Application of DSAPSO Algorithm in Distribution Network Reconfiguration with Distributed Generation

With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms.Consequently,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima.To tackle this issue,a more advanced particle swarm optimization algorithm is proposed.To address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning factors.The Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization process.The inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search abilities.The incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the results.Simulation analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy resources.The findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the network.Furthermore,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply quality.Additionally,the algorithm exhibits a high level of generality and applicability.

Distributed Generators Location and Capacity Effect on Voltage Profile Improvement and Power Losses Reduction Using Genetic Algorithm

This paper presents a powerful approach to find the optimal size and location of distributed generation units in a distribution system using GA （Genetic Optimization algorithm）. It is proved that GA method is fast and easy tool to enable the planners to select accurate and the optimum size of generators to improve the system voltage profile in addition to reduce the active and reactive power loss. GA fitness function is introduced including the active power losses, reactive power losses and the cumulative voltage deviation variables with selecting weight of each variable. GA fitness function is subjected to voltage constraints, active and reactive power losses constraints and DG size constraint.

Optimization of the Placement and Size of Photovoltaic Source

This paper presents a new optimization study of the placement and size of a photovoltaic source(PVS)in a distribution grid,based on annual records of meteorological parameters(irradiance,temperature).Based on the recorded data,the production output as well as the daily average power(24-h vector)of the PVS is extracted over the year.When a power vector is available,it can be used as an input when searching for the optimal size of the PVS.This allows to take into account the constraint of the variation of the power generated by this source considering the variation of the power consumed by the electrical loads during the whole day.A multi-objective fitness function has been considered.The latter minimizes the active losses and maximizes the voltage stability index during the day,while considering the constraints of the system,that is,the security,technical,geographical,and meteorological constraints.This problem was solved using the Non-dominated Sorting Genetic Algorithm NSGA-II optimization technique under MATLAB 2021.It was applied to the distribution network of Ghardaïa of 59 nodes.

Optimal integration of DGs into radial distribution network in the presence of plug-in electric vehicles to minimize daily active power losses and to improve the voltage profile of the system using bioinspired optimization algorithms

Purpose:The increase in plug-in electric vehicles(PEVs)is likely to see a noteworthy impact on the distribution system due to high electric power consumption during charging and uncertainty in charging behavior.To address this problem,the present work mainly focuses on optimal integration of distributed generators(DG)into radial distribution systems in the presence of PEV loads with their charging behavior under daily load pattern including load models by considering the daily(24 h)power loss and voltage improvement of the system as objectives for better system performance.Design/methodology/approach:To achieve the desired outcomes,an efficient weighted factor multi-objective function is modeled.Particle Swarm Optimization(PSO)and Butterfly Optimization(BO)algorithms are selected and implemented to minimize the objectives of the system.A repetitive backward-forward sweep-based load flow has been introduced to calculate the daily power loss and bus voltages of the radial distribution system.The simulations are carried out using MATLAB software.Findings:The simulation outcomes reveal that the proposed approach definitely improved the system performance in all aspects.Among PSO and BO,BO is comparatively successful in achieving the desired objectives.Originality/value:The main contribution of this paper is the formulation of the multi-objective function that can address daily active power loss and voltage deviation under 24-h load pattern including grouping of residential,industrial and commercial loads.Introduction of repetitive backward-forward sweep-based load flow and the modeling of PEV load with two different charging scenarios.

Dielectric Properties of Bi_4Ti_3O_(12) Ceramics by Impedance Spectroscopic Method

Various lead-free ceramics have been investigated in search for new high-temperature dielectrics. In particular, Bi_4Ti_3O_（12） is a type of ferroelectric ceramics, which is supposed to replace leadcontaining ceramics for its outstanding dielectric properties in the near future. Ferroelectric ceramics of Bi_4Ti_3O_（12） made by conventional mixed oxide route have been studied by impedance spectroscopy in a wide range of temperature. X-ray diffraction patterns show that Bi_4Ti_3O_（12） ceramics are a single-phase of ferroelectric Bi-layered perovskite structure whether it is calcined at 800 ℃ or after sintering production. This study focused on the effect of the grain size on the electric properties of BIT ceramics. The BIT ceramics with different grain sizes were prepared at different sintering temperatures. Grain becomes coarser with the sintering temperature increasing by 50 ℃, relative permittivity and dielectric loss also change a lot. When sintered at 1 100 ℃, r values peak can reach 205.40 at a frequency of 100 k Hz, the minimum dielectric losses of four different frequencies make no difference, all close to 0.027. The values of Ea range from 0.52 to 0.68 e V. The dielectric properties of the sample sintered at 1 100 ℃ are relatively better than those of the other samples by analyzing the relationship of the grain, the internal stresses, the homogeneity and the dielectric properties. SEM can better explain the results of the dielectric spectrum at different sintering temperatures. The results show that Bi_4Ti_3O_（12） ceramics are a kind of dielectrics. Thus, Bi_4Ti_3O_（12） can be used in high-temperature capacitors and microwave ceramics.

