Decrease Power Loss Research Articles

A hybrid optimization for distributed generation and D-STATCOM placement in radial distribution network: a multi-faceted evaluation

The deregulation of the power system, upward growth in electrical energy demand and network expansion have resulted in an increasing integration of distributed generation (DG) and distribution static synchronous compensator (D-STATCOM) into radial distribution systems (RDS). Nonetheless, the optimal allocation of these devices is highly important to derive immense benefits. This investigation narrows down on optimizing DG and D-STATCOM placement in IEEE 33-bus RDS with a view to increase bus voltages, decrease power losses as well as maximize economic gains. The study undertakes a comprehensive analysis comparing the technical, economic and environmental performance of DG and D-STATCOM; thereby enabling power engineers to make informed choices concerning which device will be most advantageous when it comes to delivering power in RDS. A fuzzy enhanced firefly optimization (FEFO) approach is proposed for the optimization and a multifaceted evaluation in terms of technical, financial and environmental is presented for effective decision-making on distributed energy resource deployment. D-STATCOM and wind DG integrations led to notable reductions in power loss and pollutant emissions, highlighting their effectiveness in improving power quality and reducing reliance on fossil fuels. While wind DG incurred a higher installation cost ($3,100,749.2) compared to D-STATCOM ($90,566.6), it achieved greater yearly power loss cost savings ($69,198 versus $47,619). FEFO’s efficiency in optimization stands out, aiding engineers in making informed decisions for optimizing D-STATCOM and wind-DG integration in the IEEE-33 RDS, ultimately enhancing system performance and cost-effectiveness through proactive planning. The integration of D-STATCOM and wind DG led to a significant improvement in distribution system efficiency, with D-STATCOM reducing real power loss by 28.7% and reactive power loss by 27.8%, while wind DG achieved greater reductions of 41.8% in real power loss and 37.5% in reactive power loss, alongside reductions in pollutant emissions of 1.5% and 2.2%, respectively.

Load Balancing in Distribution Networks based on SSA Optimized Algorithm

The low voltage power distribution networks are three-phase networks where most of the clients are supplied from a different single phase with different load behavior. This way of supply causes several problems that imply the unbalance in the voltage percentage (UV %) in the three phases, and unbalanced increase in the neutral currents and power loss limits. One of the mitigation techniques for such problems is through swamping customers between phases and applying much simpler and more reliable smart systems to resolve the balancing problems. The introduction of an automated method based on a re-phasing technique for swamping customers between phases solves the balancing problem directly and effectively. The Salp Swarm Algorithm (SSA) with a set of constraints and limitations in the objective function to ensure the lower number of switching processes was proposed in this paper. It is found that phase balancing using SSA is considered an effective and direct method to decrease power losses, minimizing the problem of voltage or current unbalance, and enhance the system stability and efficiency of the power system. This technique was examined on 19 different low-voltage customers. A comparison between the neutral current before and after the treatments shows that it has been reduced from about 24 A to 1.15 A. The power loss was also reduced from 1.8 to 1.2 kW respectively and finally, UV % was reduced from 11-15% to about 1.2%.

Τhe effect of Ni on the magnetic properties of power or high permeability MnZn ferrites

In this article an extensive study is presented on the Ni addition in three subcategories of MnZn ferrites under conditions of constant Mn/Zn ratio and Fe excess, namely i) low frequency (∼100 kHz) power ferrites, ii) medium frequency (∼500 kHz) power ferrites and iii) high permeability (μi ∼ 8000, 25 °C) ferrites. As found, Ni is a useful additive for optimizing the high temperature performance of MnZn ferrites since it increases Curie temperature, saturation flux density, magnetic permeability and decreases power losses at temperatures above 100 °C. In addition, the addition of Ni increases the resonance frequency and the frequency stability of the initial permeability and partly counteracts the ageing effects caused by Co, when it is present in medium frequency ferrites. The magnetic results are explained on the basis of Ni-substitutions on octahedral sites associated with a negative contribution to the total magnetocrystalline anisotropy, thereby shifting the temperature at which the magnetocrystalline anisotropy constant K1 changes sign, to higher temperatures. The morphological results are explained assuming that the presence of Ni is associated with decreased cation vacancy and increased anion vacancy concentrations.

