Solving Load Phase Balancing Problem in LV Distribution Networks by Chaotic Simulated Annealing

2012 ◽  
Vol 463-464 ◽  
pp. 689-693 ◽  
Author(s):  
Chun Guo Fei
Keyword(s):  
Simulated Annealing ◽  
Load Balancing ◽  
Objective Function ◽  
Heuristic Algorithm ◽  
Energy Function ◽  
Current Flow ◽  
Low Voltage ◽  
Distribution Networks ◽  
Maximum Difference ◽  
Chaotic Simulated Annealing

Phase balancing problem is to make a feeder system balanced in terms of phases in low voltage (LV) distribution networks. In this paper, we investigate the use of chaotic simulated annealing (CSA) for realize phase balancing in the low voltage circuit of the distribution network. The network energy function of the CSA is constructed for objective function that defined the load balancing problem. The CSA is applied to solve the problem when load is represented in terms of current flow at the connection points. The results obtained using CSA are compared with those from a heuristic algorithm. Simulations results show that the CSA is very effective and outperforms the heuristic algorithm in terms of the maximum difference of the phase currents

Test Pattern Generation of VLSI Circuits Using Hopfield Neural Networks

2010 ◽  
Vol 29-32 ◽  
pp. 1034-1039
Author(s):  
Zhong Liang Pan ◽  
Ling Chen ◽  
Guang Zhao Zhang
Keyword(s):  
Neural Networks ◽  
Simulated Annealing ◽  
Energy Function ◽  
Digital Circuits ◽  
Test Pattern ◽  
Pattern Generation ◽  
Vlsi Circuits ◽  
Hopfield Neural Networks ◽  
Test Pattern Generation ◽  
Chaotic Simulated Annealing

A new test pattern generation method for the stuck-at faults in VLSI circuits is presented in this paper, the method uses Hopfield neural networks and chaotic simulated annealing. The Hopfield neural network corresponding to a digital circuit is built, the test patterns of faults in digital circuits are produced by computing the optima of the energy function. A chaotic simulated annealing algorithm is designed, which combines the features of chaotic systems and conventional simulated annealing, it is able to take the advantages of the stochastic properties and global search ability of chaotic system. The algorithm is used to compute the optima of the energy function of neural networks in order to produce the test patterns of faults. Experimental results show that the test pattern generation method proposed in this paper can produce the test patterns in short time for both single stuck-at faults and multiple stuck-at faults in digital circuits.

scholarly journals Bi-Level Phase Load Balancing Methodology with Clustering-Based Consumers’ Selection Criterion for Switching Device Placement in Low Voltage Distribution Networks

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 542
Author(s):  
Gheorghe Grigoraș ◽  
Bogdan-Constantin Neagu ◽  
Florina Scarlatache ◽  
Livia Noroc ◽  
Ecaterina Chelaru
Keyword(s):  
Decision Making ◽  
Load Balancing ◽  
Low Voltage ◽  
Selection Criterion ◽  
Distribution Networks ◽  
Computational Time ◽  
Smart Devices ◽  
Remote Communication ◽  
Full Implementation ◽  
Starting Point

In the last years, the distribution network operators (DNOs) assumed transition strategies of the electric distribution networks (EDNs) towards the active areas of the microgrids where, regardless of the operating regimes, flexibility, economic efficiency, low power losses, and high power quality are ensured. Artificial intelligence techniques, combined with the smart devices and real-time remote communication solutions of the enormous data amounts, can represent the starting point in establishing decision-making strategies to solve one of the most important challenges related to phase load balancing (PLB). In this context, the purpose of the paper is to prove that a decision-making strategy based on a limited number of PLB devices installed at the consumers (small implementation degree) leads to similar technical benefits as in the case of full implementation in the EDNs. Thus, an original bi-level PLB methodology, considering a clustering-based selection criterion of the consumers for placement of the switching devices, was proposed. A real EDN from a rural area belonging to a Romanian DNO has been considered in testing the proposed methodology. An implementation degree of the PLB devices in the EDN by 17.5% represented the optimal solution, leading to a faster computational time with 43% and reducing the number of switching operations by 92%, compared to a full implementation degree (100%). The performance indicators related to the unbalance factor and energy-saving highlighted the efficiency of the proposed methodology.

