Advanced modelling for network planning under uncertainty


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In this project commissioned by NGESO in Great Britain, the Melbourne Energy Institute analysed current industry practices in transmission network planning and provided recommendations on how to develop a state-of-the-art planning methodology subject to long-term uncertainty, whilst considering the associated risk and the role of new technologies.

A lot goes into network planning. It is about deciding the most appropriate type of network asset to build, determining when to build them, and enabling integration of greater volumes of low-carbon resources at lower cost - all while preserving system security and reliability.

Network investment usually has a high upfront cost and a long lifetime, which makes cost recovery very sensitive to the significant uncertainty in future generation and demand. In fact, some assets might end up being underutilised, resulting in undesirable increases to consumers’ electricity bills. On the other hand, an investment strategy that is too “slow” might prevent the development of inexpensive, low-carbon technologies. New technologies, such as various types of storage, are emerging that could both complement and compete with more traditional network investment options.

The aim of this project, commissioned by National Grid Electricity System Operator (NGESO) in Great Britain, was to understand the current industry practices in transmission network planning.

MEI researchers set out to provide recommendations on how to develop a state-of-the-art planning methodology subject to long-term uncertainty, while considering the associated risk and the role of new technologies. This kind of methodology is essential to guide system planning and investment in the transition towards a low-carbon system, not only for Great Britain but potentially for other countries around the world.

The MEI team, led by Professor Pierluigi Mancarella, reviewed the methodologies developed by system operators around the world, summarised NGESO’s current planning processes and then made several recommendations to improve NGESO’s planning methodology in several respects. Assisting with this process, NGESO provided valuable information on their planning methodology and insightful feedback to sharpen MEI’s recommendations.

Balancing risk and welfare

Ofgem, Great Britain’s electricity and gas market regulator, also provided advice on the suitability of different risk assessment approaches, highlighting the regulator’s interest in striking a balance between investment risk and consumer welfare.

The research outcomes provide a comprehensive view of costs, benefits and risks that are involved in such a complex engineering problem, and proposes a new methodology to assess the risk implications of network investment under uncertainty. The research outcomes also discuss the benefits of a new, flexible and adaptable approach to system planning, and puts forward the role of alternative technology solutions (eg storage) to complement network-based reinforcements. Overall, improving the system planning methodology to better account for uncertainty and risk will provide substantial community benefits in terms of lower energy costs and prices, and deeper penetration of low-carbon technologies. This is achieved by making the investment plan more flexible and adaptable to future technology developments.

Standard deterministic cost-benefit analysis that is widely adopted in transmission network planning around the world is becoming less effective in mitigating the risk arising from large-scale uncertainty brought by the development of new technologies and end-use energy electrification. The MEI team proposed several novel ideas to move away from deterministic planning and embrace aspects of probabilistic modelling, including a new metric named least worst weighted regret (LWWR), to better account for risk and robustness of the decision making. LWWR is now also being adopted by AEMO as part of their draft methodology for the 2022 Integrated System Plan.

The MEI team has also recently been appointed by CSIRO to develop, in the context of the Global Power System Transformation (GPST) consortium, a research plan for Australia in the area of power system planning.

Read the full reports to learn more:

‘Study of advanced modelling for network planning under uncertainty’ - Part 1: Review of frameworks and industrial practices for decision-making in transmission network planning and Part 2: Review of power transfer capability assessment and investment flexibility in transmission network planning.

First published by the Melbourne Energy Institute

First published on 9 November 2021.

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