Developing a Hybrid Approach Based on Analytical and Metaheuristic Optimization Algorithms for the Optimization of Renewable DG Allocation Considering Various Types of Loads

The relationship of stress and strength gradients must be considered simultaneously in analysis of a particular type of fracture. This chapter discusses the principal elastic stress distribution in members of various shapes under different types of pure loads. A basic understanding of both the stress and strength gradients of metal parts with and without stress concentrations and under different types of loading is provided. The chapter also describes the effect of service conditions on applied stresses.

Distribution system is the crucial part of the power system which needs to be monitored for quality since it is the last stage in delivering electricity to consumers. The main aim of suppliers is therefore to maintain excellent quality of supply with minimal support at the network level. This includes dealing with issues around voltage regulation and minimization of real power losses on the network which are reflected in a uniform voltage profile through various load points on the feeders. However, with increase in decentralization, Distributed Generation (DG) becomes the focal point of distribution networks and can be used to achieve the above mentioned objectives. DGs are used in this paper to minimize the losses along with an improvement in the voltage profile. The location of these DG units on the network is addressed as an optimization problem using the loss sensitivity index and voltage deviation index. The size of power injected by DG units is obtained with using an intelligent approach that combines Genetic Algorithm (GA) with neural networks. Different cases of DG in terms of real and reactive power injected are considered resulting in an improvement in voltage profile. The loss sensitivity and voltage deviation indices show the best result for the location of DG needed to minimize the power loss along with improvement in voltage regulation. This approach is tested on a 13-bus distribution network with different types of loads placed throughout the feeder.

This paper presents a simple analytical method for obtaining optimal sizing of Distributed Generator (DG) units considering reduction of power loss and improvement of voltage profile in distribution system. Sensitivity analysis is used to find out the best location of DG placement. The optimum power penetration by DGs operating at unity power factor and lagging power factor is carried out using analytical method for constant power (CP), constant current (CI), constant impedance (CZ) and composite (CPIZ) loads. Effectiveness of the proposed method is demonstrated through an example.

Performance evaluation of isolated three-phase voltage source inverter with LC filter adopting different MPC methods under various types of load

This paper evaluates the fatigue strength of ultrafine-grained (UFG) Grade 4 Ti in the low-cycle fatigue region, as well as the strength of medical implants (plates and screws) made of UFG Ti under various types of loading in comparison with the strength of products made of coarse-grained (CG) Ti. To produce a UFG state, titanium billets after annealing were processed by the ECAP-Conform technique. The fatigue of the prismatic specimens with a thickness of 10 mm from CG and UFG Ti was tested by the three-point bending method using an Instron 8802 facility. The modeling and evaluation of the stress-strain state in the ANSYS software package for finite-element analysis revealed, in particular, the localization of equivalent stresses in the area of hole edges and at fillets during the tension of the plates. The performed research has demonstrated that medical implants (plates and screws) from UFG Grade 4 Ti have a higher strength under different types of loading (tension, fatigue strength, torsion) in comparison with products from CG Ti. This opens up a possibility for the miniaturization of medical products from UFG Ti while preserving their main performance properties at an acceptable level.

This paper shows the variation of different power system parameters for a grid-tied Distributed Generation system during the situation of islanding under different types of load conditions. Parameters that have been taken into account here are RMS voltage, RMS current, Active Power, Reactive Power, Apparent Power, Impedance and Frequency at the Point of Common Coupling (PCC). A fundamental assumption considered here is that the load remains fixed for all the load cases discussed in the result section. The simulation results show the variations in the above parameters for different values and types of loads when islanding occurs in the grid-tied DG power system.

