Energy planning methodologies and tools

This joint study looks at the potential for decarbonisation in the energy sector in G20 countries and around the world. The workshop aims to provide capacity building to support the design of renewable energy targets and The workshop will bring together large number of relevant stakeholders to discuss challenges Members Login.

Long-term planning tools and methodologies. Show Hide Quick Links. Perspectives for the energy transition: Investment needs for a low-carbon energy system This joint study looks at the potential for decarbonisation in the energy sector in G20 countries and around the world. Recent Publications. Geopolitics of the Energy Transformation: The Hydrogen Factor The report provides a comprehensive analysis of the geopolitical drivers and potential con NDCs and Renewable Energy Targets in This report assesses current climate pledges in light of the challenge ahead, and explores Off-grid renewable energy statistics This publication presents statistics for the decade in trilingual tables, coveri Energy planning methodologies and tools.

As with any tool, it is useful to look ahead before choosing an energy planning tool. Also, there will usually be choice between different tools that all might, at least in principle, serve the energy planning task to be addressed with the tool. To facilitate efficient selection of a tool, it is important to specify not only the overall purpose of using the tool, but also to formulate specific questions. Here it is argued that one criterion for the selection of a tool should be the simplest and gives relevant answers to the questions raised.

In many situations of energy planning, uncertainty is an important aspect. Although stochastic models address uncertainty by design, it should be remembered that for this type of models to be really useful, the probability distributions built into the model should be known, at least within reasonable limits.

If they are not, the uncertainty is just shifted from the model parameters to the parameters of a class of probability distributions. Care must also be taken when assessing model validity. The so-called "back-casting" running the model for the past to check whether it correctly produces actually observed values fails to produce much evidence if it is possible to specify model parameters with the benefit of hindsight.