With the fast development of network technology and computing power, a huge amount of data has been generated in almost every aspect of our lives. The International Data Corporation reported that 90 ZB of data will be created each year by 2020, indicating that a big data era is upon us. A typical example is in the energy sector where a large amount of data is generated every day due to smart meter and other digitized changes. These are in turn changing the operation of the energy industry as big data analytics can provide efficient and effective decision support processes. The effect of decentralised generation in the future electricity landscape has and will continue to significantly increase the population of microgrids comprising renewable generation (wind and PV) and battery energy storage supplying local demand, with the excess being exported to the grid. The traditional control design for the energy management system of microgrids is based on a highly simplified model, whose results are highly suboptimal for such a complicated distributed system. Data-driven control could largely improve performance as there is enough data and computing power available today. In addition, energy management systems and market trading optimization packages provided by the big companies are generally designed for large utility and power generation companies and not tailored for smaller prosumers. Given the rapid growth of small prosumers, the PI will develop packages which are tailored to the micro level and meet their individual needs. The PI aims to develop a data-driven intelligent energy management system for a micro grid (connected to a main grid) consisting of wind and solar generation, batteries, and local load in order to provide an integrated, local, smart source of energy. It will use available information (e.g. wind data, weather forecast, energy pricing profile, balancing services pricing etc) to manage the energy generation/utilization and export on site to maximise the financial return to the stakeholder of the microgrid site, and provide balancing services to the System Operator (e.g. my project partner National Grid in the UK). Eventually this will benefit the environment and lead to cheaper energy to the end users due to the improved usage efficiency of renewable energy and the reduced system operation cost.

Potential Impact:
Academic impact: The key purpose of the proposed research is to produce new knowledge at the interface of 3 disciplines (control systems, data science and power systems) and to develop a new data-driven multi-objective intelligent energy management system for the microgrid that will facilitate future technology development in microgrids in a financially efficient manner. This becomes extremely critical to secure economic and high quality operations of the microgrid, particularly under the conditions of large-scale intermittent renewable energy sources. It will create a synergistic approach across control theory with data science and power systems in order to contribute to microgrid technology, ultimately helping to address the big challenge of providing society with clean and renewable energy.

Economic Impact: The developed intelligent energy management system will allow microgrids to maximize their potential to generate, store and consume electricity at the most advantageous times to improve the productivity of renewable generation and maximise the financial return to the stakeholder of the microgrid site. This will attract more investment for building more microgrids which will be widely distributed across the GB network. They will have the capability of providing flexibility and resilience to the grid by allowing control of many small embedded wind and solar generation plants coupled with energy storage. This will help in enhancing the future system operations (e.g., more effective balancing services) as proposed in the National Grid System Operability Framework 2015 document, leading to cheaper system operating costs and thus, cheaper energy to the end users. Given the generation is nearer to the demand as it is mainly locally generated, the resilience of supply to the end user will improve in the event of large disturbances at the transmission level. These sites could be designed to operate in islanding mode in the event of failure at the upstream of the supply network. The end result will be cheaper and allow more flexible local power generation and utilisation leading to a more secured, efficient, resilient, and affordable energy infrastructure. This will have a direct economic impact by making wind and solar energy more competitive, which will benefit local economies.

Societal Impact: this project will help facilitate the expansion of clean sources of energy in an environmentally sympathetic manner. It will enhance the UK capabilities in renewables technology, contributing to maintain the UK's position as global leader in renewable energy installation. It will help achieve the government's aim to cut greenhouse gas emissions by at least 80% below the level that it was in 1990.

People Impact: the project will provide the opportunity for both the PI and researchers involved to develop a wide range of skills. The PI will develop leadership skills as well as project and financial management. It will also allow him to continue to grow his profile in both control and renewable energy communities and develop a new area - microgrid, and will positively improve his track record in industry focused research. The researchers will be part of a multidisciplinary project and a strong research group lead by the PI, enabling them to develop new technical and interpersonal skills and contribute to an important challenge.

The impact plan has been designed across 2 key areas: 1) academic impact & dissemination by conferences, seminars (including 4 planned industry engagement seminars) and publications, closing workshop, and through PI's existing consortiums; 2) industrial collaboration & wider dissemination. As mentioned in the proposal, the PI has collaborations with key energy companies which facilitates the dissemination process. Beyond this group, the PI will continue active engagement with the wider UK renewables energy community e.g. Supergen ORE for which the PI has just been appointed as a co-director.