This article presents a hybrid method based on analytical and metaheuristic optimization techniques for the optimal placement of distributed generations (DGs) and shunt capacitors (SCs) into radial distribution systems (RDSs) to minimize power loss. In the hybrid method, a meta-heuristic called the Salp Swarm Algorithm is utilized to determine the optimal locations of DGs and SCs, while an efficient analytical technique is applied to calculate the optimal sizes. To check the robustness of the proposed method, two standard IEEE systems are employed; IEEE 33-bus and 69-bus, and compared with existing optimization techniques. Also to confirm the ability of the proposed method on improving performance, it applied to an actual 94-bus Portuguese RDS. The obtained results show the feasibility of the proposed method in optimal allocating of the DG and SC into RDS.

Identification of combined power quality disturbances in the modern power systems by considering the development of different types of loads and distribution generations has become increasingly important. The novelty of this paper comes from the accurate and fast identification of the combined power quality disturbances in the presence of different distributed generations and loads such as photovoltaic cell, wind turbine with doubly fed induction generators, diesel engines, electric arc furnace, DC machine, 6-pulse and 12-pulse rectifier loads. In this paper, the features are extracted using variational mode decomposition, just from voltage waveforms. To reduce the redundant data, dimension of features vector, and time, the Relief-F method and correlation feature selection method are applied on the extracted features and these two methods are compared together. In this paper, the K-nearest neighbors classifier is used to classify the multiple power quality disturbances. To verify the effectiveness of the proposed method, different scenarios such as misfiring, variation of sun radiation and wind speed, entrance and exit of loads, capacitors and distributed generators, different fault at the grid in half-load to full-load were simulated. This method can be used as an added algorithm for smart metering in modern and smart power systems.

With the increase in the scale of demand side management (DSM) activities, the load characteristic of power system at the load reduction and recovery times will experience significant changes due to DSM actions and hence affect the dynamic performance of power systems. This paper proposes a methodology to assess the effect of DSM actions on power system network performance — small signal stability of transmission network. A case study of shifting of different type of load from one hour to the other is tested and investigated to what extent the impact of these DSM activities can have on grid performance. A generic 295 bus distribution network and the IEEE standard 9-bus transmission network are used to demonstrate this effect. In the proposed methodology, different types of load sectors (domestic, commercial, industrial) with corresponding mix of load categories (small and large induction motors, constant power, constant impedance and constant current load) in each of them are modelled in DigSILENT/PowerFactory based on typical structure and composition of demand in distribution network. The paper demonstrates and quantifies the impact of the DSM actions on transmission network performance and establish the extent to which DSM can contribute, or otherwise, to power system stability. It will pave the way to development of optimal DSM that will ensure that not only total demand is managed but also the way how it should be managed in order not to endanger network performance in case of disturbances.

Several extreme weather disasters have demonstrated that grid resilience is a significant aspect of modern power systems to work upon. In event of grid failure, back up power sources must support the network. Thus, optimal planning of distributed generations (DGs) in power distribution networks need to be done so that in addition to grid power support, ancilliary services such as minimized real power losses and voltage deviations are attained. In the present work, combined resilience evaluation and analytic operational enhancement strategy has been studied in a radial power distribution network. To achieve overall minimal power losses and better voltage control, the Marine Predator (MPA) meta-heuristic optimization technique is adopted. The MPA is utilised to discover the best DG location and size at the same time. The proposed method is applicable to both single and multiple DG unit sizing and siting. Furthermore, to calculate the best size of DG unit, the suggested method just requires the results of the base case load flow. The proposed approach is tested on a IEEE 33-bus radial distribution test system.

