scholarly journals Application of Time-Voltage Characteristics in Overcurrent Scheme to Reduce Arc-Flash Incident Energy for Safety and Reliability of Microgrid Protection

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8074
Author(s):  
Feras Alasali ◽  
Saad M. Saad ◽  
Naser El-Naily ◽  
Anis Layas ◽  
Abdelsalam Elhaffar ◽  
...  
Keyword(s):  
Incident Energy ◽  
Water Cycle ◽  
Complex Structure ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimization Approach ◽  
Coordination Problem ◽  
Protection Method ◽  
Optimal Coordination ◽  
Arc Flash

The interconnection between diverse Distribution Generations (DGs) that utilize various technologies and complex structure of networks are the most characteristic of modern Distribution Networks (DN). The wide adoption of DGs considerably affects the power flow dynamics in the DN and consequently the fault characteristics. The excessive level of fault currents can pose risks of heat (high temperature) and pressure in accordance to Arc Flash (AF) incident energy in microgrids. This research studies the relationship between AF severity and the solving of coordination problem of Overcurrent Relays (OCRs) in DN, and introduces a novel equation that considers the AF qualities in solving the coordination problem for OCRs. In this study, a novel optimization problem, the AF severity with the optimal coordination of OCRs in DN is presented and the Water Cycle Optimization Method (WCOM) is employed to find the best combination of the OCR’s settings in the DN while considering the AF induced energy. The proposed optimization approach and the novel equation are evaluated with an IEC microgrid and compared with the conventional protection method and Particle Swarm Optimization (PSO) used in optimizing the coordination of OCR in the DN. The optimal settings of the OCR scheme are achieved and examined on the modified IEC microgrid benchmark system. In order to verify the result, an industrial simulation package (ETAP) and OCR (GE Multiin, model-750/760) was used in this work.

scholarly journals Hybrid Harmony Search Algorithm Applied to the Optimal Coordination of Overcurrent Relays in Distribution Networks with Distributed Generation

2021 ◽  
Vol 11 (19) ◽  
pp. 9207
Author(s):  
Sergio D. Saldarriaga-Zuluaga ◽  
Jesús M. López-Lezama ◽  
Nicolás Muñoz-Galeano
Keyword(s):  
Distributed Generation ◽  
Search Algorithm ◽  
Short Circuit ◽  
Harmony Search ◽  
Distribution Networks ◽  
Harmony Search Algorithm ◽  
Small Scale ◽  
Coordination Problem ◽  
Overcurrent Relays ◽  
Optimal Coordination

In recent years, distributed generation (DG) has become more common in modern distribution networks (DNs). The presence of these small-scale generation units within a DN brings new challenges to protection engineers, since short-circuit currents tend to increase; additionally, as with microgrids, modern DNs may feature several operational modes depending on their topology and the availability of DG. This paper presents a methodology for the optimal coordination of overcurrent relays (OCRs) in modern DNs with a high presence of DG. Given the fact that protection coordination is a non-linear and non-convex optimization problem, a hybrid harmony search and simulated annealing (HS-SA) approach was implemented for its solution and compared against other techniques, such as conventional HS, genetic algorithm (GA), particle swarm optimization (PSO) and hybrid PSO-HS. Several tests were performed on a DN, considering different operative scenarios as a function of the DG available within the network. A comparison with other works reported in the specialized literature was carried out, evidencing the applicability and effectiveness of the HS-SA technique in solving the optimal OCR coordination problem in modern DNs.

The Application of the Combination of Monte Carlo Optimization Method based QSAR Modeling and Molecular Docking in Drug Design and Development

2020 ◽  
Vol 20 (14) ◽  
pp. 1389-1402 ◽  
Author(s):  
Maja Zivkovic ◽  
Marko Zlatanovic ◽  
Nevena Zlatanovic ◽  
Mladjan Golubović ◽  
Aleksandar M. Veselinović
Keyword(s):  
Monte Carlo ◽  
Molecular Docking ◽  
Computer Calculation ◽  
Molecular Graph ◽  
Optimization Method ◽  
Docking Studies ◽  
Optimization Approach ◽  
Qsar Modeling ◽  
Monte Carlo Optimization ◽  
Molecular Docking Studies

In recent years, one of the promising approaches in the QSAR modeling Monte Carlo optimization approach as conformation independent method, has emerged. Monte Carlo optimization has proven to be a valuable tool in chemoinformatics, and this review presents its application in drug discovery and design. In this review, the basic principles and important features of these methods are discussed as well as the advantages of conformation independent optimal descriptors developed from the molecular graph and the Simplified Molecular Input Line Entry System (SMILES) notation compared to commonly used descriptors in QSAR modeling. This review presents the summary of obtained results from Monte Carlo optimization-based QSAR modeling with the further addition of molecular docking studies applied for various pharmacologically important endpoints. SMILES notation based optimal descriptors, defined as molecular fragments, identified as main contributors to the increase/ decrease of biological activity, which are used further to design compounds with targeted activity based on computer calculation, are presented. In this mini-review, research papers in which molecular docking was applied as an additional method to design molecules to validate their activity further, are summarized. These papers present a very good correlation among results obtained from Monte Carlo optimization modeling and molecular docking studies.

scholarly journals Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1452
Author(s):  
Cristian Mateo Castiblanco-Pérez ◽  
David Esteban Toro-Rodríguez ◽  
Oscar Danilo Montoya ◽  
Diego Armando Giral-Ramírez
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Power Balance ◽  
Continuous Version ◽  
Discrete Part

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.

