scholarly journals Improved genetic algorithm for distribution system performance analysis

2017 ◽  
Author(s):  
◽  
Zhuoqun Shi
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Load Flow ◽  
Initial Population ◽  
Pareto Optimal ◽  
Power Losses ◽  
Solution Sets ◽  
Cpu Time ◽  
Time Requirements ◽  
Newton Raphson

The incipient smart grid initiative and increasing use of distributed generation, along with classical problems of distribution system reconfiguration and restoration (DSR), have led to the need for efficient and reliable power distribution system simulation tools. One recently developed tool, the Fast Non-dominated Sorting Genetic Algorithm, or FNSGA, has been shown to be very effective at finding Pareto optimal distribution systems that are optimized with respect to voltages, currents, and power losses. Despite its promise, the FNSGA has two shortcomings, which are addressed in this thesis. The first is that it uses a load flow sub-program (to determine voltages, currents, and losses throughout the power system in question) that is based on the classical Newton-Raphson numerical analytical approach. For a variety of reasons, the Newton-Raphson method often encounters convergence problems when applied to distribution (rather than transmission) systems, and it has burdensome memory and CPU time requirements when applied to large systems. In this thesis, the Newton-Raphson load flow program is replaced in the FNSGA with a revised version of the so-called direct method, the principal revision being a coded novel scheme for properly, rapidly, and repeatedly re-numbering the busses and branches in the power system for load flow analysis within the FNSGA. Validation results for the described scheme are presented by comparing results obtained with it and with the Newton-Raphson-based load flow scheme. The principal difference between the two methods is that the computation time is significantly reduced with the revised direct load flow method. The second shortcoming of the FNSGA to be addressed here is that it is not optimized for certain important parameters, namely the initial population size N and the number of generations Gen, which could lead to excessive CPU time requirements. In this thesis, a parametric study was conducted to determine minimum values of N and Gen that lead to reasonably repeatable configurations of a distribution system that are optimized for the multiple objectives of voltages (in the voltage profiles), currents (in the system load balancing index), and power losses. Studies conducted on 16- and 32-bus test systems revealed that, to produce repeatable solution sets in the 16-bus system, optimum values of N and Gen are small enough that CPU times are very small. However, in the 32-bus system, N and Gen need to be so large that CPU times become prohibitive. Presumably, the problem would get worse with even larger systems. Fortunately, a solution to this problem was found, which involves removing certain branches from the pool of possibilities when producing the initial population N in the genetic algorithm. Disqualified branches are those determined in preliminary simulations to never appear in Pareto optimal solution sets. This method was shown to be very effective at leading to small enough optimum values of N and Gen that CPU times are reasonable.

scholarly journals Optimal Network Reconfiguration to Reduce Power Loss Using an Initial Searching Point for Continuous Genetic Algorithm

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Thuan Thanh Nguyen ◽  
Thang Trung Nguyen ◽  
Ngoc Au Nguyen
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Power Loss ◽  
Distribution Systems ◽  
Closed Loop ◽  
Control Variable ◽  
Initial Population ◽  
Network Reconfiguration ◽  
Power Loss Reduction ◽  
Continuous Genetic Algorithm

In this paper, an effective method to determine an initial searching point (ISP) of the network reconfiguration (NR) problem for power loss reduction is proposed for improving the efficiency of the continuous genetic algorithm (CGA) to the NR problem. The idea of the method is to close each initial open switch in turn and solve power flow for the distribution system with the presence of a closed loop to choose a switch with the smallest current in the closed loop for opening. If the radial topology constraint of the distribution system is satisfied, the switch opened is considered as a control variable of the ISP. Then, ISP is attached to the initial population of CGA. The calculated results from the different distribution systems show that the proposed CGA using ISP could reach the optimal radial topology with better successful rate and obtained solution quality than the method based on CGA using the initial population generated randomly and the method based on CGA using the initial radial configuration attached to the initial population. As a result, CGA using ISP can be a favorable method for finding a more effective radial topology in operating distribution systems.

scholarly journals Optimal sizing and location of multiple distributed generation for power loss minimization using genetic algorithm

