The complexity of energy systems operation and the necessity to design secure and reliable systems, compatible with greenhouse gas (GHG) mitigation goals, have justified the development of energy models. They are capable of representing detailed energy systems (technical and economic characteristics) and the interconnections between supply and consumer sectors, assessing energy consumption and production pathways. Energy modeling tools have been widely used to help energy planners to assess energy systems; from different approaches as the impacts of alternative energy and environmental policies, or the competitiveness of different energy technologies. This paper provides an overview of the energy-environmental-economic modeling tool TIMES_PT, the last generation of the IEA/ETSAP integrated technological energy models, with a focus on its structure, functioning, and calibration for the case of the Portuguese energy system. Applications cases of TIMES_PT, namely for the design of low carbon scenarios for the long-term, are presented. Innovative developments on linking TIMES_PT with a macro-economic model (GEM-E3_PT) and the assessment of non-technological variables are also described.
Since the 70’s energy models have been widely used to support energy planning. In
that time, models were used to understand the implications of an oil embargo in
energy supply security. More recently, climate change and the need to reduce GHG
emissions has become one of the main issues in energy planning [
One of the major energy optimization tools used are the bottom-up technology MARKAL (MARKet ALlocation) and TIMES (The Integrated MARKAL-EFOM System) models. These models are used by more than 100 institutions and countries and supported under the ETSAP/IEA.
TIMES_PT [
The objective of the TIMES model is the satisfaction of an exogenous energy service demand at the minimum total system cost over the entire planning horizon (i.e. the optimal energy-technology pathways). Thus, supported by a database of more than 2000 technologies, the model determines the optimal mix of technologies and fuels at each period, the associated emissions and trading activities.
The TIMES_PT model has been extensively used in several national and international
studies and its technological database has been continuously updated and validated by
national stakeholders and international literature. TIMES_PT, as other TIMES
models, is written in General Algebraic Modeling System (GAMS) language [
This paper aims to provide an overview of the energy-environmental-economic modeling tool TIMES_PT, focused on its general features and main components (Section 2), and applications cases (Section 3). Section 4 of the paper concludes and presents innovative features under development. 2
As abovementioned, TIMES_PT is a peer-reviewed linear programming optimization
bottom-up technology model. This section describes the main features of the model as
well as its specific characteristics that have been improved or updated in the last
years. The TIMES_PT model formulates a single, overall mathematical programming
(optimization) problem that covers the energy supply system, according to equation 1
[
TIMES_PT represents the energy system of PT and its possible long-term
developments. The actual system encompasses all the steps from primary resources in place
to the supply of the energy services demanded by energy consumers, through the
chain of processes which transform, transport, distribute and convert energy into
services [
Each element in the network is characterized by several input parameters. The
TIMES_PT technological database has more than two thousands of existing and
future energy related technologies. Technologies are described by means of technical
data (e.g. capacity, efficiency), environmental emission coefficients (e.g. CO2, SOx,
NOx), and economic values (e.g. capital cost, date of commercialization). Possible
future developments of the system are driven by reference demands for energy
services (e.g. commercial lighting, residential space heating, air conditioning, mobility
and many others), and the supply curves of the resources (e.g. amount available at
each price level) [
Several assets distinguish TIMES_PT from European aggregated models like PET
(Pan European TIMES [
TIMES_PT is a long-term model designed to explore the development of the PT
energy system till 2050 through the computation of projections for the period
20052050. While in its original version, developed within NEEDS project [
Annual flows of energy consumption and production are split by season - spring, summer, fall, winter; and daily load profiles - night, day and peak, considering the Portuguese electricity demand profile. 2.2
The supply side of the TIMES_PT model represents the primary energy sector: resource extraction or imports, processing and transport to transformation – plants and refineries, coke ovens and bio-conversion, etc. – followed by transport and distribution of the final energy products.
Each primary resource is modeled independently, and represented by a linearized
stepwise supply function. The number of steps approximating each curve depends on
the resource and on the country reserves. The energy commodities are disaggregated
to the level of detail of the extended national energy balances reported by [
TIMES_PT model includes five main end-use sectors: Agriculture (AGR), Industry (IND), Services (SERV), Residential (RSD) and Transport (TRA).
The AGR sector is represented in a simplified way, and future energy demand is driven by the projection of the sectorial economic activity.
Regarding IND, TIMES_PT model breaks-out the national industrial sector in eleven sub-sectors: hollow and flat glass, high and lower quality paper, chemistry, cement, iron & steel, lime, other non-ferrous metals, other non-metallic minerals and other chemical. Each of them includes diverse manufacturing processes and is modeled according to its mass and energy balance.
The SERV sector represents several different economic sub sectors like offices, banks, hospitals, etc. However, due to the lack of data for PT on specific sub sectors energy consumption and equipment, this sector is modeled in an aggregated way, considering two types of SERV - large (>1000m2) and small (<1000m2). The SERV sector energy demand includes: space heating and cooling, water heating, cooking, lighting, refrigeration and other electric equipment.
