physics

Prospective Outlook on Long-term Energy Systems

Prospective Outlook on Long-term Energy Systems is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Prospective Outlook on Long-term Energy Systems rather than just read about it. In short: Prospective Outlook on Long-term Energy Systems (POLES) is a world simulation model for the energy sector that runs on the Vensim software. It is a techno-economic model with endogenous projection of energy prices, a complete accounting of energy demand and supply of numerous energy vectors and associated technologies, and a carbon dioxide and other greenhouse gases emissions module.

Key takeaways

Prospective Outlook on Long-term Energy Systems belongs to physics; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Prospective Outlook on Long-term Energy Systems to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Prospective Outlook on Long-term Energy Systems from memory before moving on to harder problems.

Reference excerpt

Prospective Outlook on Long-term Energy Systems (POLES) is a world simulation model for the energy sector that runs on the Vensim software. It is a techno-economic model with endogenous projection of energy prices, a complete accounting of energy demand and supply of numerous energy vectors and associated technologies, and a carbon dioxide and other greenhouse gases emissions module.

History POLES was initially developed in the early 1990s in the Institute of Energy Policy and Economics IEPE (now EDDEN-CNRS) in Grenoble, France. It was conceived on the basis of research issues related to global energy supply and climate change and the long-term impact of energy policies. It was initially developed through a detailed description of sectoral energy demand, electricity capacity planning and fossil fuel exploration and production in the different world regions. Along its development it incorporated theoretical and practical expertise in many fields such as mathematics, economics, engineering, energy analysis, international trade and technical change. The initial development of POLES was financed by the JOULE II and III programmes of the European Commission’s Third and Fourth Framework Programmes (FP) for Research and Technological Development (1990-1994 and 1994-1998) as well as by the French CNRS. Since then, the model has been developed extensively through several projects, some partly financed by FP5, FP6 and FP7, and in collaboration between the EDDEN-CNRS, the consulting company Enerdata and the European Joint Research Centre IPTS. With a history spanning twenty years, it is one of the few energy models worldwide, that has been in continuous development process and over such an extended time period.

Structure The model provides a complete system for the simulation and economic analysis of the world’s energy sector up to 2050. POLES is a partial equilibrium model with a yearly recursive simulation process with a combination of price-induced behavioural equations and a cost- and performance-based system for a large number of energy or energy-related technologies. Contrary to several other energy sector models, international energy prices are endogenous. The main exogenous variables are the gross domestic product and population for each country or region. The model’s structure corresponds to a system of interconnected modules and articulates three levels of analysis: international energy markets, regional energy balances, and national energy demand (which includes new technologies, electricity production, primary energy production systems and sectoral greenhouse gas emissions). POLES breaks down the world into 66 regions, of which 54 correspond to countries (including the 28 countries of the European Union) and 12 correspond to countries aggregates; for each of these regions, a full energy balance is modelled. The model covers 15 energy demand sectors in each region.

Demand sectors Each demand sector is described with a high degree of detail, including activity indicators, short- and long-term energy prices and associated elasticities and technological evolution trends (thus including the dynamic cumulative processes associated with technological learning curves). This allows a strong economic consistency in the adjustment of supply and demand by region, as relative price changes at a sectoral level impact all key component of a region’s sector. Sectoral value added is simulated. Energy demand for each fuel in a sector follows a market share-based competition driven by energy prices and factors related to policy or development assumptions. The model is composed of the following demand sectors:

Residential and Tertiary: two sectors. Industry: Energy uses in industry: four sectors, allowing for a detailed modelling of such energy-intensive industries such as the steel industry, the chemicals industry and the non-metallic minerals industry (cement, glass). Non-energy uses in industry: two sectors, for the transformation sectors such as plastics production and chemical feedstock production. Transport: four sectors (air, rail, road and other). Road transport modelling comprises several vehicle types (passenger cars, merchandise heavy trucks) and allows the study of inter-technology competition with the penetration of alternative vehicles (hybrids, electric or fuel cell vehicles). International bunkers: two sectors. Agriculture: one sector.

Oil and gas supply There are 88 oil and gas production regions with inter-regional trade; these producing regions supply the international energy markets, which in turn feed the demand of the 66 aforementioned world regions. Fossil fuel supply modelisation includes a technological improvement in the oil recovery rate, a linkage between new discoveries and cumulative drilling and a feedback of the reserves/production ratio on the oil price. OPEC and non-OPEC production is differentiated. The model includes non-conventional oil resources such as oil shales and tar sands.

Power Generation There are 30 electricity generation technologies, among which several technologies that are still marginal or planned, such as thermal production with carbon capture and storage or new nuclear designs. Price-induced diffusion tools such as feed-in tariffs can be included as drivers for projecting the future development of new energy technologies. The model distinguishes four typical daily load curves in a year, with two-hour steps. The load curves are met by a generation mix given by a merit order that is based on marginal costs of operation, maintenance and annualized capital costs. Expected power demand over the year influences investment decisions for new capacity planning in the next step.

Emissions and carbon price The model includes accounting of greenhouse gas (GHG) emissions and allows visualising GHG flows on sectoral, regional and global levels. POLES covers fuel combustion-related emissions in all demand sectors, thus covering over half of global GHG emissions. The six Kyoto Protocol GHGs are covered (carbon dioxide, methane, nitrous oxide, sulphur hexafluoride, hydrofluorocarbons and perfluorocarbons). The model can be used to test the sensibility of the energy sector to the carbon price as applied to the price of fossil fuels on a regional level, as envisaged or experimented by cap and trade systems like the EU’s Emissions Trading Scheme.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Prospective Outlook on Long-term Energy Systems

Start with the simplest possible case. Write down what Prospective Outlook on Long-term Energy Systems claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Prospective Outlook on Long-term Energy Systems before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Prospective Outlook on Long-term Energy Systems ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Prospective Outlook on Long-term Energy Systems

In research: Prospective Outlook on Long-term Energy Systems appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Prospective Outlook on Long-term Energy Systems in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Prospective Outlook on Long-term Energy Systems is common in secondary-school and first-year university syllabi. It links to neighbouring topics Energy economics, Energy models, so understanding it makes those chapters shorter.
In everyday life: Look for Prospective Outlook on Long-term Energy Systems outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Prospective Outlook on Long-term Energy Systems in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Prospective Outlook on Long-term Energy Systems means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Prospective Outlook on Long-term Energy Systems out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Prospective Outlook on Long-term Energy Systems in simple terms?

Why does Prospective Outlook on Long-term Energy Systems matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Prospective Outlook on Long-term Energy Systems?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Prospective Outlook on Long-term Energy Systems.