Power Loss Flow Research Articles

Optimal Power Flow and Performance Analysis of SPV Penetration to IEEE Bus System Using MI Power

The need to meet changing demand in an economical manner while making the best use of already-expensive electrical systems led to inescapable problems with overloading, increased power transfer coupled with extremely high system loss, and unstable voltage profiles that ultimately resulted in an unreliable system. Power distribution is impacted by the remarkable changes that are currently taking place in the use and provision of energy services. Numerous new avenues for the provision and use of electrical energy have been opened up as a result of developed and diverse distributed technologies, including distributed electricity generation. The emergence of powerful and affordable software has enabled us to cope with the fast-paced development in the power industry which requires updating resources with modern technologies to manage substations. The goal of the proposed work is to integrate solar photovoltaic and optimize the power flow, voltage profile, and real power loss through the building of a simulation model on Mi Power. Power flow analysis was used to calculate the actual power loss, which was then minimized through SPV placement. Additionally, the impact of PV penetration on single bus loading was assessed for all load buses operating in succession with either active, reactive, or combined active and reactive loads.

High penetration PV active distribution network power flow optimization and loss reduction based on flexible interconnection technology

High penetration PV active distribution network power flow optimization and loss reduction based on flexible interconnection technology

Impact study of flexible alternating current transmission system on power flow and power loss in power systems using MATLAB and PSAT

The work presented in this paper is to study the impact of FACTS (flexible alternating current transmission system) on the power flow and power losses of a multi-machine electrical system. In this work, we have calculated the power flow and the active and reactive power losses for a 6-bus 3-machine network system, in the first case where there are no FACTS, and in the second case where there are FACTS (SVC). So, and in the second case we used an SVC ((Static Var Compensator) because it is one of the elements of FACTS, to see their influence on power flow and power losses in electrical systems using MATLAB software (we used the Newton-Raphson method) and using PSAT software (Power System Analysis Toolbox), we calculated the power flow and the active and reactive power losses in the lines, respectively. Finally, we compare the results obtained by the simulation programs MATLAB and PSAT, and see what effect FACTS (SVC) has on the power flow and power loss in our electrical system that we are studying.

Techno-economic and environmental comparative analysis for DC microgrids in households: Portuguese and French household case study

This study revisits the use of the direct current (DC) distribution system concept in households to increase energy savings and potentially reduce costs and associated environmental impacts by comparing the impact of alternating current (AC) and DC distribution networks with today's trending appliances and highly efficient appliances. The study is based on environmental-economic modelling for various microgrid configurations with different DC load ratios and renewable energy capacities. An adaptive load profile based on initial assumptions is developed, the optimal distributed energy resource schedule is identified using DERCAM software, and the proper converters and system cabling are chosen. The converter's operation efficiency curve and dynamic consumption behaviours are examined for real-time sequential analysis for power flow loss. Two datasets from France and Portugal are used to explore the impact of different climate zones, socio-economic conditions and electricity prices on the configuration viability. The results show that DC solutions are efficient for large consumers in both countries, and current AC configurations are still cost-effective for medium consumers.

Simulation and Modeling of Detailed Load flow Analysis for the 400kVA and 132kVA Iraqi Grid

A load flow program is developed using MATLAB and based on the Newton–Raphson method,which shows very fast and efficient rate of convergence as well as computationally the proposed method is very efficient and it requires less computer memory through the use of sparsing method and other methods in programming to accelerate the run speed to be near the real time. The designed program computes the voltage magnitudes and phase angles at each bus of the network under steady–state operating conditions. It also computes the power flow and power losses for all equipment, including transformers and transmission lines taking into consideration the effects of off–nominal, tap and phase shift transformers, generators, shunt capacitors, shunt inductors, line reactors and bus reactors. Thus, overloaded transformers and transmission lines are identified, and remedial measure can be designed and implemented. It also provides the ability of tie lines, area splitting, and contingency analysis.Any generator station(s) or busbar(s) that exceeds the specified operation limits will be automatically checked and flagged and then the program will automatically suggest the best solution to the problem. It also automatically checks whether the system is sub divided into sub areas or not. If yes, it will find the solution for each area separately. A complete report about the results and the state of the system (the violated generators, busbars, and transmission lines, the required modifications to overcome the violations, the names of the areas splitted,…) will be displayed in working window as well as generating a text file containing all details . It is important to mention that this program is used by the national control center of the Ministry of Electricity and its efficiency was tested through applying the data of the two major Iraqi networks (400kV and 132kV), the program shows very accurate results and provides efficient notes about the status of the networks

