Constrained population extremal optimization-based robust load frequency control of multi-area interconnected power system

Coordination strategies of distributed energy resources including FESS, DEG, FC and WTG in load frequency control (LFC) scheme of hybrid isolated micro-grid

The high-penetration of distributed generation technologies in the form of MicroGrids (MGs), in recent years, has increased the risk of frequency instability since their energy is supplied by renewable energy resources (RESs) with uncertain nature. Under such circumstances, providing an MG model with an efficient load frequency control (LFC) has a fundamental role in restoring the stability of the unstructured power system. In this study, a hybrid power system with the application of the Tidal Power Unit (TPU) and Vehicle-to-Grid (V2G) is effectively planed as an isolated MG. A new fractional gradient descent (FGD) based on a single-input interval type-2 fuzzy logic controller (SIT2-FLC) is suggested as the main LFC controller, where the footprint of uncertainty (FOU) coefficient of the SIT2-FLC is specifically adjusted to enhance the LFC performance. Additionally, a deep deterministic policy gradient (DDPG) with the actor-critic framework is considered to generate the supplementary control action, which is useful for the frequency stabilization by adapting to the randomness of load disturbances and RESs. Lastly, a model-in-the-loop (MiL) simulation is conducted to appraise the feasibility and applicability of the suggested design method from a systemic perspective.

A Novel Deep Reinforcement Learning Controller Based Type-II Fuzzy System: Frequency Regulation in Microgrids

This paper proposes a novel, unknown input functional observer based optimal load frequency control approach for real-world complex nonlinear power systems. In the proposed control approach, the control signal applied to each power plant is directly estimated via the well-designed functional observer. The proposed functional dynamic estimator is able to handle parametric and nonparametric uncertainties, control loop and sensor faults, unknown inputs, and cyber-attacks. The observer for each power plant is decoupled from the other plants resulting in a more feasible implementation, reducing the complexity of the estimator and improving the reliability of the proposed control system. The applicability of the proposed method is shown on IEEE 39 bus-system divided into three control areas. The effectiveness of the proposed control scheme is verified by comparing results with well-known control schemes. Tolerance of the proposed technique to unknown inputs, uncertainties, and possible cyber-attacks is verified by several simulation scenarios.

A Decentralized Functional Observer Based Optimal LFC Considering Unknown Inputs, Uncertainties, and Cyber-Attacks

The uncertain demeanour from wind generators and loads adversely affect the grid operational stability. Various control approaches have been explored to remedy the system uncertainties while maintaining generation and load demand balance. This study proposes a fuzzy-based proportional–fractional integral–derivative with filter controller to sustain frequency stability in wind integrated power systems having different configurations. The controller parameters have been tuned using a recently developed coyote optimisation algorithm (COA). The proposed control approach is executed and validated on three distinct configurations of two-area power systems. All test models are integrated with a doubly fed induction generator (DFIG) type wind turbine units (WTUs). Different case scenarios have been considered to analyse the efficacy of the proposed control strategy in the presence of WTU. Furthermore, the impact of inertial support delivered by the DFIG-WTU and higher penetration of wind energy in the power system has been studied. The analysis reveals that the control scheme in coordination with WTU support reduces the stress on a wind turbine during the inertial control scheme and maintains the grid frequency stability under unexpected load disturbances. Stability and robustness analysis are also conducted to verify the validity of the introduced control approach.

https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-rpg.2020.0882

Frequency excursion mitigation strategy using a novel COA optimised fuzzy controller in wind integrated power systems

In a high penetrated wind farm power system, wind farms can collaborate to control the power system frequency as like as conventional units. This paper presents a novel model to control the frequency of the wind farm connected to conventional units. Throughout the proposed frequency control, the integral controller, washout filter, and the PID controller could determine the active power variation value in different situations. In fact, a PID controller makes the wind farm aware of power variations. To improve the efficiency of the model, the defined frequency control parameters (i.e., PID coefficients) are optimized based on a multiobjective function using particle swarm optimization algorithm. This study has a unique perspective based on the wind farm collaboration through inertia control, primary frequency control, and supplementary frequency control of the system. A swift power reserve in a stable condition is needed in which wind farm can ameliorate the system frequency response. It is worth saying that the wind farm consists of variable speed turbines, such as a doubly fed induction generator, or a permanent magnet synchronous generator. To assess the performance of the proposed model, it is applied to a typical two-area system and the results are compared.

An Optimal Frequency Control Method Through a Dynamic Load Frequency Control (LFC) Model Incorporating Wind Farm

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An Optimal Frequency Control Method Through a Dynamic Load Frequency Control (LFC) Model Incorporating Wind Farm