A Cyber-physical systems perspective on decentralized energy management
Driven by the effects of climate change, our world is in a rapid transition towards a sustainable society powered by renewable energy, such as produced by solar panels and wind turbines. The advanced civilization we live in today depends on a stable and reliable supply of energy. However, renewable energy sources are intermittent and the generated energy may fluctuate heavily throughout the day. Next to this, the number of locally installed renewable microgenerators is rapidly rising. As a result, the supply of energy becomes less controllable, endangering the stability of the electricity system and the reliable supply of energy to consumers.
The adoption of renewable energy results in a shift of the energy generation mix towards electricity. This also implies that the share of electricity consumption increases. Notable is the rising market share of electric vehicles and the adoption of electricity powered space heating and cooling solutions. This shift has significant impact on the existing infrastructure, which in general is not designed to distribute the amount of electricity we face within the energy transition, with the risk of an increased number of supply interruptions. On the other hand, these new developments also provide an opportunity as the distance between consumers and producers reduces due to the decentralization.
To benefit from this opportunity, coordination among a cluster containing a heterogeneous set of producers and consumers, also known as distributed energy resources (DERs), is required. Therefore, the scope of this thesis is to perform decentralized energy management, specifically within residential distribution grids where large scale adoption of DERs is expected. Such a cluster in a particular subgrid, often referred to as a microgrid, may achieve a high degree of energy autarky. A cyber-physical systems approach is taken to study the interaction between control systems, the operation of devices and the effect on the physical grid.
The first contribution is a proactive control methodology for decentralized energy management based on model predictive control. The foundation of this methodology is the profile steering heuristic to decentralize the coordination between all DERs in such a microgrid. This approach uses predictions to estimate the future state and the available flexibility of one or multiple DERs. In an iterative and coordinated manner, each element receives an incentive to schedule its flexibility towards a desired power profile for a number of future time intervals. These predictions and schedules are created locally, e.g. within a household or microgrid. Parallelism can be exploited as only local information is required to create such a schedule, resulting in a decentralized and scalable solution.
The profile steering algorithm utilizes a hierarchical structure to spread its steering signals. As distribution grids are commonly operated in a tree structure as well, characteristics and power limits of the distribution grid are embedded into the control structure as optimization constraints. Another important aspect to power delivery is the supplied power quality, such as the voltage levels and balance in a three-phase distribution system. Therefore, the profile steering approach is extended with multiple steering signals to perform phase balancing and reactive power control simultaneously. In the realization of the planned profile, prediction errors in both the energy and time domain may arise. As a consequence, plannings may become infeasible. However, a complete replanning of a cluster of DERs is often too computationally intensive. Therefore, an event-based variant of profile steering is presented to perform partial replanning. The model predictive nature of this approach, resolves prediction errors in both the time and energy domain.
A second contribution is a control methodology based on double-sided auctions, for real-time balancing in microgrid islanding situations. In such situations, DERs can assist conventional backup solutions in supplying and balancing the microgrid. Within this process, the reaction time of DERs is included to avoid overreaction and unstable behaviour. This method can be combined with the profile steering approach to benefit from predictive control. Secondly, since communication is expected to play a crucial role to maintain reliability in future grids, precautions need to be taken for emergency situations when communication networks fail. Locally available measurement data, such as the voltage or frequency, are used as an alternative communication channel to infer the microgrid state. Subsequently, this information is used to perform a local market clearing to balance a microgrid.
The third contribution is the developed simulation and demonstration framework to test these control methodologies in a cyber-physical systems context. Next to this framework, an artificial load profile generator is developed to generate futuristic use-cases with the explicit modelling of available flexibility. The combination of these two tools is used to evaluate the performance of the presented control methodologies in various use-cases.
The accuracy of individual models is validated using measurements and field tests conducted in a smart grid test site in the Dutch town of Lochem. Based on the models of the grid and baseline power consumption, futuristic scenarios are created to evaluate the impact of electrification in this town. Simulation results indicate that without control power quality issues and grid overloading occurs in such a scenario. If control is applied, the current grid is capable of delivering reliable electricity as the aforementioned opportunity of coordination between local production and consumption translates into reduced utilization of the distribution network.
A real-life stress-test, in which a 2025 scenario was created, resulted in a supply interruption due to grid overloading. The lack of controllability was a major cause for this, illustrating the importance of control in future distribution grids. The presented decentralized energy management approach is therefore a valuable tool to unlock flexibility of DERs and provide means for a smooth energy transition.