A novel field plate with arcuate end for improving GaN HEMTs

AbstractA new field plate (FP) is proposed for gallium nitride high‐electron‐mobility transistors (HEMTs). It features an innovative arcuate end (AE), which allows the induced charges that originally gathered at the FP end to diffuse over a wider area. Hence, not only is the electric field in the channel at the gate edge alleviated due to the induced charges, but also that concentrated at the FP end is reduced by means of AE. The simulation results indicate that by upgrading a source FP with AE, HEMT gains a 99% increase in breakdown voltage while remaining unaltered in specific on‐resistance. It also gets a 43.41% decrease in power loss during one cycle while maintaining the same breakdown voltage, which greatly contributes to enhance the efficiency of power electronic circuits.

Optimizing virtual power plant allocation for enhanced resilience in smart microgrids under severe fault conditions using the hunting prey optimization algorithm

The rapid expansion of renewable energy sources (RESs), such as photovoltaic (PV), wind turbine (WT), micro turbine (MT), and fuel cell (FC), has presented both opportunities and challenges to power systems, particularly in terms of environmental sustainability and economic feasibility. While RESs offer benefits like reduced environmental pollution, decreased power losses, and enhanced power quality, their intermittent nature and uncertainties pose challenges, resulting in variable generation and instability in distribution systems. To address these challenges, the concept of aggregating distributed energy resources (DERs), battery energy storage system (BESS), electric vehicles (EVs), and controllable loads into a virtual power plant (VPP) managed by an energy management system (EMS) has emerged. This study aims to determine the optimal location and size of VPPs within radial distribution system (RDS) while considering network resilience to severe weather events. The problem is formulated as an optimization task with dual objectives: minimizing the operating cost of VPPs and reducing energy not supplied (ENS) during natural disasters such as floods and earthquakes. To address this optimization problem, a novel meta-heuristic optimization algorithm called the hunting prey optimization algorithm (HPOA) is applied. HPOA serves various functions within the RDS, specifically targeting the optimization of VPP location, VPP resource management, and the objective functions. A case study is conducted, incorporating RESs, BESS, and EVs, and compared against existing algorithms such as BESA and SMA using a standard IEEE 85-bus RDS. Simulation results conducted in MATLAB demonstrate that the proposed HPOA algorithm effectively determines the optimal size and location of VPPs, leading to improved economic, operational, and resilience indices in the network.

Optimal allocation of distributed generation in meshed power networks: A metaheuristic approach

AbstractThis paper introduces a novel metaheuristic technique, a COOT‐based algorithm, to determine the optimal Distributed Generation (DG) allocation within a loop‐configured network. This method significantly narrows the optimization gap by leveraging a COOT‐based algorithm, ensuring accelerated convergence and resultant global optima. The core incentive for employing this technique is to substantially mitigate power loss, curtail voltage deviation, and bolster system stability in a loop distribution network. To attain optimal outcomes, the elaborated COOT and improved grey wolf optimization improved grey wolf optimization (IGWO) algorithms were executed on IEEE bus‐33 and 69 mesh distribution networks (MDNs) under varying power factors. The derived mathematical results effectively underscore accomplishing the stipulated objectives: a marked reduction in voltage deviation and power loss coupled with an augmentation in system stability. Notably, at unity, incorporating DGs resulted in a paramount reduction in power loss, attaining a decrease of 78% and 85% for bus‐33 and 69 MDNs, respectively. Moreover, an impressive decrease in power loss by 94% and 98% was observed at the optimal power factor for both MDNs. A comparative evaluation of the results accentuates that the proposed COOT and IGWO algorithms eclipse other documented research in performance, showcasing superior efficiency on a techno‐economic basis.

Performance Investigation on PMSG based Fractional Frequency Transmission Systems via XLPE cables for Offshore Wind Power

Presently, the research on Fractional Frequency Transmission System (FFTS) is fastened for the megawatt Offshore Wind Farms (OWF). FFTS has an ability to overcome the problem of charging current presented in the HVAC transmission and will effectively serve as an alternative to the traditional transmission systems. The basic structures and characteristics of a typical PMSG-based FFTS via XLPE cable for offshore wind power system is proposed and described first. Then the technical performance of power transmission through XLPE cable is evaluated by comparing the different cables such as flat and trefoil formation. Simulation results showcase notable enhancements in power transfer capacity, decreased power losses, and improved performance of control schemes. The feasibility studies describe the performance of FFTS (16.67 Hz) via trefoil cable is superior than FFTS flat formation cable transmission.

