Article: The New Times: a Model for the Millennium
Introduction | What's new in TIMES | GERAD's TIMES website (external link)
The scene is a waterfront motel in Hampton Bays, Long Island, USA. It is a clear, bright early fall day in 1996. The summer crowds have gone, and the motel is all but abandoned. In an upstairs meeting room, a view of the bay framed in a large picture window, a group sits down at a scramble of chairs facing an easel with a blank flip chart. They are an American, two Germans, and an Indian by way of Canada. They are the embryo of a multinational group setting out to design the best bottom-up energy systems model in the world.
Prepared with a wish list of new modeling features desired by the ETSAP participants, the group begins setting down the mathematics that will define new the model, TIMES.
The group is led by Gary Goldstein, the ETSAP primary systems coordinator since 1991 when he returned to Brookhaven National Laboratory after a stint abroad. Gary took over MARKAL, then a mainframe computer model, converted it for desktop computers, and added the MARKAL User's Support System (MUSS), a shell that makes entering data and interpreting results easy. Now an independent contractor to ETSAP, Gary believes that the state of the art of computer hardware and software has advanced to the point where the successor to MARKAL is needed.
The others are Peter Schaumann and Günter Schmid of the Institute for Energy Research (IER) at the University of Stuttgart, and Amit Kanudia of Canada's Groupe d'études et de recherche en analyse des décisions (GERAD). They are to be joined by Tom Kram of the Netherlands Energy Research Foundation, Tomas Larsson of the Gothenburg University of Technology, Sweden, Richard Loulou of GERAD, Ken Noble of the Australian Bureau of Agricultural and Resource Economics (ABARE), Uwe Remme of IER, GianCarlo Tosato of the Italian Agency for New Technologies, Energy and the Environment (ENEA), and Denise van Regemorter of the Catholic University of Leuven, Belgium, as the core group designing the new model.
Fast-forward to November 1999. The semiannual meeting of ETSAP, this one in Bergen, the Netherlands. Between these two meetings, the group has met at ETSAP workshops in Oslo, Rome, Berlin, Turkey, Washington, D.C., and two workshops of their own, with continuing E-mail correspondence in between. After one more workshop held for two days at the Netherlands Energy Research Foundation in nearby Petten, Goldstein reports on the new model to the semiannual ETSAP workshop.
In general, the model is behaving as anticipated mathematically, he says. During the past months, three national teams have been converting their MARKAL databases to TIMES with the assistance of a MARKAL-to-TIMES (M2T) conversion utility as part of the task of validating the new model. In Canada, Kanudia has converted three provincial models, and he is developing a results analysis utility that will be joined with a basic report writer. Denise van Regemorter of Belgium reports that you need to start with a good understanding of both MARKAL and TIMES, with Gary available to deal with the details at times. Mario Contaldi reports that the Italian model runs quite smoothly, with results within 5 percent of MARKAL.
"With most of the core features available, TIMES is making progress through the validation phase, although there are still some idiosyncrasies to be sorted out in both the M2T conversion utility and the model itself," says Goldstein. The Netherlands plans to begin its model conversion, and other ETSAP partners are urged to do the same.
Ahead is the choice of the Expert Shell that will enable experienced MARKAL users to use TIMES, and then the User's Shell. The leading candidates are MESAP, by adding a thin layer to a full-featured energy data management system conceived by Christoph Schlenzig of IER, and ANSWER, the current system for working with MARKAL, developed by Ken Noble of ABARE.
The goal is to have a WORLD-TIMES model fully functioning by the spring 2000. Richard Loulou hopes to have a 20-country version running in time to do global bottom-up modeling for the Third Assessment Report of the Intergovernmental Panel on Climate Change.
TIMES is not the first model to be created with this extraordinary multinational participation. It's the second. MARKAL was originally developed by two teams with representatives from 16 countries, one working in the U.S. at Brookhaven National Laboratory and one in Germany at the Energy Research Center in Jülich. Designed 20 years ago to meet the differing requirements of 16 countries, MARKAL has the flexibility that has led to its being used in more than 40.
TIMES will greatly expand upon MARKAL's traditional strengths and inherent flexibility, building on the advanced features added to MARKAL over time. For example:
New features in TIMES include:
"TIMES builds on the best features of MARKAL and the Energy Flow Optimization Model (EFOM), a sister model to MARKAL widely used earlier in Europe," said Goldstein, "hence the acronym TIMES (The Integrated MARKAL-EFOM System). We think it will promote the consolidation and uniting of the E3 optimization community.
"MARKAL, while achieving unprecedented longevity as modeling systems go, has not benefited from a re-thinking of the basic approach to describe the Reference Energy System (RES) upon which it is based, nor the way the RES is depicted mathematically.
"With the experience gained over the past two decades applying MARKAL to real world problems, with the many fresh ideas arising from this experience, and with the expanding need for a detailed technology-oriented model that can be scaled from the municipal level up to a multiregional global model, we decided to take on this challenging job."
TIMES adopts a generic concept to describe the components (commodities and processes) of an RES and its interconnections.
The flexible representation of processes in TIMES allows the relationship between individual flows to be depicted in a natural way to describe even the most complex processes.
The process box will allow inputs and outputs to be described in a flexible manner so that almost any (linear, for now) relationship may be depicted. This includes, but is not limited to:
Data are organized by attributes that are either global to the model or provide knowledge of the nature of a piece, or time-series, of information to be associated with a process or commodity. An attribute qualifier, or index, provides further knowledge of the specific nature or particular instance of an attribute. Primary attribute qualifiers are:
In traditional systems engineering models, attributes usually have one time index, and the data generally relate to one specific future year. Without vintaging, the characteristics of any modeled technology are independent of the age structure of the stock of installations.. However, the technical characteristics of an installation often change with aging. For example, the availability of power plants may increase at first as initial problems are overcome, and later decline due to more outages as parts wear out. Some changes over time may be independent of the technology itself, such as a rise in "fixed" operating and maintenance expense due to higher wages.
By vintaging installations, their technical characteristics depend upon the year of installation and the age structure of the stock. The change of attribute values over the lifetime of one vintage can be specified in TIMES using a function called SHAPE.
The objective function of TIMES, which is minimized by the solution to the program, includes a number of innovations. The objective function is expressed as the discounted sum of annual costs minus revenues, so as to provide year-by-year reporting of net costs.
Figure 1: The annualized objective function handles repeated investments in long time periods, as shown here for light bulbs.
Figure 2. The annualized objective function represents delayed investments due to construction lead times, for example in nuclear plants as shown here, as well as decommissioning costs. (to be provided!)
When the validation and testing phase is completed, the formulation of TIMES will be expanded to include enhanced quality control, stochastics, and a linkage with the economic model MACRO, as well as other advanced features such as grouping technologies and sectors for selective representation, and learning curves for investment costs.
TIMES, a model for the millennium?
"Well, at least for the next decade or two," says Goldstein.