Multi Vector Energy Distribution System Modelling and Optimisation with Integrated Demand Side Response

Electricity and natural gas networks, as two major energy transport infrastructure, have traditionally been planned and operated independently from each other. Electricity generation was dominated by coal, oil and nuclear power stations prior to 1990, when the "dash for gas" brought a significant number of gas-fired power stations into the generation mix. These geographically dispersed large power stations have created a loose link between natural gas and electricity networks at the energy source. As the pace of decarbonising our electricity section accelerates, the two energy networks will progressively become more closely linked by end users, driven by the electrification of heat and major efficiency improvements. This presents critical new challenges to the traditional network modelling, operation and optimisations, in particular as they were developed independently for natural gas and electricity networks. The traditional methods do not take into account of the substantial rise in the interaction between the two networks, i.e. how a change in gas demand/resource might impact the demand/generation of the electrical system and vice versa.

The vision of this research is to develop a statistical model for combined gas and electricity systems at the distribution level that can efficiently simulate the interactions across the energy vector under severe uncertainties. The developed model will then be fed to the novel optimal operation strategies to manage the two systems for encouraging increased use of renewables and infrastructure and promoting customer interaction with the systems. This fellowship will address this vision by developing highly efficient network sampling methodologies, multi-vector probabilistic energy flow and optimisation tools that will transform the modelling and analysis of highly integrated systems. These new developments will: i) enable detailed real-time analyses of energy flows and capacity bottlenecks of the highly integrated energy systems with high accuracy and in reasonable time scale, ii) assist network operators to optimise the performance of the existing energy systems to minimise the cost of integrating low carbon generation and demand, and iii) assist policy makers to design effective policies and regulations for economic and sustainable energy network development.

The industrial beneficiaries are domestic consumers, network operators, renewable generation, and energy suppliers.
1. The ultimate beneficiaries will be end domestic customers. The multi-vector energy systems provide two routes to transmit energy, which provide more flexibility for end customers to interact with multi-vector systems over time. They can have low energy costs by storing and generating energy as appropriate, or switching demand from one type of source to the other in response to energy prices and energy system conditions.
2. Network operators will benefit from the research. The research develops fundamentally new approaches in modelling multi-vector energy carriers, which underpins the optimisation of demand response to increase the utilisation of existing energy transport infrastructure. The optimal management will provide cheaper alternatives by exploring the potential capacity from the existing infrastructure to release network constraints to support demand and generation growth. By doing so, the needed network investment can be deferred or ideally avoided, without compromising network security and quality of supply.
3. Renewable generation can also benefit. Due to the intermittency, renewable energy can not be dispatched to serve base loads and are normally constrained off when the electricity networks are congested. This incurs not only monetary loss for renewable generation companies but also a waste of clean energy for the society. The proposed research provides an alternative route- gas networks for renewable energy to be delivered to end-use customers. The benefits for renewable generation are the reduction in output constraint at the time of electricity systems being stressed.
4. The last group beneficiary is energy suppliers. Energy suppliers have to pay network operators for their use of the energy systems to transport energy. The proposed research can maximise the existing energy infrastructure to minimise future reinforcement or upgrades needed to support increasing generation and demand. This decreasing investment means energy suppliers will pay less for using the infrastructure.

The benefits to the UK society lies in assisting national energy security and cleanness, helping policy making, and promoting business opportunities.
1. The multi-vector energy networks will improve security of supply. When one system is undergoing sever interruption or congestion, the other system will still function properly as a backup to transport the energy. The linkage between the two energy systems reduces end customers' energy interruption and deterioration in security and quality of supply during severe times. The multi-vector systems can also enable more penetration of renewable energies, which are wasted due to network congestion. It will reduce the nation's dependence on scarce fossil-fired resources and increase national energy security and cleanness.
2. The proposed work will be valuable for future low carbon energy system modelling, planning, and operation. It is not only because it will enable more renewable penetration on a large but also because more efficient utilisation of existing energy transport infrastructure. It will benefit renewable penetration, investment saving and CO2 reduction. The findings will inform the energy network regulator, policy makers, and the government on the paradigm shift needed in the design, operation, and management of energy systems for a low carbon future.
3. The work will also inform new knowledge and research areas. The proposed research will benefit several academic communities through the large-scale, multi-level, non-linear modelling and optimisation of closely coupled gas and electricity networks. The scientific knowledge from this research creates new business opportunities for third parties who are interested in providing services for multi-vector energy system planning, operation and economics, and implementation of cross-vector demand response.