Optimizing PV Sources and Shunt Capacitors for Energy Efficiency Improvement in Distribution Systems Using Subtraction-Average Algorithm

This work presents an optimal methodology based on an augmented, improved, subtraction-average-based technique (ASABT) which is developed to minimize the energy-dissipated losses that occur during electrical power supply. It includes a way of collaborative learning that utilizes the most effective response with the goal of improving the ability to search. Two different scenarios are investigated. First, the suggested ASABT is used considering the shunt capacitors only to minimize the power losses. Second, simultaneous placement and sizing of both PV units and capacitors are handled. Applications of the suggested ASAB methodology are performed on two distribution systems. First, a practical Egyptian distribution system is considered. The results of the simulation show that the suggested ASABT has a significant 56.4% decrease in power losses over the original scenario using the capacitors only. By incorporating PV units in addition to the capacitors, the energy losses are reduced from 26,227.31 to 10,554 kW/day with a high reduction of 59.75% and 4.26% compared to the initial case and the SABT alone, respectively. Also, the emissions produced from the substation are greatly reduced from 110,823.88 kgCO2 to 79,189 kgCO2, with a reduction of 28.54% compared to the initial case. Second, the standard IEEE 69-node system is added to the application. Comparable results indicate that ASABT significantly reduces power losses (5.61%) as compared to SABT and enhances the minimum voltage (2.38%) with a substantial reduction in energy losses (64.07%) compared to the initial case. For both investigated systems, the proposed ASABT outcomes are compared with the Coati optimization algorithm, the Osprey optimization algorithm (OOA), the dragonfly algorithm (DA), and SABT methods; the proposed ASABT shows superior outcomes, especially in the standard deviation of the obtained losses.

Simulasi Aliran Daya Pada Pembangkitan PLTBG 1 MW Di Laboratorium Teknik Listrik Dengan Koneksi PLN Penyulang RA.01 Rantau Prapat Menggunakan Software Electric Transient And Analysis Program (Etap) 12.6.0

PT Pangkatan Indonesia is an oil palm plantation company operating in Labuhanbatu Regency, North Sumatra Province, with a plantation area of 7,134.8 ha and has built a palm oil mill with an installed capacity of 40 tons / hour. Liquid waste from the plant has the potential to be an alternative source of raw materials for Biogas Power Plants (PLTBg) which is also a distributed generation (DG). The parameters to be studied in this study are the decrease in power losses and the voltage profile of the electrical power produced. The simulation process produces voltage under normal conditions, which only increases about 0.3% of the nominal voltage (complies with Ministerial Regulation No. 4 of 2009). In addition, the results of interconnection analysis at the 1 MW PLTBG show that the voltage at the ends before and after the connection has increased. Furthermore, the ratio of the total current before and after (load 75% - 95% ) is fixed (no change). The conclusion of the results of this study is, the greater the load, the greater the power produced.

New multi-injection commutation topology for circuit breakers of HVDC transmission lines

Power-sharing between countries has an essential effect on increasing the power system’s reliability and allowing a resilient energy market. High voltage direct current (HVDC) transmission systems are preferable for long-distance transmission to decrease power losses. However, HVDC transmission lines have many protection challenges including the differentiability between various types of HVDC circuit breakers (HVDC-CB). Although mechanical HVDC-CBs suffered from long response time, they superseded their solid-state counterparts in terms of price and power losses. In this paper, a multi-injection commutation system MICS-HVDC-CB is developed to provide economic and fast response HVDC-CB. The proposed breaker doesn’t add external elements to avoid any price increase but instead modifies the existing topology. The MICS consists of multiple L–C commutation circuits inserted sequentially following the receiving of the tripping signal. The proposed MICS-HVDC-CB was tested upon a real transmission line using ATP simulation software. The results emphasize that the developed MICS-HVDC-CB decreased the arcing time to 38.5% and 20% compared to passive and active DC-CBs. The impact of cooling power, arcing time constant, and fault resistance was also investigated. The results showed the effectiveness of the proposed MICS topology in reducing the arcing time while keeping a simple and economic breaker structure.

