Power flow and small signal stability analysis on the interconnected Philippine power grid

SummaryThe Philippines, as one of the developing nations in south-east Asia, has isolated power system networks which bring forth challenges in its operational systems, especially when subjected to a deregulated environment. This paper presents an analysis on the power flow and small signal stability of the interconnected three isolated Philippine Power Grid. To achieve this, eigenvalue analysis is employed to probe the small signal stability of the main power grids. The free software, Power Systems Analysis Toolbox (PSAT), is used to develop the model using MATLAB®/Simulink®. There have been no publicly available studies regarding stability of the proposed link between the major grid and the Mindanao (south island) grid. Participation factors were further studied to determine which states contributes most with the variety of modes. The lowest oscillatory damping modes are also assessed to better understand the systems characteristics

Optimal Integration of the Renewable Energy to the Grid by Considering Small Signal Stability Constraint

In recent decades, one of the main management’s concerns of professional engineers is the optimal integration of various types of renewable energy to the grid. This paper discusses the optimal allocation of one type of renewable energy i.e. wind turbine to the grid for enhancing network’s performance. A multi-objective function is used as indexes of the system’s performance, such as increasing system loadability and minimizing the loss of real power transmission line by considering security and stability of systems’ constraints viz.: voltage and line margins, and eigenvalues as well which is representing as small signal stability. To solve the optimization problems, a new method has been developed using a novel variant of the Genetic Algorithm (GA), specifically known as Non-dominated Sorting Genetic Algorithm II (NSGA-II). Whereas the Fuzzy-based mechanism is used to support the decision makers prefer the best compromise solution from the Pareto front. The effectiveness of the developed method has been established on a modified IEEE 14-bus system with wind turbine system, and their simulation results showed that the dynamic performance of the power system can be effectively improved by considering the stability and security of the system

Optimal placement of FACTS controllers for maximising system loadability by PSO

In this paper, a multi objective-based method has been suggested to enhance the power system loadability with optimal placement of flexible AC transmission system (FACTS) controllers using particle swarm optimisation (PSO) technique. The objective function is to maximise the system loadability subjected to maintaining the system security, integrity, and stability margins within limits by obtaining the optimal location, installation costs, and control settings of the FACTS controllers. The various FACTS controllers, i.e., static var compensator (SVC), thyristor controlled series compensator (TCSC), and unified power flow controller (UPFC), have been considered in this study. The effectiveness of the proposed methodology has been investigated on the standard IEEE 14-bus, 30-bus, and practical Java-Bali 24-bus Indonesian system and the results are compared with the method suggested in the literatures. Moreover, the results obtained by PSO have also been compared with other evolutionary approach, viz., genetic algorithm (GA)

Optimal Placement of A Series FACTS ControllerinJava-Bali 24-bus Indonesian System for Maximizing System Loadability by Evolutionary Optimization Technique

In this paper, a series FACTS controllernamely Thyristor Controller Series Compensator (TCSC) has been suggested to enhance the power system loadability.The location of the controllerand the setting of their control parameters are optimized by one type of Evolutionary Optimization Technique to improve the performance of the power network. The objective functions are to maximize the system loadability whereas maintaining system security and stability margins, e.g., small signal stability, voltage stability index, and line stability factor within limits by considering the investment costs of the controllerand minimizing active power loss of the system. The series FACTS controllerismodeled and incorporated in the Newton Raphson power flow problem. The effectiveness of the proposed methodology has been investigated on a practical Java-Bali 24-bus Indonesian grid syste

Optimal Placement of UPFC for Maximizing System Loadability and Minimize Active Power Losses by NSGA-II

This paper presented application of a new variant of Genetic Algorithm, specialized in multi-objective optimizations problem known as Non-dominated Sorting Genetic Algorithm II (NSGA-II), to obtain the optimal allocation of Unified Power Flow Controller (UPFC) for enhancing the power system loadability as well as minimizing the active power loss in transmission line. An Optimal Power Flow (OPF) problem with mixed integer programming has been formulated for optimizing the above two objectives as well as obtaining the optimal location of the UPFC while maintaining the system security and stability margins, e.g., small signal stability, voltage stability index, and line stability factor. In addition, a fuzzy based mechanism has been employed to extract the best compromise solution from the Pareto front. The effectiveness of the proposed methodology has been investigated on a standard IEEE 30-bus and practical Java­Bali 24-bus of Indonesian systems. Results demonstrate that the static and dynamic performances of the power system can be effectively enhanced by the optimal allocation of the UPFC. Moreover, UPFC installation cost is also calculated and overall performance has been compared with existing method

PSO Based Tuningof FACTS Controllers for Maximizing theWind Energy Penetration in Power Systems