scholarly journals Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-Based Algorithm

2020 ◽  
Author(s):  
Gheorghe Grigoras ◽  
Bogdan-Constantin Neagu ◽  
Mihai Gavrilas ◽  
Ion Tristiu ◽  
Constantin Bulac
Keyword(s):  
Load Balancing ◽  
Distribution Systems ◽  
Energy Savings ◽  
Low Voltage ◽  
Distribution Networks ◽  
Hybrid Structure ◽  
Optimal Operation ◽  
Time Interval ◽  
Voltage Distribution ◽  
Load Balancing Algorithm

In the electric distribution systems, the “Smart Grid” concept is implemented to encourage energy savings and integration of the innovative technologies, helping the Distribution Network Operators (DNOs) in choosing the investment plans which to lead the optimal operation of the networks and increasing the energy efficiency. In this context, a new phase load balancing algorithm was proposed to be implemented in the low voltage distribution networks with hybrid structures of the consumption points (switchable and non-switchable consumers). It can work in both operation modes (on-line and off-line), uploading information from different databases of the DNO which contain: the consumers’ characteristics, the real loads of the consumers integrated into the Smart Metering System (SMS), and the typical load profiles for the consumers non-integrated in the SMS. The algorithm was tested in a real network, having a hybrid structure of the consumption points, on a time interval by 24 hours. The obtained results were analyzed and compared with other algorithms from the heuristic (Minimum Count of Loads Adjustment algorithm) and the metaheuristic (Particle Swarm Optimization and Genetic Algorithms) categories. The best performances were provided by the proposed algorithm, such that the unbalance coefficient resulted in the smallest value (1.0017). The phase load balancing led to the following technical effects: decreasing the average current in the neutral conductor with 94% and for the energy losses with 61.75 %, and increasing the minimum value of the phase voltage at the farthest pillar with the 7.14 %, compared to the unbalanced case.

scholarly journals Optimal Phase Load Balancing in Low Voltage Distribution Networks Using a Smart Meter Data-Based Algorithm

Mathematics ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 549 ◽  
Author(s):  
Gheorghe Grigoraș ◽  
Bogdan-Constantin Neagu ◽  
Mihai Gavrilaș ◽  
Ion Triștiu ◽  
Constantin Bulac
Keyword(s):  
Load Balancing ◽  
Distribution Systems ◽  
Energy Savings ◽  
Low Voltage ◽  
Distribution Networks ◽  
Hybrid Structure ◽  
Optimal Operation ◽  
Voltage Distribution ◽  
Average Current ◽  
Load Balancing Algorithm

In the electric distribution systems, the “Smart Grid” concept is implemented to encourage energy savings and integration of the innovative technologies, helping the distribution network operators (DNOs) in choosing the investment plans which lead to the optimal operation of the networks and increasing the energy efficiency. In this context, a new phase load balancing algorithm was proposed to be implemented in the low voltage distribution networks with hybrid structures of the consumption points (switchable and non-switchable consumers). It can work in both operation modes (real-time and off-line), uploading information from different databases of the DNO which contain: The consumers’ characteristics, the real loads of the consumers integrated into the smart metering system (SMS), and the typical load profiles for the consumers non-integrated in the SMS. The algorithm was tested in a real network, having a hybrid structure of the consumption points, on a by 24-h interval. The obtained results were analyzed and compared with other algorithms from the heuristic (minimum count of loads adjustment algorithm) and the metaheuristic (particle swarm optimization and genetic algorithms) categories. The best performances were provided by the proposed algorithm, such that the unbalance coefficient had the smallest value (1.0017). The phase load balancing led to the following technical effects: decrease of the average current in the neutral conductor and the energy losses with 94%, respectively 61.75%, and increase of the minimum value of the phase voltage at the farthest pillar with 7.14%, compared to the unbalanced case.

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