Power Flow Analysis of Electrical Network Systems Using Gauss-Seidel Method and Python

This study aims to analyze the power flow in a 150kV radial power system on the island of Bali, the reason the author uses the Bali island system is because the number of busbars in the system is not too many and the data on the system is known. The problem of this research is limited by determining the voltage, power flow, and power losses in the system. The method used in this study is the Gauss-Seidel method through simulation with the help of Visual Studio Code software and the Python 3.9.2 program. The simulation is carried out by producing a total of 8 iterations. The simulation is carried out to find the parameters of the load voltage, apparent power on the slack bus, current, power flow and power losses on the line. The simulation results show that, under a load condition of 70% of the load transformer capacity, the voltage at the load bus node experiences a voltage drop, reaching 4.48% at bus 10. So when the system operates for generation conditions, the power that can be generated is 1,275.6 MegaWatt of the total generator installed, and the power delivered to each bus node is 2,090 MVa and the power losses in the system are 3.69% of the total power distributed to the bus nodes

A chaotic equilibrium optimization for temperature-dependent optimal power flow

ABSTRACT Optimal power flow (OPF) is one of the common problems in power systems. In general, the branch resistance of the system is assumed to be constant with respect to temperature variation in conventional optimal power flow. However, the temperature correlation of the branch resistance should be taken into account to enhance the accurate calculation of the power flow and branch losses. This paper suggests a new and efficient method, which is chaotic equilibrium optimization (CEO) to deal with the temperature-dependent optimal power flow (TDOPF) problem. The CEO is validated on IEEE 30-bus and 118-bus networks with different objective functions, including generating fuel cost, total active power losses, voltage profile enhancement, voltage stability improvement, and emission reduction. Furthermore, the temperature effect on the TDOPF problem is also analyzed. In the case of fuel cost optimization in the 30-bus network, fuel cost increases from 799.85 $/h to 802.9474 $/h when the temperature increases from 0°C to 100°C, corresponding to a fuel cost increase of 0.04% for each 10°C. From the obtained outcomes, the efficacy of the CEO has been proven in finding accurate solutions for the TDOPF problem.

THE WATER FLOW MOVEMENT MODELING IN PASSIVE DISINTEGRATOR OF THE GRAIN MOLASSES’ INSTALLATION

The equipment features’ studying is important because the volume of small and medium sized businesses related to dairy and meat farming in our country is growing. It is also important for the energysaving technologies’ developing and improving. Due to the grain’s high demand as a farm animals’ feed element, its processing technologies are being developed and widely used. In particular, technologies and technical means of grain molasses preparing have been developed. The scheme of grain molasses preparation and modeling conditions are given, water movement in a passive shredder’s modeling results are presented. This modeling in the Star CCM+ program was carried out. The water flow around two grids located at a distance equal to 100 and 200 mm was set; the pipe diameter d = is 30 mm, calculated section length - 1 m. At looking through the fields’ velocity and fluid flow’s lines in the shredder, it was revealed that the flow rates in both cases under consideration are almost identical. There is a velocity clear increasing when the liquid passes through the openings of the gratings and the water bends around the gratings up to a value of 23 m/s. The gratings’ presence in the shredder leads to network resistance and flow power loss’s increasing. The distance between the grids increasing allows to reduce slightly the resistance of the network (in 3%) and flow power’s loss (in 5%). The fluid motion’s given modeling has shown that the passive shredder scheme in the form of a circular tube with two grids installed in it can be considered ineffective due to the proposed device’s high resistances.

Feeder Losses Analysis of Marine Vessel Power Systems: A Case Study of Container Ship Power Loss Analysis Using Newton–Raphson Method

Load survey has become a routine project for shipbuilding and shipping companies to investigate electrical load characteristics to enhance the power system planning and operation of marine vessels. In this brief perspective, we will outline a few steps to feeder losses analysis based on the result conducted by the load survey. The power flow and feeder loss analysis are extracted and used to determine the critical parameters that can significantly affect the system feeder losses used in the electrical load analysis in new ships. Exploring this new research direction will provide a more thorough understanding of feeder losses in marine vessel power systems. In this paper, a case study of container ship power loss analysis using the Newton–Raphson method is presented. The analysis results can provide shipbuilding corporations and ship owners with useful information for planning, designing, operating, and controlling shipboard power systems. As an energy-saving measure for ship microgrids, the frequency converters are widely used by shipyards for seawater and freshwater cooling systems and heating, ventilation, and air conditioning (HVAC) systems, so that these systems can adjust the speed of the motor according to the actual demand of the load, so as to avoid full-load operation during the motor operation. With the proposed method, other measures, such as battery energy storage systems and energy-saving lighting equipment based on LEDs, are also utilized for shipboard power demand management.

