B3LYP Study on Reduction Mechanisms from O2 to H2O at the Catalytic Sites of Fully Reduced and Mixed-Valence Bovine Cytochrome c Oxidases

Reduction mechanisms of oxygen molecule to water molecules in the fully reduced (FR) and mixed-valence (MV) bovine cytochrome c oxidases (CcO) have been systematically examined based on the B3LYP calculations. The catalytic cycle using four electrons and four protons has been also shown consistently. The MV CcO catalyses reduction to produce one water molecule, while the FR CcO catalyses to produce two water molecules. One water molecule is added into vacant space between His240 and His290 in the catalytic site. This water molecule constructs the network of hydrogen bonds of Tyr244, farnesyl ethyl, and Thr316 that is a terminal residue of the K-pathway. It plays crucial roles for the proton transfer to the dioxygen to produce the water molecules in both MV and FR CcOs. Tyr244 functions as a relay of the proton transfer from the K-pathway to the added water molecule, not as donors of a proton and an electron to the dioxygen. The reduction mechanisms of MV and FR CcOs are strictly distinguished. In the FR CcO, the Cu atom at the CuB site maintains the reduced state Cu(I) during the process of formation of first water molecule and plays an electron storage. At the final stage of formation of first water molecule, the Cu(I) atom releases an electron to Fe-O. During the process of formation of second water molecule, the Cu atom maintains the oxidized state Cu(II). In contrast with experimental proposals, the K-pathway functions for formation of first water molecule, while the D-pathway functions for second water molecule. The intermediates, PM, PR, F, and O, obtained in this work are compared with those proposed experimentally

Robust Control of Hydro-Thermal Power System Considering Energy Capacitor System

This article proposes a robust controller design of hydro-thermal power system considering of the thermal power plant area connected to the hydro power plant area. The automation generation control of an interconnected hydro-thermal power system with a small Energy Capacitor System (ECS) augmented to both area has been investigated. The controller is used in order to control the frequency robustly and to improve the power system stability due to the uncertainties in load change and energy capacitors in the system. The power from the load changes are introduced into the system and treated it as the uncertainty during the design process. The H-infinity loop-shaping design procedure (H-infinity LSDP) is adopted as the control design procedure in this study. The results reveal that H-infinity LSDP can achieve higher performance and more robustness compared with PID controller

Power System Stabilizer Tuning Based on Multiobjective Design Using Hierarchical and Parallel Micro Genetic Algorithm

In order to achieve the optimal design based on some specific criteria by applying conventional techniques, sequence of design, selected locations of PSSs are critical involved factors. This paper presents a method to simultaneously tune PSSs in multimachine power system using hierarchical genetic algorithm (HGA) and parallel micro genetic algorithm (parallel micro-GA) based on multiobjective function comprising the damping ratio, damping factor and number of PSSs. First, the problem of selecting proper PSS parameters is converted to a simple multiobjective optimization problem. Then, the problem is solved by a parallel micro GA based on HGA. The stabilizers are tuned to simultaneously shift the lightly damped and undamped oscillation modes to a specific stable zone in the s-plane and to self identify the appropriate choice of PSS locations by using eigenvalue-based multiobjective function. Many scenarios with different operating conditions have been included in the process of simultaneous tuning so as to guarantee the robustness and their performance. A 68-bus and 16-generator power system has been employed to validate the effectiveness of the proposed tuning method

New heuristic-based design of robust power system stabilizers

This paper proposes a new robust design of power system stabilizers (PSSs) in a multimachine power system using a heuristic optimization method. The structure of each PSS used is similar to that of a conventional lead/lag stabilizer. The proposed design regards a multimachine power system with PSSs as a multi-input multi-output (MIMO) control system. Additionally, a multiplicative uncertainty model is taken into account in the power system representation. Accordingly, the robust stability margin can be guaranteed by a multiplicative stability margin (MSM). The presented method utilizes the MSM as the design specification for robust stability. To acquire the control parameters of PSSs, a control design in MIMO system is formulated as an optimization problem. In the selection of objective function, not only disturbance attenuation performance but also robust stability indices are considered. Subsequently, the hybrid tabu search and evolutionary programming (hybrid TS/EP) is employed to search for the optimal parameters. The significant effects of designed PSSs are investigated under several system operating conditions

