Wind Energy conference (EWEC).
the Danish Energy sector will be organized as annual seminars or go home
meetings organized in cooperation with Energinet.dk and the Danish
A user group of
institutions interested in the methods, models, and analyses developed
in the project will be established and invited to comment on project
priorities, progress and exploitation of results.