Distributed multi-agent scheme to improve dynamic voltage stability of distribution networks

In this paper, a distributed multi-agent scheme is presented for reactive power management with renewable energy sources (RESs). The multi-agent system (MAS) framework is developed for distribution systems to improve the stability which is mostly dominated by voltage and the agents in this framework coordinate among themselves using online information and energy flow. In this paper, the agents basically perform two tasks- reactive power estimation and necessary control actions. The topology of distribution network is used to estimate the required reactive power for maintaining voltage stability where distributed static synchronous compensators (DSTATCOMs) are used to supply this reactive power. The DSTATCOM is controlled by using a linear quadratic regulator (LQR) controller within the agent framework. The proposed scheme is further compared with the conventional approach to validate the simulation results.

Agent-based reactive power management of power distribution networks with distributed energy generation

In this paper, a new agent-based distributed reactive power management scheme is proposed to improve the voltage stability of energy distribution systems with distributed generation units. Three types of agents – distribution system agent, estimator agent, and control agent are developed within the multi-agent framework. The agents simultaneously coordinated their activities through the online information and energy flow. The overall achievement of the proposed scheme depends on the coordination between two tasks – (i) estimation of reactive power using voltage variation formula and (ii) necessary control actions to provide the estimated reactive power to the distribution networks through the distributed static synchronous compensators. A linear quadratic regulator with a proportional integrator is designed for the control agent in order to control the reactive component of the current and the DC voltage of the compensators. The performance of the proposed scheme is tested on a 10-bus power distribution network under various scenarios. The effectiveness is validated by comparing the proposed approach to the conventional proportional integral control approach. It is found that, the agent-based scheme provides excellent robust performance under various operating conditions of the power distribution network.

An alternative LQR-based excitation controller design for power systems to enhance small-signal stability

This paper presents a new approach to design excitation controller for power systems to enhance small-signal stability. Partial feedback linearization scheme is used to design the controller for a linearized power system model which transforms a part of this model into a new system through linear coordinate transformation. In this paper, the excitation control law as a function of state variables is determined from the dynamics of the partly transformed new system provided that the controller stabilizes the remaining dynamics of the system which are not transformed through feedback linearization. The stability of the remaining dynamics is also discussed in this paper. Since the proposed control scheme uses state variables as feedback, it is analogous to a linear quadratic regulator (LQR) based excitation controller. Therefore, the performance of the proposed scheme is evaluated on a single machine infinite bus (SMIB) system and compared to that of an LQR controller.

Active power control in an islanded microgrid using DC link voltage status

This paper proposes a power balancing strategy for dispatchable and non-dispatchable sources in an islanded microgrid. This control method enables energy storage system that employs a voltage-band at a dc busbar to maintain grid voltage stability for short period disturbances in a network. This voltage-band, applied to obtain maximum benefit from the storage system, depends on a storage capacity feature to avoid voltage limit violation. In addition, a linear quadratic regulator is employed as a voltage controller to track the reference grid voltage that is obtained from the proposed P/V droop control strategy. In the proposed control method, a long-term energy storage element, such as a battery, also can be used to regulate voltage and deliver insufficient power in a microgrid. It is concluded that the proposed control method exhibits an effective result in voltage and power issue during transient.

Stability enhancement of DFIG wind turbine using LQR pitch control over rated wind speed

A novel pitch control design method is proposed for the doubly fed induction generator (DFIG) wind turbine (WT) using linear quadratic regulator (LQR). A seven-order model represents the DFIG WT which is linearized by truncated Taylor series expansion. A systematic approach is adopted to determine the weighting matrices in LQR design for the optimal solution. Simulations have been carried out to compare the performance of the proposed LQR pitch control method against a PI pitch control for small and large disturbances. It is shown that the proposed control method enhances low-voltage ride-through capability and improves system damping under large disturbances.

Association between obesity and diabetes using nested linear models

A data source with 7260 cases from the prospective observational study was used. Cases included both sexes and age ranging between 20yr and 7Oyr. Chi-squared tests and linear models were used to examine the effects of age (linear and quadratic), sex, smoking habit (currently a smoker or non-smoker), presence or absence of type 2 diabetes on obesity as measured by body mass index (BMI) and waist to hip ratio (WHR). Both these measures of
obesity were significantly affected by age, sex and the presence of diabetes. Cases with diabetes were significantly more obese (10%) between the ages 40yr to 59yr compared to patients without diabetes. These results accentuate the need to further examine the association between age, diabetes and obesity and other risk factors with cardiovascular diseases.