Long-term Modeled Projections of the Energy Sector: An Incremental Approach to Narrowing Down the Uncertainty Range

This book discusses improving long-term projections of the national energy sector development by introducing a multi-stage approach to narrowing down uncertainty. It covers regional energy markets forecasting and assessing barriers and strategic-level energy security threats.

Format: Paperback / softback
Length: 98 pages
Publication date: 26 August 2021
Publisher: Springer Nature Switzerland AG

This comprehensive book delves into various approaches to enhancing the accuracy and significance of long-term projections for the national energy sector development. It then presents an innovative multi-stage methodology to narrow down the uncertainty range associated with input data and resulting projections. What sets this work apart is its step-by-step limitation of the scope for each projection timeframe segment through iterative calculations. These calculations employ dedicated methods and tools to elucidate and solve top-priority problems specific to each time segment. In conclusion, the book offers a detailed treatment of two critical research problems: long-term forecasting for regional energy markets and the quantitative assessment of barriers to energy sector development and strategic-level energy security threats.

Introduction:
The energy sector plays a pivotal role in shaping the future of our world, and accurate long-term projections are essential for informed decision-making. However, the complexity and uncertainty of the sector make it challenging to develop reliable projections. This book aims to address this challenge by exploring available approaches to improving the performance and impact of long-term projections of the national energy sector development.

Approaches to Improving Projections:
The book discusses a range of approaches to enhancing the accuracy and reliability of long-term projections. These include statistical modeling, scenario analysis, and optimization techniques. Statistical modeling involves using historical data to develop models that can predict future trends in the energy sector. Scenario analysis involves creating multiple scenarios based on different assumptions about economic, political, and environmental factors that can impact the sector. Optimization techniques involve using mathematical algorithms to find the best solution to a given problem.

Multi-Stage Approach:
One of the unique contributions of this book is its introduction of an original multi-stage approach to narrowing down the uncertainty range of input data and resulting projections. The approach involves dividing the projection timeframe into smaller segments and analyzing each segment separately. This allows for a more detailed examination of the factors that can impact the sector and enables the identification of specific risks and uncertainties.

Step-by-Step Limitation of Scope:
The multi-stage approach also involves a step-by-step limitation of the scope for each projection timeframe segment. This is done in the course of iterative calculations, which employ dedicated methods and other tools to elucidate and solve top-priority problems specific to each time segment. By limiting the scope, the book ensures that the projections are focused on the most critical factors and that the uncertainty range is minimized.

Treatment of Research Problems:
In addition to improving the accuracy and reliability of projections, the book also provides a detailed treatment of two essential research problems: long-term forecasting for regional energy markets and the quantitative assessment of barriers to energy sector development and strategic-level energy security threats.

Conclusion:
This comprehensive book offers valuable insights into the challenges and opportunities of long-term projections for the national energy sector development. It provides a framework for improving the accuracy and significance of projections and introduces an innovative multi-stage approach to narrowing down the uncertainty range. By addressing these research problems, the book contributes to the development of a more robust and resilient energy sector.

Weight: 191g
Dimension: 235 x 155 (mm)
ISBN-13: 9783030305352
Edition number: 1st ed. 2020