2019 ◽  
Vol 16 (2) ◽  
pp. 956
Author(s):  
Abdulhamid Musa ◽  
Tengku Juhana Tengku Hashim
Keyword(s):  
Genetic Algorithm ◽  
Distributed Generation ◽  
Distribution System ◽  
Power Loss ◽  
Total Power ◽  
Power Losses ◽  
Loss Minimization ◽  
Power Constraints ◽  
Voltage Deviation ◽  
Power Limits

This paper presents a Genetic Algorithm (GA) for optimal location and sizing of multiple distributed generation (DG) for loss minimization. The study is implemented on a 33-bus radial distribution system to optimally allocate different numbers of DGs through the minimization of total active power losses and voltage deviation at power constraints of 0 – 2 MW and 0 – 3 MW respectively. The study proposed a PQ model of DG and Direct Load Flow (DLF) technique that uses Bus Incidence to Branch current (BIBC) and Branch Current to Bus Voltage (BCBV) matrices. The result obtained a minimum base case voltage level of 0.9898 p.u at bus 18 with variations of voltage improvements at other buses after single and multiple DG allocations in the system. Besides, the total power loss before DG allocation is observed as 0.2243 MW, and total power loss after DG allocation was determined based on the power constraints. Various optimal locations were seen depending on the power limits of different DG sizes. The results have shown that the impact of optimal allocation and sizing of three DG is more advantageous concerning voltage improvement, reduction of the voltage deviation and also total power loss in the distribution system. The results obtained in the 0 – 2 MW power limit is consistent to the 0 – 3 MW power limits regarding the influence of allocating DG to the network and minimization of total power losses.

scholarly journals Impacts of Photovoltaic Distributed Generation Location and Size on Distribution Power System Network

2018 ◽  
Vol 9 (2) ◽  
pp. 905 ◽  
Author(s):  
N. Md. Saad ◽  
M. Z. Sujod ◽  
Lee Hui Ming ◽  
M. F. Abas ◽  
M. S. Jadin ◽  
...  
Keyword(s):  
Power Systems ◽  
Distributed Generation ◽  
Distribution System ◽  
Short Circuit ◽  
Rapid Development ◽  
Reducing Power ◽  
Load Flow ◽  
Voltage Profile ◽  
Power Losses ◽  
Distribution Grid

As the rapid development of photovoltaic (PV) technology in recent years with the growth of electricity demand, integration of photovoltaic distributed generation (PVDG) to the distribution system is emerging to fulfil the demand. There are benefits and drawbacks to the distribution system due to the penetration of PVDG. This paper discussed and investigated the impacts of PVDG location and size on distribution power systems. The medium voltage distribution network is connected to the grid with the load being supplied by PVDG. Load flow and short circuit calculation are analyzed by using DigSILENT Power Factory Software. Comparisons have been made between the typical distribution system and the distribution system with the penetration of PVDG. Impacts in which PVDG location and size integrates with distribution system are investigated with the results given from the load flow and short circuit analysis. The results indicate positive impacts on the system interconnected with PVDG such as improving voltage profile, reducing power losses, releasing transmission and distribution grid capacity. It also shows that optimal locations and sizes of DGs are needed to minimize the system’s power losses. On the other hand, it shows that PVDG interconnection to the system can cause reverse power flow at improper DG size and location and increases short circuit level.

scholarly journals Improved Genetic Algorithm for Distribution System Performance Analysis by Taking Advantage of Essential Spanning Trees

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Yanzhu Ji ◽  
Zhuoqun Shi ◽  
Robert M. O’Connell
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Spanning Trees ◽  
Distribution Automation ◽  
Initial Population ◽  
Improved Genetic Algorithm ◽  
Small Test ◽  
Distribution System Reconfiguration ◽  
System Configurations ◽  
Automation Tools