A pulser R&D for the HEPS booster bumper magnet

The High Energy Photon Source (HEPS) is a fourth generation photon source, including a storage ring, a booster ring and a Linac. Due to the small dynamic aperture of the storage ring, a novel on-axis swap-out injection scheme was chosen. Here, the 6GeV booster acts as an accumulating ring during that injection process. To extract 6 GeV beam from the booster before injection into the storage ring, four slow bumper magnets are applied to assist the extraction kicker to accomplish. The bumper pulse magnetic field waveform is a half-sine wave with 1ms pulse bottom width. Depending on the simulation and test, a classic LC resonance circuit topology with IGBT switching in series with fast recovery diodes is adopted. In addition, an energy recycle circuit and capacitor charging circuit are designed, to decrease power loss and reduce the influence on the output pulse current waveform during the capacitor re-charge process. A pulsed power supply prototype has been completed, and the testing results show that the bumper pulser can fully meet the all requirements of HEPS booster high energy extraction system.

Estimation of pulmonary vascular resistance for Glenn physiology.

Children with single ventricle heart disease typically require a series of three operations, (1) Norwood, (2) Glenn, and (3) Fontan, which ultimately results in complete separation of the pulmonary and systemic circuits to improve pulmonary/systemic circulation. In the last stage, the Fontan operation, the inferior vena cava (IVC) is connected to the pulmonary arteries (PAs), allowing the remainder of deoxygenated blood to passively flow to the pulmonary circuit. It is hypothesized that optimizing the Fontan anatomy would lead to decreased power loss and more balanced hepatic flow distribution. One approach to optimizing the geometry is to create a patient-specific digital twin to simulate various configurations of the Fontan conduit, which requires a computational model of the proximal PA anatomy and resistance, as well as the distal Pulmonary Vascular Resistance (PVR), at the Glenn stage. To that end, an optimization pipeline was developed using 3D computational fluid dynamics (CFD) and 0D lumped parameter (LP) simulations to iteratively refine the PVR of each lung by minimizing the simulated flow and pressure error relative to patients' cardiac magnetic resonance (CMR) and catheterization (CATH) data. While the PVR can also be estimated directly by computing the ratio of pressure gradients and flow from CATH and CMR data, the computational approach can separately identify the different components of PVR along the Glenn pathway, allowing for a more detailed depiction of the Glenn vasculature. Results indicate good correlation between the optimized PVR of the CFD and LP models (n = 16), with an intraclass correlation coefficient (ICC) of 0.998 (p = 0.976) and 0.991 (p = 0.943) for the left and right lung, respectively. Furthermore, compared to CMR flow and CATH pressure data, the optimized PVR estimates result in mean outlet flow and pressure errors of less than 5%. The optimized PVR estimates also agree well with the computed PVR estimates from CATH pressure and CMR flow for both lungs, yielding a mean difference of less than 4%.

OPTIMAL COORDINATED VOLTAGE CONTROL OF ELECTRICAL DISTRIBUTION NETWORKS IN THE PRESENCE OF DISTRIBUTED RENEWABLE ENERGY SOURCES

Recently, distributed generation (DG), as clean and renewable energy, has increased due to the global warming problems and depletion of fossil sources. Several DGs are installed near the end-user, with the feature that this will decrease power losses. However, without optimal control, many problems, such as voltage instability and power losses, may affect the performance and the good operation of the power system. This paper proposes an optimal coordinated voltage control (OCVC) method for the distribution networks with distributed generation sources. The method is based on a genetic algorithm (GA) approach in multi-core simulation with an open-source OpenDSS to obtain the optimal setting of voltage control devices adjusted remotely. This method takes into account time-varying load and generation based on day-ahead scheduling. To validate the performances of the proposed technique, simulations are performed in a distribution network test with DG integration.

CAVOA: A chaotic optimization algorithm for optimal power flow with facts devices and stochastic wind power generation

