Grid-edge energy flow management in dynamic system charging models
Grid-edge balancing services will be required to manage the flexibility issues in future power grids. In this mindset, the supply and demand are matched locally. Current practices involve energy communities for local energy consumption and aggregators. An emerging concept in this domain is transactive energy, that aims to balance local supply and demand through peer to peer energy transactions in real time, autonomous and in a decentralised manner. The technology that is thought to enable transactive energy is the blockchain – a digital contract permitting an individual party to perform and bill a transaction (in this case a sale of energy) directly (peer to peer) with another party. It uses decentralized storage to record all transaction data and it provides inherent security through the encryption mechanism.
Blockchains have been in the spotlight in the energy sector and their potential use has generated vast interest, but present technology is not yet mature. The development of transactive energy enables a multitude of benefits, for both consumers and grids, that can be categorised as follows:
- Increased value of renewable generation by enabling owner to sell their production on a peer to peer market.
- Decarbonization of the energy sector by increase uptake of renewable generation
- Reduced network reinforcement costs as we move from large power plants to decentralised and local energy consumption.
The envisioned research will take an integrated whole systems approach to the operation of future grids by looking across vectors: enabling technologies and grid edge management, future energy flow patterns and security of supply.
By security of supply, we refer here to the long-term ability of the grid to support energy demand in future scenarios where peer to peer energy trading will heavily influence network operation.
There is currently little recognition of the risks associated with residential energy trading and this research will address the allocation of risk of network imbalances under peer to peer trading. Moreover, the role of the grid in such frameworks is at present underestimated.
This research will aim to create an understanding of the limitations of current network access arrangements in relation to peer to peer energy trading and to develop an adaptive DUoS charging model that enables transactive energy while maintaining security of supply.
The research will seek to address the following questions through novel models of energy trading:
1) What impact will increasing pervasion of grid-edge management have on security of supply?
2) How can the provisions for network reinforcement be designed to ensure compatibility with future energy trading patterns?
3) How can dynamic DUoS influence the use of networks in conjunction with peer to peer energy trading?
4) How can balancing risk be mitigated in a fair manner to grids and energy communities?
We are ideally seeking applicants with good honours degree in electrical, electronic, computer engineering or a closely related discipline. Previous experience in, or knowledge of, energy systems is preferable.
The successful candidate is also expected to possess the following expertise:
• A strong knowledge base of electrical systems, power engineering and energy markets.
• Demonstrable skills in scientific or data-scientific programming (such as Python, R, C++ etc.);
• A strong interest in blockchain technologies and their applications;
Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: View Website. Recently the UK Government made available the Doctoral Student Loans of up to £25,000 for UK and EU students and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.)
How good is research at Brunel University London in General Engineering?
FTE Category A staff submitted: 63.45
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