Inertia Response Coordination Strategy of Wind Generators and Hybrid Energy Storage and Operation Cost-Based Multi-Objective Optimizing of Frequency Control Parameters

Abstract

Due to the high penetration of renewable energy resources in microgrids (MGs), the grid inertia becomes low which leads to the grid to be vulnerable to large disturbances. The energy storage devices can play an important role to enhance the inertia of MGs. However, due to the high investment cost of storages or their dp/dt limitation, the installed energy storages cannot cover the challenge of high df/dt. A prominent solution to solve the problem is to use the inertia response of the wind generators. However, relatively high second frequency nadir is the main drawback of using the inertia response of the wind generators which may impose an extensive disturbance to MGs. Accordingly, a coordinated operation strategy for MGs between wind generator and hybrid energy storage (HES) system is proposed in this paper. In addition, to improve the inertia response of the MG; providing high-quality communication infrastructures with low delay and increasing the Ultracapacitor capacity have been paid attention. In this paper, the costs of the installed Ultracapacitor and quality of communication services are defined as the operation cost. Guaranteeing enough frequency damping for the MG with low operation cost are two conflict objectives. Therefore, a multi-objective optimization method is used to set the controllers' values and reduce the operation cost. The results confirmed that the effectiveness of the proposed strategy to control hybrid power storage in coordination with the wind generator and the frequency recovery process is improved. Also, employing the optimum values guaranteed the frequency damping effectively with low operation cost. The Integral Absolute Error (IAE) value and operation cost are reduced by 13.6% and 32%, respectively. Also, the simulation results show that the maximum MG frequency deviation and maximum df/dt is well compatible with different standards in the presence of load perturbations and different wind speeds.INDEX TERMS Microgrid (MG), Frequency control, Wind generator, Hybrid energy storage (HES), Ultra-capacitor, Inertia response, Multi-objective optimization.

A novel output power determination and power distribution of hybrid energy storage system for wind turbine power smoothing

“…In islanded mode, the HESS is not only responsible for compensating for power fluctuations established by the wind turbine but also it must participate in balancing the generated and load powers such as other batteries. In this regard, the HESS fixes the voltage of the DC bus on the value decided by the droop controller, not only to compensate for the power fluctuations but also to satisfy a part of the microgrid power mismatch (The difference between the generation and load powers) [39,40]. Figure 12 shows the control scheme of the HESS and other batteries in islanded mode.…”

The Impact of Frequency Support by Wind Turbines on the Small-Signal Stability of Power Systems

“…For example, coordinated control of both the inertial and primary frequency support is described in [34]. In [35], the model for inertial response includes hybrid energy storage and communication delays. Finally, in [36], the control gains were considered time variant due to the boundary conditions, such as the wind speed.…”

PMSM Speed Control Based on Particle Swarm Optimization and Deep Deterministic Policy Gradient under Load Disturbance

“…m and d are the number of particles and dimension of the searching space, respectively. The individual best position P n and global best position P g are expressed as follows: The integral absolute error (IAE), integral square error (ISE), integral time absolute error (ITAE), integral time square error (ITSE), and integral square time error (ISTE) are popular objective functions [42][43][44]. In this study, the IAE was adopted as the fitness function, which is calculated as follows:…”