Multi-objective optimization of optimal capacitor allocation in radial distribution systems

2020 ◽  
Vol 21 (3) ◽  
Author(s):  
Sayed Mir Shah Danish ◽  
Mikaeel Ahmadi ◽  
Atsushi Yona ◽  
Tomonobu Senjyu ◽  
Narayanan Krishna ◽  
...  
Keyword(s):  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Reactive Power ◽  
Stability Index ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Size ◽  
Multi Objective Optimization ◽  
Multi Objective

AbstractThe optimal size and location of the compensator in the distribution system play a significant role in minimizing the energy loss and the cost of reactive power compensation. This article introduces an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using multi-objective optimization method. A new objective function different from literature is adapted to enhance the overall system voltage stability index, minimize power loss, and to achieve maximum net yearly savings. However, the capacitor sizes are assumed as discrete known variables, which are to be placed on the buses such that it reduces the losses of the distribution system to a minimum. Load sensitive factor (LSF) has been used to predict the most effective buses as the best place for installing compensator devices. IEEE 34-bus and 118-bus test distribution systems are utilized to validate and demonstrate the applicability of the proposed method. The simulation results obtained are compared with previous methods reported in the literature and found to be encouraging.

scholarly journals Evolution of coordination in pairwise and multi-player interactions via prior commitments

2021 ◽  
pp. 105971232199316
Author(s):  
Ndidi Bianca Ogbo ◽  
Aiman Elragig ◽  
The Anh Han
Keyword(s):  
Autonomous Agents ◽  
Evolutionary Game ◽  
Multi Agent Systems ◽  
Coordination Problem ◽  
Mutual Cooperation ◽  
Payoff Structure ◽  
Optimal Coordination ◽  
Selection Intensities ◽  
Collective Benefit ◽  
High Level

Upon starting a collective endeavour, it is important to understand your partners’ preferences and how strongly they commit to a common goal. Establishing a prior commitment or agreement in terms of posterior benefits and consequences from those engaging in it provides an important mechanism for securing cooperation. Resorting to methods from Evolutionary Game Theory (EGT), here we analyse how prior commitments can also be adopted as a tool for enhancing coordination when its outcomes exhibit an asymmetric payoff structure, in both pairwise and multi-party interactions. Arguably, coordination is more complex to achieve than cooperation since there might be several desirable collective outcomes in a coordination problem (compared to mutual cooperation, the only desirable collective outcome in cooperation dilemmas). Our analysis, both analytically and via numerical simulations, shows that whether prior commitment would be a viable evolutionary mechanism for enhancing coordination and the overall population social welfare strongly depends on the collective benefit and severity of competition, and more importantly, how asymmetric benefits are resolved in a commitment deal. Moreover, in multi-party interactions, prior commitments prove to be crucial when a high level of group diversity is required for optimal coordination. The results are robust for different selection intensities. Overall, our analysis provides new insights into the complexity and beauty of behavioural evolution driven by humans’ capacity for commitment, as well as for the design of self-organised and distributed multi-agent systems for ensuring coordination among autonomous agents.

scholarly journals Optimal Water Quality Sensor Placement by Accounting for Possible Contamination Events in Water Distribution Networks

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 1999
Author(s):  
Malvin S. Marlim ◽  
Doosun Kang
Keyword(s):  
Water Quality ◽  
Water Distribution ◽  
Sensor Placement ◽  
Pso Algorithm ◽  
Distribution Networks ◽  
Fair Value ◽  
Water Distribution Networks ◽  
Optimization Approach ◽  
Protection Measure ◽  
Contamination Events

Contamination in water distribution networks (WDNs) can occur at any time and location. One protection measure in WDNs is the placement of water quality sensors (WQSs) to detect contamination and provide information for locating the potential contamination source. The placement of WQSs in WDNs must be optimally planned. Therefore, a robust sensor-placement strategy (SPS) is vital. The SPS should have clear objectives regarding what needs to be achieved by the sensor configuration. Here, the objectives of the SPS were set to cover the contamination event stages of detection, consumption, and source localization. As contamination events occur in any form of intrusion, at any location and time, the objectives had to be tested against many possible scenarios, and they needed to reach a fair value considering all scenarios. In this study, the particle swarm optimization (PSO) algorithm was selected as the optimizer. The SPS was further reinforced using a databasing method to improve its computational efficiency. The performance of the proposed method was examined by comparing it with a benchmark SPS example and applying it to DMA-sized, real WDNs. The proposed optimization approach improved the overall fitness of the configuration by 23.1% and showed a stable placement behavior with the increase in sensors.

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