RSD sector includes the same categories as the SERV, but improved disaggregation on electric equipment including cloth washing and drying machines and cloth washing, among others. The devices that supply warm water, space heating and cooling are broken out by building type as its need vary significantly – namely multi apartment building, single house in urban areas and single house in rural areas.
The TRA sector corresponds to the economic sector “transport services” and
private mobility. The demand for TRA is first broken out by: road, rail, navigation and
aviation. Road and rail transport are split between passenger and freight. The demand
for road passengers’ transportation is further divided to short and long distance
private car transport, urban busses, intercity busses and motorcycles. Passenger’s rail
transport is further divided into urban metro transport and intercity train transport.
Freight transport is disaggregated into road transport by heavy and light trucks and
intercity rail transport [
Energy end-use demand is an exogenous model input, commonly generated according
to the methodology presented in [
For Portugal, the endogenous primary energy potential solely relates to renewable energy sources (RES) once there are not known endogenous fossil resources. For most resources the potential is given not only having in mind the technical potential but also possible deployment of technologies in the near future.
These technical economical potentials restrict the use and future deployment of
each technology, limiting its capacity. Generally speaking, the 2020 figures are in line
with the expectation presented in National Renewable Energy Action Plan [
Primary energy prices definition is crucial for setting the boundaries of an energy
system future development. Average primary energy import prices projections are
annually updated based on the scenarios from [
The evolution of the costs of supply and demand technologies between 2010 and 2050, are dependent on the actual expectation in terms of development and implementation, and are crucial to evaluate the competitiveness of the technologies. The model combines the technical economic data with energy prices to dynamically calculate supply cost curves for year and energy demand category. The combination between supply cost curves defines the competitiveness of the technologies. Fig. 2 presents an example of a supply curve for cooling services buildings. 40 J/€P M30 20 10 0
INVCOST
FIXCOST
VARCOST
FUELCOST Non,reversible4 Room4air, Roof,top4central4 electricity4heat4 conditioner4 electric4chiller4 pump4
Air4fans4
Centralized4 Non4reversible4 Centralized4gas4 electrical4air4 gas4heat4pump4 air4conditioner conditioner4 TIMES_PT technological database is frequently updated in order to reflect recent technological developments and national specificities. Table 1 presents, an example investment costs expectations for different RES and combined cycle natural gas power plants for Portugal. Availability factors are also an important characteristic of a technology, especially for RES, influencing its future uses. For wind turbines and solar technologies the availability was defined based on the data from the production of the existing plants and parks in Portugal and Spain and national stakeholder’s. The availability factors for hydro power plants are updated to an average Portuguese hydraulicity year.
TIMES_PT model can be used for a wide set of policy and technological analysis associated with GHG and air pollutants emissions and energy related activities (e.g. Fig. 3). This section presents a sample of international and national projects where TIMES_PT has been used for different purposes.
• • • •
COMET - Integrated infrastructure for CO2 transport and storage in the west Mediterranean - is a EU research project aiming at identifying and assessing the most cost effective infrastructure of CO2 transport and geologic storage, that will be able to serve the West Mediterranean area (Spain, Portugal and Morocco), as well as the location, capacity and availability of potential CO2 storage in geological formations.
HybCO2 - Hybrid approaches to assess economic, environmental and technological impacts of long term low carbon scenarios: the Portuguese case is a national research project aiming to develop and implement two hybrid modeling tools to improve the cost-effectiveness assessment of energy/climate policy instruments.
Low Carbon RoadMap: Portugal 2050 - outlines how the transition to a low
carbon economy in Portugal can be achieved, focusing on changes in the
national energy system and evaluating its economic impact. The model was
used to outline a -60% and -70% GHG decarbonization pathways (face to
1990) [
RoadMap for New Energy Technologies: Portugal 2010-2050 - Policy
support project for assessing the competitiveness of national energy
technologies, namely RES electricity generation and electric mobility technologies
and its long-term impact in the PT energy system [
0 -‐200 -‐400 -‐600 -‐800 -‐1000 77% 77% 80% 60% 50% 40% 30% 20% 10% 0% The complexity of energy systems operation and the necessity to design secure and reliable systems, compatible with GHG mitigation goals, have justified the development of energy models. In this paper we describe the linear optimization model TIMES_PT that has been improved and updated to reflect the PT energy system and policies, and selected projects supported by it. Although technological based models have been useful to design future scenarios of energy systems, they present limitations that have been identified and researched.
Future work will advance energy modeling in two areas: a) by integrating nontechnological features as the case of consumer behavior in residential sector, based on the knowledge behind energy consumption drivers; b) by linking with an economic computable general equilibrium (GEM-E3_PT) constituting a hybrid technologyeconomic platform (HybTEP), which overcome the state of the art absence of macroeconomic feedbacks of different energy system pathways, namely the impact on gross domestic product or industry production, underestimating the costs of mitigation policies. These advancements will improve greatly the ability to model energy systems and reduce uncertainty for the medium to long term.