Microgrid: planning of active and reactive power loss reduction in distribution network

2016 ◽  
Author(s):  
T.K. Chattopadhyay ◽  
S. Banerjee ◽  
D. Maity ◽  
C.K. Chanda
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Distribution Network ◽  
Loss Reduction ◽  
Active And Reactive Power ◽  
Power Loss Reduction

scholarly journals A Loss Reduction Optimization Method for Distribution Network Based on Combined Power Loss Reduction Strategy

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jihua Xie ◽  
Chang Chen ◽  
Huan Long
Keyword(s):  
Optimization Model ◽  
Power Loss ◽  
Reactive Power ◽  
Distribution Network ◽  
Cost Benefit ◽  
Optimization Method ◽  
Utilization Rate ◽  
Loss Reduction ◽  
Reduction Strategy ◽  
Power Loss Reduction

Power loss reflects the effective utilization rate of energy and the management level of power grids. In this paper, we propose a combined power loss reduction strategy optimization framework to improve the power loss reduction effect in a distribution network. The weak points of the distribution network are analyzed based on power flow calculation. The corresponding power loss reduction strategies are generated considering the following three aspects: replacing distribution lines, distribution transformers, and reactive power compensation. A combined power loss reduction strategy optimization model considering the comprehensive benefits of power loss reduction is established. A method for solving the optimization model based on the cost-benefit ratio is also proposed. Experiments based on the dataset from Tianjin show that the proposed loss reduction optimization method can effectively reduce power loss and formulate a reasonable loss reduction modification scheme in the distribution network.

scholarly journals Voltage profile improvement and losses minimization for Hayin Rigasa radial network Kaduna using distributed generation

2021 ◽  
Vol 5 (1) ◽  
pp. 20-36
Author(s):  
Idris A. Araga ◽  
Abel E. Airoboman ◽  
Simon A. Auta
Keyword(s):  
Distributed Generation ◽  
Power Loss ◽  
Reactive Power ◽  
Circuit Breaker ◽  
Research Work ◽  
Sensitivity Index ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Active And Reactive Power ◽  
Power Loss Reduction

This research work has presented the application of distributed generation (DG) units in a simultaneous placement approach on IEEE 33 radial test systems for validation of the technique with further implementation on 56-Bus Hayin Rigasa feeder. The genetic algorithm (GA) is employed in obtaining the optimal sizes and load loss sensitivity index for locations of the DGs for entire active and reactive power loss reduction. The voltage profile index is computed for each bus of the networks to ascertain the weakest voltage bus of the network before and after DG and circuit breaker allocation. The simultaneous placement approach of the DGs is tested with the IEEE 33-bus test networks and Hayin Rigasa feeder network and the results obtained are confirmed by comparing with the results gotten from separate DGs allocation on the networks. For IEEE 33-bus system, the simultaneous allocation of DGs and of optimal sizes 750 kW, 800 kW and at locations of buses 2 and 6 respectively, lead to a 66.49 % and 68.64 % drop in active and reactive power loss and 3.02 % improvement in voltage profile. For the 56-bus Hayin Rigasa network in Kaduna distribution network, the simultaneous placement of DGs of sizes 1,470 kW and 1490 kW at locations of bus 16 and 23 respectively, lead to a 79.54 % and 73.98 % drop in active and reactive power loss and 15.94 % improvement in voltage profile. From results comparison, it is evident that the allocation of DGs using the combination GA and load loss sensitivity index, gives an improved performance in relations to power loss reduction and voltage profile improvements of networks when compared to without DGs.

scholarly journals ACTIVE POWER LOSS REDUCTION BY SYNTHESIZED ALGORITHM

2018 ◽  
Vol 6 (5) ◽  
pp. 149-156
Author(s):  
K. Lenin
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Harmony Search ◽  
Pso Algorithm ◽  
Loss Reduction ◽  
Exploration And Exploitation ◽  
Swarm Optimization ◽  
De Algorithm ◽  
Power Loss Reduction ◽  
Power Problem

In this paper, Synthesized Algorithm (SA) proposed to solve the optimal reactive power problem. Proposed Synthesized Algorithm (SA) is a combination of three well known evolutionary algorithms, namely Differential Evolution (DE) algorithm, Particle Swarm Optimization (PSO) algorithm, and Harmony Search (HS) algorithm. It merges the general operators of each algorithm recursively. This achieves both good exploration and exploitation in SA without altering their individual properties. In order to evaluate the performance of the proposed SA, it has been tested in Standard IEEE 57,118 bus systems and compared to other standard reported algorithms. Simulation results show’s that Synthesized Algorithm (SA) successfully reduces the real power loss and voltage profiles are within the limits.