Growing interest in the smart grid, increasing use of distributed generation, and classical distribution system reconfiguration (DSR) and restoration problems have led to the search for efficient distribution automation tools. One such tool, the improved Fast Nondominated Sorting Genetic Algorithm (FNSGA), not only is effective in finding system configurations that are optimal with respect to voltages, currents, and losses, but also considered parametric study to determine minimum values of N and Gen. In this paper, the essential spanning tree concept is expanded to improve the computational efficiency of the algorithm. Results of the study show that for relatively small test systems, optimum system configurations are obtained using values of N and Gen that require very small CPU times. In larger systems, optimum values of N and Gen requiring reasonable CPU times can also be found, provided that certain carefully chosen branches are removed from the pool of possibilities when producing the initial population in the algorithm. By using essential trees, the efficiency of the calculation is improved.

scholarly journals Penetration effects of various kinds of distributed generation systems on the distribution system

2019 ◽  
Vol 8 (9) ◽  
pp. 596-600
Keyword(s):  
Distributed Generation ◽  
Radial Distribution ◽  
Distribution System ◽  
Reactive Power ◽  
Load Flow ◽  
Voltage Profile ◽  
Power Losses ◽  
Generation System ◽  
Radial Distribution System ◽  
Real Power

Distributed generation system penetration in the existing distribution system is done for minimizing the losses and improving the voltage profile. There are total five types of distributed generation systems exist based on their power delivery like distributed generation system injecting real and reactive power, supplying real power only, supplying reactive power only, absorbing reactive power only , supplying real power and absorbing reactive power. All these five types of distributed generation systems have different penetration effects on the radial distribution system. We get different voltage profiles and power losses for different types of distributed generation systems. The testing of these five types of distributed generation systems will be done on IEEE 33 bus radial distribution system. For computing, the line parameters and power losses of the above testing system the forward-backward sweep load flow method will be applied

scholarly journals Optimal Conductor Selection in Radial Distribution Systems for Productivity Improvement Using Genetic Algorithm

2013 ◽  
Vol 9 (1) ◽  
pp. 29-35 ◽  
Author(s):  
Mahdi Legha ◽  
Hassan Javaheri ◽  
Mohammad Legha
Keyword(s):  
Genetic Algorithm ◽  
Radial Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Flow Analysis ◽  
Voltage Regulation ◽  
Load Flow ◽  
Solution Technique ◽  
Productivity Improvement ◽  
Load Flow Analysis

Development of distribution systems result in higher system losses and poor voltage regulation. Consequently, an efficient and effective distribution system has become more urgent and important. Hence proper selection of conductors in the distribution system is important as it determines the current density and the resistance of the line. This paper examines the use of different evolutionary algorithms, genetic algorithm (GA), to optimal branch conductor selection in planning radial distribution systems with the objective to minimize the overall cost of annual energy losses and depreciation on the cost of conductors and reliability in order to improve productivity. Furthermore, The Backward-Forward sweep iterative method was adopted to solve the radial load flow analysis. Simulations are carried out on 69-bus radial distribution network using GA approach in order to show the accuracy as well as the efficiency of the proposed solution technique.

scholarly journals A Modification of Newton–Raphson Power Flow for Using in LV Distribution System

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7600
Author(s):  
Anuwat Chanhome ◽  
Surachai Chaitusaney
Keyword(s):  
Distribution System ◽  
Power Flow ◽  
Quadratic Convergence ◽  
Low Voltage ◽  
Load Flow ◽  
Voltage Distribution ◽  
Convergence Properties ◽  
Branch Model ◽  
Power Injection ◽  
Newton Raphson

The Newton–Raphson (NR) method is still frequently applied for computing load flow (LF) due to its precision and quadratic convergence properties. To compute LF in a low voltage distribution system (LVDS) with unbalanced topologies, each branch model in the LVDS can be simplified by defining the neutral and ground voltages as zero and then using Kron’s reduction to transform into a 3 × 3 branch matrix, but this decreases accuracy. Therefore, this paper proposes a modified branch model that is also reduced into a 3 × 3 matrix but is derived from the impedances of the phase-A, -B, -C, neutral, and ground conductors together with the grounding resistances, thereby increasing the accuracy. Moreover, this paper proposes improved LF equations for unbalanced LVDS with both PQ and PV nodes. The improved LF equations are based on the polar-form power injection approach. The simulation results show the effectiveness of the modified branch model and the improved LF equations.

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