Wide-Area Measurement-Based Two-Level Control Design to Tolerate Permanent Communication Failures

Abstract

The operation of modern power systems must meet stability requirements to guarantee the supply of electrical energy. One of these requirements is to ensure that the low-frequency oscillation modes have high damping ratios to avoid angular instability and future power system blackouts. Advances in phasor measurement units (PMUs) have contributed to the development and improvement of wide-area damping controllers (WADCs) capable of increasing the damping rates of the oscillation modes of the system, especially the inter-area modes. Nevertheless, the operation of WADCs is vulnerable to communication failures and cyber-attacks, and if not properly designed the WADC can affect the stability of the entire system. This research proposes a procedure for designing a WADC robust to permanent communication failures using a linear quadratic regulator (LQR) and genetic algorithms. Case studies conducted on an IEEE 68-bus test power system show the effectiveness of the WADC designed by the proposed procedure even when communication failures are occurring in the system. The use of genetic algorithms improves the convergence and results of the LQR-based method.

Internet of Things Application in an Automated Irrigation Prototype Powered by Photovoltaic Energy

“…Portions of water were also considered, which, when added to the soil sample, were equivalent to 9,11,13,15,17,19,21,23,25,27, and 29% of moisture based on mass. The humidity range chosen for calibration was based on the average field capacity and permanent wilting point of the University's experimental area.…”

“…Many control [13][14][15], monitoring [16][17][18], and protection [19][20][21] projects have been developed over the years to guarantee the exploitation of the potential of the photovoltaic generation source in power systems. A set of challenges were encountered regarding the maximum use and operation of photovoltaic generation sources in power systems, but these challenges have been gradually overcome in recent years [22][23][24][25][26].…”

Load Margin Assessment of Power Systems Using Physics-Informed Neural Network with Optimized Parameters

“…Bio-inspired algorithms are optimization algorithms that draw on the principles and inspiration of nature's biological evolution to develop new search tools for optimization problems. Different bio-inspired algorithms have been proposed such as Particle Swarm Optimization [71], Coati Optimization Algorithm [72], Pelican Optimization Algorithm [73], Marine Predators Algorithm [74], Electric Eel Foraging Optimization [75], Hippopotamus Optimization Algorithm [76], Several applications of bio-inspired algorithms in power systems have been proposed over the years such as wide-area damping control design [77,78], electricity theft detection [79], integrated energy system optimization [80], optimization of HVAC systems [81], power system stabilizer design [82], load dispatch for microgrid [83], energy management [84], load profile generation [85], power system state estimation [86], short-term hydrothermal scheduling [87], distributed power generation planning [88], reactive power optimization [89], maximum power point tracking [90], wind turbine placement [91], coordination of directional overcurrent relays [92], placement of electric vehicle charging station [93], optimal DG unit placement [94], power quality disturbances identifi-cation [95], optimal power flow [96]. The use of bio-inspired algorithms to tune traditional ANN is possible and some authors have already pointed out this benefit to improve the generalization capacity of the ANN.…”