AbstractThe study proposes a modified version of African Vultures Optimization Algorithm (AVOA) to address the optimal power flow (OPF) issue. The developed optimizer is called Chaotic AVOA (CAVOA). Prior to applying CAVOA to the problem at hand, its accuracy is evaluated using 23 benchmark functions. The production powers of WTs that are interrupted are predicted using Weibull probability density functions (PDFs). Two additional costs, namely penalty cost and reserve cost, are incorporated into the goal function of the OPF. The simulation results of CAVOA are compared with those of the original AVOA to solve the OPF. The proposed OPF technique and its solution methodology are verified on the IEEE 30‐bus test system, taking into account the flexible alternating current transmission systems (FACTS) devices, which have several benefits such as reducing active power transmission loss, regulating power flow, and improving voltage stability/profile. The research's simulation results demonstrate that CAVOA is more effective in identifying the OPF's optimal solution by reducing the overall power cost and power losses. The results indicate that the CAVOA algorithm outperforms AVOA as a metaheuristic optimization algorithm due to its superior capability in addressing challenging OPF problems with a minimal convergence rate. For example, when comparing the two algorithms, CAVOA achieved a significant improvement. It successfully reduced the cost function by approximately 0.023% in Case I and 0.035% in Case II, while also decreasing power loss by 2.57% in Case II and 0.57% in Case I. Additionally, CAVOA exhibited a remarkable reduction of 5.36% in voltage deviation compared to AVOA in Case I. Furthermore, in Case III, CAVOA demonstrated a decrease of 0.64% in gross cost when compared to AVOA.

Comprehensive layout optimization of the transmission system in a deepwater wind farm cluster

Compared to nearshore wind farms, deepwater offshore wind farms have better wind resources and broader development space and will be the main trend of wind power development in the future. Due to the long distance from the shore, the investment and operation costs of the transmission system in a deepwater wind farm cluster are high and the electricity generated by the cluster is commonly transmitted by high-voltage direct current transmission technology to decrease power losses. For a given converter station, the comprehensive optimization of the layouts of the substations, AC export cables from the substation to the converter station, and cable arrays within each wind farm are complex and have not been well studied. This paper proposes a multi-level nested optimization strategy to minimize the total cost of the collection cables for a deepwater offshore wind farm cluster. The proposed method applies the Informed-RRT* method to optimize the layout of AC export cables while the cable arrays are arranged by Prim’s algorithm. During the optimization process, the gradient descent algorithm is used to optimize the positions of the substations, obtaining the transmission system scheme with the minimum cable investment. For a certain deepwater wind farm cluster, the total cable cost after optimization is reduced by 3.58%, which indicates the effectiveness of this method.

Exfoliation, hydroxylation and silanization of two-dimensional (2D) montmorillonites (MMTs) and evaluation of the effects on tire rubber properties

In this work, effects of two-dimensional (2D) montmorillonite (MMT) on physical/mechanical/dynamic properties and rolling resistance of a model tire rubber were assessed. To achieve proper performance of MMTs in rubber compound, the layered stacks were initially exfoliated using sonication in deionized water. Pure MMTs showed a great tendency to aggregation in rubber matrix due to their superhydrophilic nature, so they were functionalized using 5 M NaOH solution to create surface OH groups for subsequent modification. The functionalized MMTs were silane modified with vinyltrimethoxysilane (VTMS) at different concentrations, finally, vinyl groups caused hydrophobicity and increment of water contact angle (WCA) from 35° to 92° in comparison with pure MMTs. The performance of tire rubber blends (TRBs) containing the pure MMTs, exfoliated MMTs and silanized MMTs was compared to the pristine rubber. Silanization of MMT caused a 140.47 % increase in the crosslink density of TRB nanocomposite. The results showed that the optimum curing time of rubber decreased by 56 s compared to the pristine TRB. The modulus of 100 and 300 % increased by 103 and 20 % for sample that contained silane modified MMTs, respectively. The elongation at break decreased by 7 % for the modified nanocomposite compared to the pristine TRB. Also, the storage modulus and transition glass temperature of nanocomposite containing silanized MMTs increased by 54 % and 7 °C compared to the control TRB, respectively. The rolling resistance in the tire (i.e. C-s5-MMT1) demonstrates a prominent reduction of 19.42 %, accomplished with a 30.28 % decrease in power loss, 85.07 % Akron abrasion loss, and the lowest Heat-Build up, as compared with the pure tire (i.e. C-Ctrl).

