Inverter-based low-voltage microgrids face the issue of imbalanced reactive power sharing among parallel inverter units due to predominantly resistive feeders. This issue can be addressed using large droop coefficients in primary power control loops. However, the large droop coefficients can lead to increased power oscillations and lightly damped modes in the system. To address this issue, this paper proposes an adaptive droop control strategy. This approach adapts the reactive droop coefficient in real-time, ensuring the best possible reactive power sharing while maintaining sufficiently high damping of the inverter oscillatory modes. The paper first derives a mathematical relationship between the damping-ratio of the associated inverter mode and droop coefficients, showing their monotonically inverse dependence. Based on the relationship, an adaptive strategy is formulated that continuously updates the reactive droop coefficient based on the estimated damping-ratio of the critical system modes. The damping-ratio is derived by perturbing the reactive power droop coefficient and processing the inverter's active power response using the Matrix-Pencil mode estimation algorithm. The proposed adaptive droop control offers three key advantages: (i) enhanced reactive power sharing, (ii) improved microgrid stability through adaptive droop coefficient adjustment, enabling inverters to act as stability reservoirs, and (iii) applicability to grids with unknown R/X ratios.

Fast frequency response services, designed to quickly balance the electrical grid within seconds, have a critical importance for managing sudden anomalies in low-inertia power systems. Battery systems often serve as versatile prosumers on the demand side to facilitate fast frequency response services. However, the nature of the fast frequency response services leads to a highly fluctuating power profile for batteries, which can shorten their lifetime. In contrast, distributed air-source heat pumps in residential areas have a substantial untapped potential to support fast frequency response services. This paper seeks to integrate them into the existing services through a controller upgrade. We analyze the influence of air-source heat pumps' inherent complex thermal dynamics on fast frequency response services, revealing control challenges posed by unpredictable operating condition changes. Such a challenge is tackled with a decentralized control strategy based on H∞ and inverse-droop control, guaranteeing practical and stable operations within the permitted operating condition range. Finally, the proposed fast frequency response service scheme is tested through multiphysics simulations on a small-size low-inertia residential microgrid. The obtained results strongly supported the proposed new service.

Paper submitted to PSCC 2024. In this paper, we present a standard power-hardware-in-the-loop testing platform that can real-time simulate detailed air-source heat pump dynamics based on well-established modeling knowledge. Distributed air-source heat pumps can be potentially used for fast frequency response. However, using air-source heat pumps for rapid modulation cannot be based on the current assumptions of linear speed-power transient characteristic, which was developed for low-speed temperature control applications. Customized setups with experimental validation options are needed to design the new fast frequency response compatible heat pump controllers. Most power system laboratories struggle in building a customized air-source heat pump, which hinders the research progress. The proposed platform is relatively universal, can fit to different heat pumps with minor modifications and be implemented on standard PHIL emulators in power system laboratories. Emulation results, real-time implementation details and model complexity metrics are presented, to assist transference of the setup to other laboratoriesÂ

The heat pump system is complicated to model dynamically because of the phase changing in both evaporator and condenser. The  moving boundary model tackles this problem by dividing the evaporator and condenser into variable-length zones, and their lengths  vary with the thermal state of the refrigerant. This document explains the full derivation process of the moving boundary model of an air source heat pump system.

The transition to weather dependent renewable energy generators requires the electric loads to be adjusted to generation. This is made possible by demand response programs and home energy management systems. However, practically easy to use rule-based control systems often miss many optimization potentials. Self-learning alternatives employing reinforcement learning often ignore the partial observability of the building control problem and consequently neglect the importance of the observation history. Adaptive control systems that do consider that history often rely on policies that suffer from catastrophic forgetting, which makes them unable to fully grasp long histories. As an alternative, we present a new reinforcement learning method for autonomous building energy management control based on the soft actor-critic method and the transformer deep neural network architecture. For the control of a heat pump and an the inlet port of a thermal storage, under consideration of photovoltaic generations and dynamic electricity prices, we formulate the problem as partially observable and use the history of observations to determine the control signals. We show, based on a validated building simulation, that our method outperforms rule-based as well as reinforcement learning methods that use multi layer perceptrons or recurrent neural networks as policy.

This paper presents the design, implementation and validation of a M-Class PMU on a general purpose embedded controller, concurrently used for inverter and grid control tasks, deployed over a unified real-time control environment. The rising number of embedded controllers in active distribution grid opens an opportunity for shared computation and instrumentation resources. Unified real-time control environments can efficiently coordinate multiple embedded controllers, IOs and models from different toolchain. The PMU in this paper, is implemented within the NI Veristand real-time control environment at CoSES laboratory in TU Munich. It uses the existing instrumentation and controller setup for inverter and prosumer control in an active distribution grid laboratory. The PMU passes all Mclass device accuracy tests set by the IEC/IEEE 60255-118-1 standard. The output is compliant to the IEEE-SA C37.118.2 messaging standard and connected to an open source PDC software. The proposed solution demonstrates the possibility of merging different grid control and operation functionalities within the unified Veristand RT control environment.

This paper demonstrates a Power Hardware-in-the-Loop (PHIL) implementation of a decentralized optimal power flow (D-OPF) algorithm embedded into the operations of two microgrids connected by a tie line. To integrate the static behavior of the optimization model, a two layer control architecture is introduced. Underneath the dispatch commands from the D-OPF, a primary control scheme provides instantaneous reaction to the load dynamics. This setup is tested in the PHIL environment of the CoSES Lab in TU Munich. In the experiment, the two microgrids cooperatively optimize their operation through an ADMM based unbalanced D-OPF. The operations is then benchmarked against the exclusive use of primary control, without D-OPF. The decentralized approach outperforms, but also shows minor inefficiencies of integrating optimization methods into the real-time operation of the system.

This paper describes the Power hardware-in-the-loop (PHIL) architecture and capacities of the CoSES laboratory at TU Munich. The lab brings together renewable resources, flexible grid topologies, fully controllable prosumer emulators, a real-time control environment, and an API access for external connection to the lab. The electrical and control design of the lab allows for sophisticated PHIL experiments with an user-friendly implementation. Two experiments are included, to validate the PHIL performance and demonstrate the use of PHIL infrastructure to investigate an OPF algorithm.

The paper has been submitted to PSCC 2022 and is currently awaiting reviews. This paper proposes and implements, a harmonic analysis algorithm for microgrid Power Hardware-in-the-loop (PHIL) experiments, when the point of common coupling (PCC) voltage cannot be directly wired to the local prosumer controllers due to long distances between them. Using frequency-shifting and filtering ideas, the voltage measurement is converted to magnitude and phase information. This is passed over an asynchronous communication link to another controller, where it is recovered into a waveform after delay compensation. The method allows for accurate power calculations and grid synchronization over distributed prosumer controllers. The proposed method can work at different execution rates depending on real time (RT) workload and is shown to be robust against step changes, harmonics and communication delays. The method is demonstrated with two PHIL experiments at the CoSES, TU Munich lab in grid connected and island mode.