Control Strategy For Islanded Operation Research Articles

Planning of distribution networks islanded operation: from simulation to live demonstration

The integration of distributed Battery Energy Storage Systems (BESS) at the Medium Voltage (MV) and Low Voltage (LV) networks increases the distribution grid flexibility to deal with high penetration of Renewable Energy Sources (RES). In addition, it also enables the deployment of key self-healing functionalities, which allow the islanded operation of small sections of the distribution network. However, new planning and real-time operation strategies are required to allow the BESS coordinated control, as well as a cost-effective and stable operation. This paper presents new tools developed for the planning and real-time operation of distribution networks integrating BESS, particularly when operating islanding. For real-time operation, a short-term emergency operation-planning tool assesses the feasibility of islanded operation of a small section of the distribution network. The long-term impact of a BESS control strategy for islanded operation is assessed through a Life Cycle Analysis (LCA) tool. The results and implementation experience in real distribution network are also discussed.

Integrated Control Strategy for Islanded Operation in Smart Grids: Virtual Inertia and Ancillary Services

Distributed generation has become a consolidated phenomenon in distribution grids in the last few years. Even though the matter is very articulated and complex, islanding operation of distribution grids is being considered as a possible measure to improve service continuity. In this paper, a novel static converter control strategy to obtain frequency and voltage regulation in an islanded distribution grid is proposed. Two situations are investigated: in the former, one electronic converter and one synchronous generator are present, while in the latter only static generation is available. In the first case, converter control will realize virtual inertia and efficient frequency regulation by mean of a PID regulator; this approach allows to emulate high equivalent inertia, hence limiting the rate of change of frequency and maximum frequency deviation, and, in the meantime, to obtain faster frequency regulation, which could not be possible with traditional regulators. In the second situation, a Master–Slave approach will be adopted to maximize frequency and voltage stability. Even though the presented results are obtained in a grid with only two generators, the proposed approach can be extended to more general configurations with few generation units. Simulation results confirm that the proposed control allows islanded operation with high frequency and voltage stability under heavy load variations.

Robust Decomposition and Structured Control of an Islanded Multi-DG Microgrid

This paper presents a new robust control strategy for islanded operation of a microgrid consisting of several distributed generation (DG) units with arbitrary topology. Each DG unit is connected to its local load through a voltage-source converter, a series RL filter and a step-up transformer. The multi-DG microgrid with arbitrary connectivity graph is modeled as a linear time-invariant system subject to a parametric, norm-bounded uncertain block. By utilizing the developed model for multi-DG microgrids, a systematic approach for the design of structured dynamic output feedback control is proposed. A convex optimization problem is developed which yields a low-order dynamic controller of arbitrary structure such that the microgrid channels are all decoupled at the presence of load parameter uncertainties. Simulation case studies performed in MATLAB/SimPowerSystems Toolbox verify the performance of the proposed strategy.

Decentralised robust T‐S fuzzy controller for a parallel islanded AC microgrid

This study proposes a decentralised robust fuzzy control strategy for islanded operation of an AC microgrid with voltage source inverters. The objective is to design a robust controller for regulating the load voltage and sharing power among distributed generators (DGs) in the presence of uncertainties in the system and non-linear loads. The AC microgrid consists of parallel DGs connected to a main AC bus. A Takagi-Sugeno fuzzy approach is developed in this article to achieve stability and desired performance in dealing with non-linearities in the islanded microgrid and H ∞ criterion is used to obtain a robust control strategy in presence of uncertainties raised by unmodelled and high frequency dynamics. Therefore, a non-convex condition in H ∞ optimisation problem is converted to a convex linear matrix inequality (LMI) condition and is solved by MATLAB LMI toolbox. In order to develop a decentralized system, P–f and Q–V droop controllers are used to specify set-points for local inverter controllers in each DG. The effectiveness of the proposed control strategy in presence of constant power load and DG accidental outage is validated by the simulation of a microgrid test system in MATLAB SimPowerSystems toolbox. Comparison with cascaded proportional integral controller shows advantages of robust T-S controller.

Fractional-Order Sliding-Mode Control of Islanded Distributed Energy Resource Systems

This paper proposes a voltage control strategy for islanded operation of dispatchable electronically coupled distributed energy resource (DER) systems, for remote (off grid) electrification systems. The proposed control strategy is based on fractional-order sliding-mode control, offers black-start functionality, maintains the quality of the output voltage of the host DER system in spite of unbalanced and/or distorted load currents, and ensures protection of the power-electronic interface to external faults. Moreover, the fractional derivative order of the controller can be used as an additional tuning parameter. Performance of the proposed control strategy is demonstrated through time-domain simulation of single- and multi-DER islanded networks, starting from black-start and subjected to various operating scenario, and it is also compared to the performance of a proportional-integral (PI)-based control strategy.