Fatigue studies of CoCrFeMnNi high entropy alloy films using nanoindentation dynamic mechanical analyses

In spite of availability of natural sources, still people are now sitting on the dark zone. Because of the remote area, the grid networking system is very weak. As a result of which power stability may not be assured, which greatly effects to the day-today activities of the people in the reason. Fortunately, technology exist that can give the assurance of quality of electricity in an isolated area which is for away from the regular power network. The preset scenario is the coexistence of both AC and DC micro grids, because of the evolutions of different types of loads. The hybrid microgrid concept assume a cluster of different types of loads and distributed generatoroperating as a controllable system which maintain the quality of power and its stability to its local area. To make the world pollution free environment, renewable energy infrastructure is increasing particularly in the distribution network. It has the advantage that the power generated through distributed generation system is utilized in the grid for other users. The PV cell generates voltage at the distribution level. At the end of distribution line a 1 MVA three phase load is connected. In the absence of the generation from the PV cells, the voltages and currents at various lengths of the line are calculated with a single load of three phase 1 MVA. With the inclusion of PV cells, the improvement in voltage dip is also estimated. This estimate provides the power supplied by the PV cell and improvement in voltages. In order to determine the effect of additional load on voltage profile, a three phase load of 1 MVA was connected to intermediate point in the transmission system. This causes the dip in voltage at various nodes of the distribution line. Several combinations of source and loads have been examined to determine the effect on voltage and power. The above work has been carried out using Electro Magnetic Transient Program (EMTP) Software. In order to simulate the system, 8.98 kV, 5 km long line is divided into 5 sections of 1 km each. The sections are represented in the form of Pi-network by its series inductance, resistance and capacitance to ground. Loads are represented by R and L of appropriate magnitude and through EMTP program the calculations are done. The PV cell is represented by a source stepped up to 8.98 kV system. Both single phase and three phase lines have been examined through the above program. The results obtained for various conditions are presented in the paper.

This paper presents an application of deadbeat control theory in control of the DC/AC single-phase voltage source PWM inverter (VSI PWM). The main object of the article is to ensure a high quality of the inverter output voltage under different types of load (linear and nonlinear). One of the main criteria of the quality of the output voltage is total harmonic distortion (THD). It should be kept as small as possible. This article describes a detailed modelling of the plant and controller design. A novel multi-loop control technique based on deadbeat theory is proposed in order to achieve sinusoidal output voltage. The proposed control scheme consists of current and voltage loop. Theoretical analysis, simulation and practical results have been given to verify the proposed digital control scheme. Proposed control scheme was implemented into the TMS320F28335 DSC controller and tested on 1 kW PWM inverter.

Distribution System consist of different types of loads like linear and nonlinear load. Due to different types of loads, voltage unbalance and other power quality related issues will occur. To overcome this problem, a voltage source inverter based device called distribution static compensator can be used. In this work, an improved voltage controller for distributed static compensator, based on power balancing theory is presented. The improved controller uses only voltage sensors and this controller is developed by considering unbalanced load conditions. Proportional Integral controller is used for maintaining terminal voltage and DC link voltage. The controller is verified for different voltage disturbances such as sag and swell. MATLAB/SIMULINK package is used to verify the controller using simulation. The controller is also verified using Hardware in the loop simulation using DSPACE and results are presented for different voltage disturbances.

The efficiency of a load management system in terms of its energy performance index (EPI) depends on its capacity to enhance the reliability, resilience, and cost effectiveness of the existing system. Artificial intelligence (AI) is crucial in this shift from classical to AI-based power system planning, optimizing renewable energy (RE) and reducing gridstress. On the other hand, proper placement of resources is essential to achieve benefits and reduce transmission losses. Utility sectors of different states has revealed that in certain areas amongst different type of loads, domestic loads accounts for a substantial proportion of energy consumption. Therefore, the present work deals with optimum load scheduling, integration of RE, energy storage (ES) and proposed tri-optimized-tariff (TOT) for prosumers. We have found that the weighted-K-nearest-neighbor (KNN) method excels in selecting features for household appliances and ES scheduling. The composite greedy optimization (CGO) technique outperforms existing methods in optimization. These results demonstrate the efficiency and real-world potential of our model. We have conducted a case study and developed an AI-based strategic-residential-load-managementsystem (SRLMS), which we have tested on the IEEE33 bus system, showing cost effectiveness and improved EPI for prosumers. This work encourages the development of a harmonious relationship between utility-sectors and prosumers.