The New Definitions of Loss Function for the Model-Based Parameter Identification Method in Power Distribution Network

Accurate device parameters play critical roles in calculation and analysis of power distribution network (PDN). However, device parameters are always affected by the operating status and influenced by manual entry; besides, the distribution area of PDN is very wide with many points, which brings more challenges to PDN parameter identification. Most of the proposed algorithms recently assume that the parameters of PDN contribute in a nonlinear probability space and optimize parameters by the power flow model with a loss function. Although these algorithms can achieve satisfying results in PDN analysis, the relationship between the power flow model and loss functions remains unclear. In this paper, the outputs of the power flow model have been analyzed firstly by experimental data, which includes the head and end voltages, as well as active and reactive power on the low-voltage side. It is revealed that the loss functions used by current algorithms are not suitable and reasonable for power flow model in PDN calculation, which constitutes one of the main findings of this work. Subsequently, this work proposes four novel loss functions combined with genetic algorithm (GA) and Markov Chain Monte Carlo (MCMC) to identify PDN parameters. Compared with the published algorithms, our experimental results show that the loss function defined in this paper can achieve better and more stable performance with about two times lower in MAE, RMSE, and RMPE evaluation functions to identify PDN parameters.

Enhancement of transmission line model to analyze the matching section of a dielectric-loaded accelerator with sharp discontinuities

In this paper, a compact and single-mode X-band dielectric-loaded matching section with constant tilt angle, blended edges, and two discontinuities at both ends is analyzed by the transmission line model. This matching section is designed as a high-power injection coupler to a dielectric-loaded accelerating structure (DLA). Although the transmission line model is a powerful tool for single-mode structures, because of radial inhomogeneity and lack of single value for characteristic impedance in dielectric-loaded structures, this method is not applicable in non-uniform dielectric-loaded structures. To solve this problem, it is shown that a dielectric-loaded waveguide (DLW) can be modeled by a dielectric-filled waveguide (DFW) with the same parameters of the phase constant, power flow, and dielectric loss. The characteristic impedance of a dielectric-filled waveguide can be determined by three structural parameters of the real and imaginary parts of the dielectric material and inner radius. These structural parameters can be found by solving a non-linear equation system made by equality of the parameters of the dielectric-loaded and dielectric-filled waveguides. To analyze the matching section, it is stratified to low thickness and uniform DLWs in the propagation direction and every segment is substituted by its equal DFW model. However, because of sharp variation in dielectric region at two ends of the flared section, solving the non-linear equation system is difficult at these points due to the lack of a proper initial point for the answer. Therefore, two virtual sections are added at the discontinuities to smoothen the variation of the dielectric region. Then, the total transmission matrix and scattering matrix parameters can be obtained without considering the added virtual sections. Moreover, the matching section is simulated by a full-wave electromagnetic software and the results of the scattering matrix parameters are compared with the ones of the proposed method. It is shown that there is a good agreement between the total behavior of the simulation and analytical results and the proposed method has acceptable accuracy.

Assessments of linear power flow and transmission loss approximations in coordinated capacity expansion problems

With rising shares of renewables and the need to properly assess trade-offs between transmission, storage and sectoral integration as balancing options, building a bridge between energy system models and detailed power flow studies becomes increasingly important, but is computationally challenging.Here, we compare approximations for two nonlinear phenomena, power flow and transmission losses, in linear capacity expansion problems that co-optimise investments in generation, storage and transmission infrastructure. We evaluate different flow representations discussing differences in investment decisions, nodal prices, the deviation of optimised flows and losses from simulated AC power flows, and the computational performance. By using the open European power system model PyPSA-Eur, we obtain detailed and reproducible results aiming at facilitating the selection of a suitable power flow model.Given the differences in complexity, the optimal choice depends on the application, the user’s available computational resources, and the level of spatial detail considered. Although the commonly used transport model can already identify key features of a cost-efficient system while being quick to solve, severe deficiencies under high loading conditions arise due to the lack of a physical grid representation. Moreover, disregarding transmission losses overestimates optimal grid expansion by 20%. Adding a convex relaxation of quadratic losses with three tangents to the linearised power flow and accounting for changing line impedances as the network is reinforced suffices to represent power flows and losses adequately in design studies. We show that the obtained investment and dispatch decisions are then sufficiently physical to be used in more detailed nonlinear simulations of AC power flow evaluating their technical feasibility.