Rapid determination of lithium-ion battery degradation: High C-rate LAM and calculated limiting LLI

Herein,incremental capacity-differential voltage (IC-DV) at a high C-rate (HC) is used as a non-invasive diagnostic tool in lithium-ion batteries,which inevitably exhibit capacity fading caused by multiple mechanisms during charge/discharge cycling.Because battery degradation modes are complex,the simple output of capacity fading does not yield any useful data in that respect.Although IC and DV curves obtained under restricted conditions (<0.1C,25℃) were applied in non-invasive analysis for accurate observation of degradation symptoms,a facile,rapid diagnostic approach without intricate,complex calculations is critical in on-board applications.Herein,Li Ni_(0.5)Mn_(0.3)Co_(0.2)O_(2)(NMC532)/graphite pouch cells were cycled at 4 and 6C and the degradation characteristics,i.e.,loss of active materials (LAM) and loss of lithium inventory (LLI),were parameterized using the IC-DV curves.During the incremental current cycling,the initial steep LAM and LLI slopes underwent gradual transitions to gentle states and revealed the gap between low-and high-current measurements.A quantitative comparison of LAM at high and low C-rate showed that a IC;revealed the relative amount of available reaction region limited by cell polarization.However,this did not provide a direct relationship for estimating the LAM at a low C-rate.Conversely,the limiting LLI,which is calculated at a C-rate approaching 0,was obtained by extrapolating the LLI through more than two points measured at high C-rate,and therefore,the LLI at 0.1C was accurately determined using rapid cycling.

The analysis of distributed photovoltaic access system schemes

As the share of photovoltaic power generation in power system has increased year by year, the optimization choice of access system schemes become one of the first and most important problems in grid before admitting photovoltaic power generation. Therefore, this article takes a proposed distributed photovoltaic as an example to research and analyze two kinds of high density multiple access points distributed photovoltaic access system schemes. The emphasis is making a comprehensive comparison and selection among the aspect of active power loss and economic benefit, etc. In the premise of ensuring the normal power generation of the photovoltaic system, it puts forward the recommended scheme that can help to spontaneous self-consumption, elimination on the spot, effectively decrease network loss and economic benefit.

Impact of the penetration of distributed generation on optimal reactive power dispatch

Optimal reactive power dispatch(ORPD)is a complex and non-linear problem,and is one of the sub-problems of optimal power flow(OPF)in a power system.ORPD is formulated as a single-objective problem to minimize the active power loss in a transmission system.In this work,power from distributed generation(DG)is integrated into a conventional power system and the ORPD problem is solved to minimize transmission line power loss.It proves that the application of DG not only contributes to power loss minimization and improvement of system stability but also reduces energy consumption from the conventional sources.A recently proposed meta-heuristic algorithm known as the JAYA algorithm is applied to the standard IEEE 14,30,57 and 118 bus systems to solve the newly developed ORPD problem with the incorporation of DG.The simulation results prove the superiority of the JAYA algorithm over others.The respective optimal values of DG power that should be injected into the four IEEE test systems to obtain the minimum transmission line power losses are also provided.

Hybrid intelligence approach for multi-load level reactive power planning using VAR compensator in power transmission network

This paper formulates and solves a techno-economic planning problem of reactive power (VAR) in power transmission systems under loadings. The objective of the proposed research work is to minimize the combination of installation cost of reactive power sources, power losses and operational cost while satisfying technical constraints. Initially, the positions for the placement of reactive power sources are determined technically. Different cost components such as VAR generation cost, line charging cost etc. are then added in the total operating cost in a most economical way. Finally, the optimal parameter setting subjected to reactive power planning (RPP) is obtained by taking advantages of hybrid soft computing techniques. For the justification of the efficiency and efficacy of the proposed approach the entire work is simulated on two inter-regional transmission networks. To validate the robustness and ease of the soft computing techniques in RPP the responses of benchmark functions and statistical proof are provided simultaneously.

Optimal Site and Size of Distributed Generation Allocation in Radial Distribution Network Using Multi-objective Optimization

Distributed generation(DG)allocation in the distribution network is generally a multi-objective optimization problem.The maximum benefits of DG injection in the distribution system highly depend on the selection of an appropriate number of DGs and their capacity along with the best location.In this paper,the improved decomposition based evolutionary algorithm(I-DBEA)is used for the selection of optimal number,capacity and site of DG in order to minimize real power losses and voltage deviation,and to maximize the voltage stability index.The proposed I-DBEA technique has the ability to incorporate non-linear,nonconvex and mixed-integer variable problems and it is independent of local extrema trappings.In order to validate the effectiveness of the proposed technique,IEEE 33-bus,69-bus,and 119-bus standard radial distribution networks are considered.Furthermore,the choice of optimal number of DGs in the distribution system is also investigated.The simulation results of the proposed method are compared with the existing methods.The comparison shows that the proposed method has the ability to get the multi-objective optimization of different conflicting objective functions with global optimal values along with the smallest size of DG.

Simplified mathematical model of proton exchange membrane fuel cell based on horizon fuel cell stack

This paper presents a simplified zero-dimensional mathematical model for a self-humidifying proton exchange membrane(PEM)fuel cell stack of 1 k W.The model incorporates major electric and thermodynamic variables and parameters involved in the operation of the PEM fuel cell under different operational conditions.Influence of each of these parameters and variables upon the operation and the performance of the PEM fuel cell are investigated.The mathematical equations are modeled by using Matlab-Simulink tools in order to simulate the operation of the developed model with a commercial available 1kW horizon PEM fuel cell stack(H-1000),which is used for the purposes of model validation and tuning of the developed model.The model can be extrapolated to higher wattage fuel cells of similar arrangements.New equation is presented to determine the impact of using air to supply the PEM fuel cell instead of pure oxygen upon the concentration losses and the output voltage when useful current is drawn from it.