Genetic-Moth Swarm Algorithm for Optimal Placement and Capacity of Renewable DG Sources in Distribution Systems

This paper presents a hybrid approach based on the Genetic Algorithm (GA) and Moth Swarm Algorithm (MSA), namely Genetic Moth Swarm Algorithm (GMSA), for determining the optimal location and sizing of renewable distributed generation (DG) sources on radial distribution networks (RDN). Minimizing the electrical power loss within the framework of system operation and under security constraints is the main objective of this study. In the proposed technique, the global search ability has been regulated by the incorporation of GA operations with adaptive mutation operator on the reconnaissance phase using genetic pathfinder moths. In addition, the selection of artificial light sources has been expanded over the swarm. The representation of individuals within the three phases of MSA has been modified in terms of quality and ratio. Elite individuals have been used to play different roles in order to reduce the design space and thus increase the exploitation ability. The developed GMSA has been applied on different scales of standard RDN of the (33 and 69-bus) power systems. Firstly, the most adequate buses for installing DGs are suggested using Voltage Stability Index (VSI). Then the proposed GMSA is applied to reduce real power generation, power loss, and total system cost, in addition, to improve the minimum bus voltage and the annual net saving by selecting the DGs size and their locations. Furthermore, GMSA is compared with other literature methods under several power system constraints and conditions, in single and multi-objective optimization space. The computational results prove the effectiveness and superiority of the GMSA with respect to power loss reduction and voltage profile enhancement using a minimum size of renewable DG units

A bridge between robustness and simplicity: practical control design for complex systems

Automatic control design has been one of the major subjects in real-world system design/operation and is becoming much more significant today in accordance with increasing size, changing structure, uncertainties and complexity of artificial industry systems. A major challenge in a new environment is to integrate computing, communication and control into appropriate levels of real-world systems operation and control. In practice, many control systems usually track different control objectives such as stability, disturbance attenuation and reference tracking with considering practical constraints, simultaneously. At the moment in the industry applications, it is desirable to meet all specified goals using the controllers with simple structures. Since, practically these controllers are commonly designed based on experiences, classical and trial-and-error approaches, they are incapable of obtaining good dynamical performance to capture all design objectives and specifications for a wide range of operating conditions and various disturbances. It is significant to note that because of using simple structure, pertaining to the low-order control synthesis for dynamical systems in the presence of strong constraints and tight objectives are few and restrictive. Under such conditions, the synthesis process may not approach to a strictly feasible solution. Therefore, the most of robust and optimal approaches suggest complex state-feedback or high-order dynamic controllers. Moreover in the most of proposed approaches, a single performance criterion has been used to evaluate the robustness of resulted control systems. This research addresses three systematical, fast and flexible algorithms to design of low order or static output controllers for dynamical systems. The developed strategies attempt to invoke the strict conditions and bridge the gap between the power of optimal/robust control theory and industrial control design. To illustrate the effectiveness of the proposed control strategies, they have been applied to several complex systems in the electric industry

MSA for Optimal Reconfiguration and Capacitor Allocation in Radial/Ring Distribution Networks