In this paper, a new methodology has been proposed for attaining the maximum instantaneous wind penetration by the optimal placement and setting of Flexible AC Transmission System (FACTS) controllers. Multiple of single type of FACTS controller namely SVC have been used for achieving the maximum wind penetration. Particle Swarm Optimization (PSO) based algorithm has been developed to obtain the maximum instantaneous penetration by adjusting the grid parameters and FACTS controller settings. The developed algorithm has been tested on modified IEEE 14-bus test system. The results have shown the maximum instantaneous wind energy penetration limit in percentage, optimal setting of FACTS controllers and also maximum safe bus loading point explicitly beyond which system drives into instability

Development of PSO Based Control Algorithms for Maximizing Wind Energy Penetration

In this paper, new methodologies have been proposed for attaining the maximum safe instantaneous wind energy penetration. Various types of control algorithms namely, load increase, generation displacement and the combined load increase and generation displacement have been developed to obtain the maximum penetration. Wind Turbine used is DFIG and dynamic model of the system by considering Turbine governor (TG), Automatic voltage regulator (AVR) have been considered. Grid stability at high penetration level is obtained by conducting eigenvalue analysis of the complete power system grid. All the control algorithms are powered by Particle Swarm Optimization Algorithm (PSO) which adjusts the grid parameters for achieving maximum wind penetration. The developed algorithms have been tested with 25-bus, 220kV practical system. The results have shown the maximum safe instantaneous wind energy penetration limit possible by various methodologies proposed

Modelling and Performance Evaluation of ANFIS Controller-Based Bidirectional Power Management Scheme in Plug-in Electric Vehicles Integrated with Electric Grid

A bi-directional power exchange between the plug-in electric vehicle (PEV) and the AC electrical grid is necessary to perform the Vehicle to Grid (V2G) and Grid to Vehicle (G2V) operations. While performing these operations, different power converters and controllers play an important role as mediators between the PEV and electric grid. Various works have demonstrated the utilization of controllers for PEV’s battery power management. However, the existing conventional controllers have technical shortcomings about vulnerability to controller gain, accurate mathematical modelling, poor adaptability, sluggish response to a sudden outburst and lengthy interval execution processing. Therefore, this paper develops an adaptive neuro-fuzzy inference system (ANFIS) control strategy based bidirectional power management scheme to ensure the optimal electrical power flow exchange between the AC electrical grid and battery storage system in PEVs. This paper aims to reduce the stress on the grid power side and utilize the unused power properly. The performance of the ANFIS model is varied using two PEVs based on real-life power consumptions by different loads at home based on five operational modes. Besides, a comparative analysis between the ANFIS controller and the PI controller is carried out to demonstrate the effectiveness of the proposed control scheme. The results illustrate that the proposed ANFIS controller delivers a smoother power injection from the PEV to the AC power grid with the least harmonics as well as achieves a smoother battery profile and less distortion when power is absorbed by PEV battery.publishedVersio

Points to consider in cardiovascular disease risk management among patients with rheumatoid arthritis living in South Africa, an unequal middle income country

ABSTRACT: Background: It is plausible that optimal cardiovascular disease (CVD) risk management differs in patients with rheumatoid arthritis (RA) from low or middle income compared to high income populations. This study aimed at producing evidence-based points to consider for CVD prevention in South African RA patients. Methods: Five rheumatologists, one cardiologist and one epidemiologist with experience in CVD risk management in RA patients, as well as two patient representatives, two health professionals and one radiologist, one rheumatology fellow and 11 rheumatologists that treat RA patients regularly contributed. Systematic literature searches were performed and the level of evidence was determined according to standard guidelines. Results: Eighteen points to consider were formulated. These were grouped into 6 categories that comprised overall CVD risk assessment and management (n=4), and specific interventions aimed at reducing CVD risk including RA control with disease modifying anti-rheumatic drugs, glucocorticoids and non-steroidal anti-inflammatory drugs (n=3), lipid lowering agents (n=8), antihypertensive drugs (n=1), low dose aspirin (n=1) and lifestyle modification (n=1). Each point to consider differs partially or completely from recommendations previously reported for CVD risk management in RA patients from high income populations. Currently recommended CVD risk calculators do not reliably identify South African black RA patients with very high-risk atherosclerosis as represented by carotid artery plaque presence on ultrasound. Conclusions: Our findings indicate that optimal cardiovascular risk management likely differs substantially in RA patients from low or middle income compared to high income populations. There is an urgent need for future multicentre longitudinal studies on CVD risk in black African patients with RA.The first meeting held amongst local Rheumatologists was funded by the South African Arthritis and Rheumatology Association. The studies by Professor González-Gay have been supported by grants from “Fondo de Investigaciones Sanitarias” PI06/0024, PS09/00748, PI12/00060, PI15/00525, PI18/00043, and RD12/0009/0013 and RD16/0012 (RIER) from “Instituto de Salud Carlos III” (ISCIII) (Spain), co-funded by FEDER funds

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5) million) in 2000 to 6.0% (55.5 (44.8–67.9) million) children aged under 5 years in 2017. Areas most affected by double burden of malnutrition were located in Indonesia, Thailand, southeastern China, Botswana, Cameroon and central Nigeria. Our estimates provide a new perspective to researchers, policy makers and public health agencies in their efforts to address this global childhood syndemic