scholarly journals Real power loss reduction by hyena optimizer algorithm

2020 ◽  
Vol 9 (3) ◽  
pp. 186
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Mathematical Modelling ◽  
Convergent Evolution ◽  
Power Loss ◽  
Social Relationship ◽  
Reactive Power ◽  
Scent Marking ◽  
Loss Reduction ◽  
Real Power ◽  
Power Loss Reduction ◽  
Power Problem

<p><span>To solve optimal reactive power problem this paper projects Hyena Optimizer (HO) algorithm and it inspired from the behaviour of Hyena. Collaborative behaviour &amp; Social relationship between Hyenas is the key conception in this algorithm. Hyenas a form of carnivoran mammal &amp; deeds are analogous to canines in several elements of convergent evolution. Hyenas catch the prey with their teeth rather than claws – possess hardened skin feet with large, blunt, no retractable claws are adapted for running and make sharp turns. However, the hyenas' grooming, scent marking, defecating habits, mating and parental behaviour are constant with the deeds of other feliforms. Mathematical modelling is formulated for the basic attributes of Hyena. Standard IEEE 14,300 bus test systems used to analyze the performance of Hyena Optimizer (HO) algorithm. Loss has been reduced with control variables are within the limits.</span></p>

Real Power Loss Reduction by Billfish and Red Mullet Optimization Algorithms

2021 ◽  
Author(s):  
Lenin Kanagasabai
Keyword(s):  
Power Loss ◽  
Voltage Stability ◽  
Reactive Power ◽  
Smart Cities ◽  
Fitness Function ◽  
Loss Reduction ◽  
Real Power ◽  
Red Mullet ◽  
Power Loss Reduction ◽  
Continuous Power

In this paper Billfish Optimization Algorithm (BOA) and Red Mullet Optimization (RMO) Algorithm has been designed for voltage stability enhancement and power loss reduction. Electrical Power is one among vital need in the society and also it plays lead role in formation of smart cities. Continuous power supply is essential and mainly quality of the power should be maintained in good mode. In this work real power loss reduction is key objective. Natural hunting actions of Billfish over pilchards are utilized to model the algorithm. Candidate solutions in the projected algorithm are Billfish and population in the exploration space is arbitrarily engendered. Movement of Billfish is high, it will attack the pilchards vigorously and it can’t escape from the attack done by the group of Billfish. Then in this paper Red Mullet Optimization (RMO) Algorithm is proposed to solve optimal reactive power problem. Projected RMO algorithm modeled based on the behavior and characteristics of red mullet. As a group they hunt for the prey and in each group there will be chaser and blocker. When the prey approaches any one of the blocker red mullet then automatically it will turn as new chaser. So roles will interchangeable and very much flexible. At any time chaser will become blocker and any of the blocker will become a chaser with respect to prey position and conditions. Then in that particular area when all the preys are hunted completed then red mullet group will change the area. So there will be flexibility and changing the role quickly with respect to prey position. Alike to that with reference to the fitness function the particle will be chosen as chaser. By means of considering L (voltage stability) - index BOA, and RMO algorithms verified in IEEE 30- bus system. Then without L-index BOA and RMO algorithms is appraised in 30 bus test systems. Both BOA and RMO algorithms condensed the power loss proficiently with improvement in voltage stability and minimization of voltage deviation.

Loss Minimization in Active Distribution Network

2020 ◽  
pp. 119-135 ◽  
Author(s):  
Bawoke Simachew
Keyword(s):  
Power Loss ◽  
Reactive Power ◽  
Electrical Power ◽  
Distribution Network ◽  
Optimization Method ◽  
Energy Utilization ◽  
Optimal Size ◽  
Loss Reduction ◽  
Voltage Profile ◽  
Power Sources

Power loss reduction is an important problem that needs to be addressed with respect to generating electrical power. It is important to reduce power loss using locally generated power sources and/or compensations. This chapter brings a method of presents a method of maximizing energy utilization, feeder loss reduction, and voltage profile improvement for radial distribution network using the active and reactive power sources. Distributed Generation (DG) (wind and solar with backup by biomass generation) and shunt capacitor (QG) for reactive power demand are used. Integrating DG and QG at each bus might reduce the loss but it is economically unaffordable, especially for developing countries. Therefore, the utilization optimization method is required for finding an optimal size and location to feeders for placing QG and DG to minimize feeder loss.

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