Refactoring Energy Systems

The complexity of the present UK energy system (including numerous generators ranging from nuclear plants to individual households, transmitters, distributors, storage providers, regulators, and consumers) is ever growing.

While once only a few major power producers delivered energy to the whole country, today the energy system is drastically changing. To give a few examples: every household can supply energy into the grid, the environmentally-concerned consumers wish to purchase energy from specific sources, and communities and businesses may wish to ascertain energy self-sufficiency, but also expect to rely on the main grid as provider of the last resource. Transmission capacity must grow to meet increased consumption needs. Intermittence of new energy types (e.g., wind and solar), require larger and longer-term storage.

As the technical and participant variety in the energy system grows, the system's architecture can no longer remain uniform, for instance, some communities could rely on wind energy, others on biofuels; the level of participation of smaller suppliers would vary per locality, as will priorities of communities. Thus, there is no longer one optimal energy system architecture for the whole country. Instead, each community should be able to identify the best way that its energy system could be structured and take planned steps towards achieving and maintaining this optimal structure.

Thus, this fellowship aims to transform how the energy system is viewed, managed and evolved: moving away from the current perception of a single, uniform system across the whole of the UK, to that of localised, adaptive, largely self-reliant system-of-systems. In this new setting, the local systems will each be individually optimised, yet globally connected.

To enable this locally optimised and globally connected energy system, the fellowship will deliver a set of system refactoring patterns, tools, and techniques.
Refactoring is a disciplined approach to gradually changing the internal structure of an existing system without changing its externally useful services.

The fellowship will:
1. Collect and integrate data sources and models that would allow each community to monitor the current state of their local energy system, identify emerging problems, and address these problems through refactoring patterns. The models will also help to observe the expected effects of a refactoring application both locally and on the larger, interconnected system-of-systems.

2. Set up an open, commonly accessible technical infrastructure for data recording and model evaluation. A simple (non-specialist focused) user interface will be set up to enable all interested stakeholders to choose, evaluate and interpret models.

3. Deliver innovative methods, tools, a pattern catalogue, and good practice guidelines for energy systems refactoring.

4. Engage individuals, communities, businesses, regulators, and NGOs with the localised, renewables-based energy generation activities.

The fellowship will deliver impact to core energy system stakeholders (such as, for instance, generation and transmission systems organisations, and regulators), researchers, and the wider community through the refactoring patterns and methods, open data and model evaluation infrastructure, and stakeholder engagement activities.

Through the systems refactoring patterns and methods, the energy system stakeholders will be able to:

1. Identify areas in energy systems where refactoring is required, pinpointing problematic issues before they aggravate and further deteriorate the system's efficiency;

2. Evaluate possible refactoring patterns and strategies, gauging the impact of alternatives and basing their choices on the results of a number of model evaluations;

3. Reduce complexity of the energy system, making these systems more adaptive to the changing needs of the users, technology, and the environment.


Through the open infrastructure data and models:

1. The energy system stakeholders will be able to evaluate impact of possible change decisions at community, local, and global levels. This will allow for considered decision-making, with reduced risk of unexpected consequences.

2. The wider community members (e.g., individuals who consider installation of personal generation equipment, or groups that wish to find best ways of trading their generated energy, etc.) will be able to assess alternative options and decide upon the most preferred solution for themselves, using end-user friendly query and model evaluation interfaces.

3. Researchers from across the UK (as well as the world) will derive new hypothesis, models and theories, as well as validate their research against the free, large datasets.

4. Businesses will also be able to derive new products and business models based on free data and modelling/evaluation framework.


Through the stakeholder engagement activities:

1. Closer collaboration and partnership will be established between the various parities (from regulators to major power generators and community groups) and at various levels (from government to individual household-level prosumers) of the energy systems;

2. Direct feedback to proposed changes to the energy systems and policies will be enabled, reducing uncertainty of the decision consequences, as well as saving time and money on trials and pilots;

3. Traceability of the decisions and actions will establish clear accountability record for specific decisions to individuals and/or organisations, making energy systems decision-making transparent.