This work presents a hybrid heuristic search algorithm called Moth Swarm Algorithm (MSA) in the context of power loss minimization of radial distribution networks (RDN) through optimal allocation and rating of shunt capacitors for enhancing the performance of distribution networks. With MSA, different optimization operators are used to mimic a set of behavioral patterns of moths in nature, which allows for flexible and powerful optimizer. Hence, a new dynamic selection strategy of crossover points is proposed based on population diversity to handle the difference vectors Lévy-mutation to force MSA jump out of stagnation and enhance its exploration ability. In addition, a spiral motion, adaptive Gaussian walks, and a novel associative learning mechanism with immediate memory are implemented to exploit the promising areas in the search space. In this article, the MSA is tested to adapt the objective function to reduce the system power losses, reduce total system cost and consequently increase the annual net saving with inequity constrains on capacitor size and voltage limits. The validation of the proposed algorithm has been tested and verified through small, medium and large scales of standard RDN of IEEE (33, 69, 85-bus) systems and also on ring main systems of 33 and 69-bus. In addition, the obtained results are compared with other algorithms to highlight the advantages of the proposed approach. Numerical results stated that the MSA can achieve optimal solutions for losses reduction and capacitor locations with finest performance compared with many existing algorithms

Two-phase optimal PMU placement considering complete topological observability level for single line contingency

In order to monitor constantly power systems states, the accurate monitoring technique by Phasor Measurement Unit (PMU) has drawn attention. The use of the PMU as a meter in state estimation for constant understanding the power system state will improve the estimation accuracy and the computational burden. However, the number and the location of installed PMUs that realize topological observability for state estimation have to be optimized because of the economic perspective. Furthermore, the PMU measurement network redundancy for a single line contingency in a power system needs to be taken into account. Hence, this research proposes an optimal PMU placement by a two-phase optimization method. The first phase strategy minimizes the number of placed PMUs and the second phase strategy maximizes a PMU measurement redundancy index called Complete Topological Observability Level (CTOL) for a single line contingency. Improving the CTOL means that the PMU placement has higher possibility to carry out state estimation by complete topological observability. Because of the problem characteristics, Mutation and Reposition Binary Particle Swarm Optimization (MRBPSO) for the first phase, and Simulated Annealing (SA) for the second phase are applied to solve the problem. As a result of optimization, the suboptimal solution in the second phase is improved compared to the first one in each parametric constraint in example power systems of IEEE 57-bus and RTS-96

Reliably optimal PMU placement using disparity evolution-based genetic algorithm

Phasor Measurement Units (PMUs) are an important component in Wide Area Protection (WAP)- based operations in power systems. It is needed that a certain placement scheme of PMUs is suggested if power system scale gets larger. The optimal placement of PMU in power systems has been considered and formulated in order to reduce the number of installed PMUs while accomplishing a desired level of reliability of observation. Optimal PMU Placement (OPP) problem as the combinatorial optimization problem has been formulated to determine the minimum PMU location in the power system. In this paper, Disparity Evolution-type Genetic Algorithm (DEGA) based on disparity theory of evolution is applied. Genetic Algorithm (GA) is employed for the purpose of comparison with DEGA. The optimization model is solved for IEEE 118 standard bus system. DEGA can find better placement suggestion compared with GA because of the nature of evolution that models the double spiral structure of DNA to hold the diversity of population

Influence of measurement uncertainty propagation in current-channel-selectable multi objective optimal phasor measurement unit placement problem

This paper proposes current-channel-selectable multi objective optimal Phasor Measurement Unit (PMU) placement problem with measurement uncertainty propagation. In proposed Multi Objective Optimal PMU Placement (MOOPP) problem, allocation of the current phasor channel of the PMU can be selected for reducing the total PMU placement cost. However, in practice, uncertainty of measurement makes the estimation error bigger because of use of pseudo measurement by the current channel selection. This paper proposes the optimal PMU placement method considering minimizing both the total PMU placement cost and the state estimation error with uncertainty propagation. The result of the numerical experiment demonstrates the advantage of considering the measurement uncertainty propagation, compared to the conventional method which ignores it, in IEEE New England 39-bus test system. As a result, the proposed method obtained a better Pareto solution compared to the conventional methods because of consideration of measurement uncertainty in the pseudo measurements