I have worked in the Impact Investment sector for more than ten years. In the past four years, my work in this sector has been focused in the entrepreneurial ecosystem. With my colleagues at ClearlySo, I have been advising impactful early-stage businesses on their business modelling and capital raising. We have raised investments to support their growth strategies. Focusing on the clean-tech and energy, my portfolio of clients includes Tonik Energy, Upside Energy, and LettUs Grow.

New grant funding has been awarded to an energy demand response project using machine learning and artificial intelligence to manage a portfolio of storage assets and provide real-time energy reserves to the grid. A Knowledge Transfer Partnership (KTP) grant worth £98,400 has been awarded to Upside Energy and Heriot-Watt University in Edinburgh which will be used to fund a researcher over two years to grow the company's algorithms for grid prediction and demand response portfolio management. Upside Energy's Virtual Energy Store aims to relieve stress on the grid by managing a number of distributed storage resources to reduce reliance on the spinning reserve capacity provided by traditional power stations. The energy start-up's cloud service currently coordinates batteries and other devices across around 40 sites but has the potential to manage thousands more across a broad portfolio of technologies, including small batteries within uninterruptible power supplies (UPS), electric vehicles and solar PV. Upside will now work with Heriot-Watt University to optimise its existing selection of control algorithms and how they are utilised in different scenarios using the university's specialist skills in machine learning and artificial intelligence.

A new energy demand response start-up is preparing to launch within weeks which will use machine learning and artificial intelligence to manage a portfolio of storage assets and provide real-time energy reserves to the grid. Upside Energy's Virtual Energy Store aims to relieve stress on the grid by using predictive algorithms to manage a number of distributed storage resources to reduce reliance on the spinning reserve capacity provided by traditional power stations. The energy start-up's cloud service currently coordinates batteries and other devices at around 40 sites but has the potential to manage thousands more across a broad portfolio of technologies, including small batteries within uninterruptible power supplies (UPS), electric vehicles and solar PV. The company signed a firm frequency response (FFR) bridging contract with the National Grid in November and is currently qualifying its assets before officially launching its commercial service by early March. Upside will begin by providing initial service to large batteries at Sheffield and Manchester Universities before seeking to take advantage of National Grid's decision to lower the minimum entry point for its main frequency response tendering market from 10MW to 1MW from April.

Upside Energy and Heriot-Watt University have been awarded a Knowledge Transfer Partnership (KTP) grant by Innovate UK to maximise the opportunities presented by the emerging energy demand response market. The project will use machine learning, and distributed artificial intelligence methods to manage a portfolio of storage assets to provide real-time energy reserves to the grid. Upside Energy's Virtual Energy Store aims to relieve stress on the grid by managing a number of distributed storage resources, thereby reducing the UK's reliance on the spinning reserve capacity provided by traditional power stations. Upside has developed an Advanced Algorithmic Platform (AAP) which allows a substantial ensemble of algorithms that manage demand response of different devices to be run in parallel. Upside will work with Heriot-Watt University to optimise their existing selection of control algorithms and how they are utilised in different scenarios using the University's specialist skills in machine learning, artificial intelligence and stochastic optimisation.