Preliminary in-silico analysis of vascular graft implantation configuration and surface modification

Vascular grafts are used to reconstruct congenital cardiac anomalies, redirect flow, and offer vascular access. Donor tissue, synthetic, or more recently tissue-engineered vascular grafts each carry limitations spanning compatibility, availability, durability and cost. Synthetic and tissue-engineered grafts offer the advantage of design optimization using in-silico or in-vitro modeling techniques. We focus on an in-silico parametric study to evaluate implantation configuration alternatives and surface finishing impact of a novel silicon-lined vascular graft. The model consists of a synthetic 3D-generic model of a graft connecting the internal carotid artery to the jugular vein. The flow is assumed unsteady, incompressible, and blood is modeled as a non-Newtonian fluid. A comparison of detached eddy turbulence and laminar modeling to determine the required accuracy needed found mild differences mainly dictated by the roughness level. The conduit walls are modeled as non-compliant and fixed. The shunt configurations considered, are straight and curved with varied surface roughness. Following a grid convergence study, two shunt configurations are analyzed to better understand flow distribution, peak shear locations, stagnation regions and eddy formation. The curved shunt was found to have lower peak and mean wall-shear stress, while resulting in lower flow power system and decreased power loss across the graft. The curved smooth surface shunt shows lower peak and mean wall-shear stress and lower power loss when compared to the straight shunt.

Q-Learning Based Commercial Electric Vehicles Scheduling in a Renewable Energy Dominant Distribution Systems

The increasing prevalence of commercial electric vehicles (CEVs) for ferrying passengers has become popular in recent times. This scenario strains the distribution system (DS) during the system charging cycle. However, the design becomes beneficial if the CEVs support the utility based on the needs. This work aims to efficiently schedule the operational modes of CEVs to decrease power loss in the DS in the presence of distributed generation (DG). The CEVs are modeled by considering the uncertainty in their travel patterns. This work proposes a combined approach to reduce power loss and enhance voltage quality by adopting internet of Things (IoT) enabling technologies. This method combines Voltage Stability Index (VSI), Q-learning method, and enhanced moth flame optimization (EMFO) for efficient operation of DS. The DS considers IoT-enabled EV charging stations (EVCSs), DGs, and CEVs for 3-way communication. Various case studies are presented to show the efficacy of the proposed technique compared to existing methods in the literature.

A novel decentralized inverter control algorithm for loss minimization and LVRT improvement

Algorithms that adjust the reactive power injection of converter-connected RES to minimize losses may compromise the converters’ fault-ride-through capability. This can become crucial for the reliable operation of the distribution grids, as they could lose valuable resources to support grid voltage at the time they need them the most. This paper explores how two novel loss-minimizing algorithms can both achieve high reduction of the system losses during normal operation and remain connected to support the voltage during faults. The algorithms we propose are decentralized and model-free: they require no communication and no knowledge of the grid topology or the grid location of the converters. Using local information, they control the reactive power injection to minimize the system losses. In this paper, we extend these algorithms to ensure the low voltage ride through (LVRT) capability of the converters, and we integrate them with state-of-the-art Wavelet-CNN–LSTM RES forecasting methods that enhance their performance. We perform extensive simulations on the real-time digital simulation (RTDS) platform, where we demonstrate that the algorithms we propose can achieve a substantial decrease in power losses while remaining compliant with the grid codes for LVRT makes them suitable for the implementation across the distribution system.

Northern Goshawk Optimization Algorithm for Optimal Power Flow with FACTS Devices in Wind Power Integrated Electrical Networks

Power-operational problems must be resolved with flexible AC transmission systems (FACTS) and optimum power flow (OPF). The complexity of power flow analysis in modern power network models is increased by the unpredictability of renewable energy generating sources in addition to the challenge of determining the appropriate locations and ratings for FACTS devices. FACTS devices can increase the thermal capacity of power transmission lines, enabling the network to accommodate more electricity from renewable sources. The major goals of this study are to lower production costs, decrease power losses, enhance the voltage profile of the system, and enhance load capability. To solve a variety of optimization issues optimally, optimization meta-heuristics approaches have been created in response to the increased emphasis on renewable energy sources, such as wind power. Wind energy is an important component of modern power systems due to its affordability and clean nature. This article presents an OPF method for efficiently scheduling energy from wind farms using the Northern Goshawk Optimization (NGO) meta-heuristic technique. The Weibull probability distribution function is used to represent wind speed and estimate the cost of electricity produced by wind turbines based on the planned power. To validate the NGO approach and its results compared with those of other meta-heuristic optimization techniques, such as Chef-Based Optimization Algorithm, Dingo Optimization Algorithm, and Chameleon Swarm Algorithm, the IEEE system 30-bus is used to solve the OPF problem.