Economic Analysis, Financing & Modelling for Renewable Energy

Course Info

Length:

5 Days

Type:

In Classroom

City:

London
Available DatesVenue
2025-04-28London
2025-06-30London
2025-08-04London
2025-10-06London
2025-12-29London
Available DatesOther Venue
2025-05-05Dubai
2025-07-07Istanbul
2025-07-07Dubai
2025-07-07Amsterdam
2025-07-07Barcelona
2025-07-07Paris
2025-07-07Kuala Lumpur
2025-07-07Singapore
2025-09-29Dubai
2025-10-06Singapore
2025-10-06Kuala Lumpur
2025-10-06Istanbul
2025-10-06Paris
2025-10-06Barcelona
2025-10-06Amsterdam
2025-11-03Dubai

Course Details

  • Introduction

  • Objective

  • Who should attend

  • Course Location

As global energy markets accelerate their shift toward decarbonization, renewable energy investments are no longer driven by environmental ideals alone—they’re financial imperatives. But while the sector promises growth, navigating its economics is anything but simple. Stakeholders must now evaluate fluctuating costs, emerging storage technologies, shifting regulatory frameworks, and new risk-sharing models. For developers, investors, and analysts alike, understanding how to build and interpret robust financial models is the key to unlocking bankable, scalable, clean energy projects.


The Economic Analysis, Financing & Modelling for Renewable Energy course is designed to bridge that critical gap. Through hands-on training with real-world data and scenario-based exercises, this course equips you with the tools to analyze, structure, and optimize the financial models that shape renewable energy ventures—from onshore wind to geothermal.

Course Outline

5 days course
  • Day 1
  • Day 2
  • Day 3
  • Day 4
  • Day 5

Overview of Project Finance Terms and Value Drivers in Renewable Energy


  • Exploring key project finance terms in renewable energy financial models.
  • Discussing primary drivers of value in renewable projects (e.g, technology cost, performance, etc)
  • Reviewing the capital intensity of alternative renewable technologies and their levelized cost of electricity (LCOE).
  • Identifying the influence of storage integration on achieving grid parity.
  • Examining financial model structures for evaluating parity with and without storage.
  • Exercise: Compute grid parity scenarios using sample data, comparing solar PV projects with and without battery storage.

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