Over the past years, storage technologies have gradually become an integral part of modern power systems. One of the well-known issues is the optimum control of storage devices to maximise the efficiency or reliability of a system. For example, how to minimise the fuel consumption or maximum power of a hybrid car with a storage device by operating the device within its range.
In cooperation with his colleague from Israel, Professor Juri Belikov from the Department of Software Science developed a new control scheme for energy storage devices, which operates under uncertainty conditions. In addition to hybrid cars, the solution can be used anywhere in the production, consumption and storage of energy – in a private house using renewable energy, for example.
According to Belikov, it is not at all easy to decide how much and when the device should store energy. Optimum control issues like these are usually difficult to solve because of the high computational complexity, since finding an optimum solution requires the calculation of the stored energy at any time, the software researcher said.
He noted that in addition, the issues in optimising energy storage include uncertainties such as variable load curves, variations in renewable energy production, or prices changing in time. These uncertainties are usually taken into account by stochastic control methods. In real systems, however, their use is still problematic because the statistical model describing the load (e.g. driving profile) is either very complex or simply non-existent. Although the burden can accurately be described as a random process, the numerical algorithm for optimum control makes it impractical due to its high complexity.
Together with Yoash Levron from Technion, Juri Belikov proposed a non-linear two-tier control scheme for energy storage devices, which operates under uncertainty. As the first step, Pontryagin’s minimum principle is used in the solution to find an optimum closed loop system. As this optimum system is causal, it does not require information on the future values of the signals. However, there’s no such thing as a free lunch, so the result is the instability of the system.
A family of sub-optimal controllers is created based on this closed loop system, obtained by stabilising the original system through negative feedback. The final controller is not entirely optimal anymore, but is still causal (i.e. no information is needed on future signals), which is why the controller can work well under uncertainty. As the various forms of stabilising feedback allow for different controllers, the proposed approach opens up many opportunities for future research and potential applications.
The work of the researchers received the Best-of-the-Best conference paper award at the PES General Meeting as a testament to excellence. The highly acclaimed scientific paper (Control of Energy Storage Devices Under Uncertainty Using Nonlinear Feedback Systems) is available here.