Modified moth-Flame optimization for strategic integration of fuel cell in renewable active distribution network

In this article, a novel bi-layer optimization model is proposed for strategic accommodation of fuel cell (FC) in an active distribution network (ADN) that consists of wind turbines and photovoltaic modules. The foremost objective of the proposed model is to maximize the renewable power hosting potential of the distribution system. In outward-layer of the bi-layer optimization model, a vital multi-objective function is broached to assist the daily challenges of ancillary services. The objectives considered are minimizing the annual energy loss of the network, node voltage deviation, inverse power flow, demand deviation and conversion losses for battery energy storage system (BESS) connected with FC. Further, a modified version of moth flame optimization (MFO) is also proposed by overcoming a few limitations observed in its traditional variant. The proposed modification has enhanced the exploration and exploitation potential of MFO such that, their correct balance seeks the global optima. The presented modification is validated before applying it to the proposed simulation model. The proposed modified MFO is deployed to determine the optimization elements of the outward-layer. These are the details related to DERs accommodation. Whereas, a heuristic approach is proposed to solve the inward-layer optimization model designed to determine the optimal hourly power dispatch by BESS connected to FC, as per size suggested by outward-layer. The approach is designed to minimize the considered objectives i.e. annual energy losses and inverse power flow. To exhibit the competency of the proposed model, it is implemented on 33 and 108-bus balance distribution systems for numerous test cases. The resemblance of simulation obtain results reveals the inspirational dominance of the proposed optimization model. Further, the modified variant of MFO is found very effective to enhance the performance of ADN.

Cloud Variance Impact on the Voltage and Power Flow of Distribution Networks with Photovoltaic Generators

The present paper aims to investigate the effect of different types of clouds on the photovoltaic power generators and electricity distribution network in which they are connected. The developed methodology classifies solar irradiance data according to the GOES-13 satellite image processing, which contain information regarding the types of clouds. The image processing results are then compared with real solar irradiance data in order to analyze the influence of shading and thus classify the measured data as: clear sky, partly cloudy and cloudy. The OpenDSS software is employed for simulating the varying generation and load profiles using the IEEE 34 bus system as a testbed. The result analysis shows the power flow and electrical losses, as well as the generation profiles impact on voltage levels and the operation of voltage regulating equipment. Voltage fluctuations and tap changes are also analyzed considering different tap delays.

Active and reactive power joint optimization of active distribution network under new energy access

The access of large-scale distributed generation (DG) to the active distribution network has a great influence on the power flow, node voltage and network loss of the distribution network. In this paper, in order to improve the operation level and economic performance of the active distribution network, the distributed power supply reactive power output and load reduction are used as control variables to establish a multi-objective optimization model with the total network loss, voltage deviation and load reduction cost as the objective function. The voltage of each node, system network loss, load reduction cost and their corresponding control variables are calculated by improved simulated annealing multi-objective particle swarm optimization algorithm. Finally, the IEEE33 node system is used for example verification, the results show that the mathematical model can achieve coordinated control of voltage, reduce network loss and meet the requirements of actual power grid operation.

A Decentralized Three-Level Optimization Scheme for Optimal Planning of a Prosumer Nano-Grid

Rapid improvement in efficiency of renewable energy sources (RESs), increased concerns about carbon emission, substantial power-flow losses, and the emergence of smart grid have all contributed to increased interest toward customers’ contribution in electricity generation in RES-based prosumer nano-grids (PNGs). Such contributions within a PNG can be effectively controlled using dynamic pricing tariffs (DPTs) that hold customers accountable for their electric power exchange behaviors. Prosumer customers optimize their internal power grid based on utility-provided DPT and expect to surpass the break-even point within an anticipated period of time. However, their expected payback period may not be met, as the DPT changes over time as more customers join the market. Therefore, the joint design of PNG and DPT is necessary to give the customers the opportunity to revisit their investment plans, and, at the same time, the utility the opportunity to adjust the pricing scheme. We propose an iterative decentralized three-level optimization scheme to achieve both objectives. The proposed scheme can be applied to a large system for planning of optimal PNGs, while providing a reliable payback period on investment for customers that are involved. The effectiveness of the proposed scheme is verified numerically using a large historical data set.

Reliability-Based Probabilistic Network Pricing With Demand Uncertainty

The future energy system embraces growing flexible demand and generation, which bring large-scale uncertainties and challenges to current deterministic network pricing methods. This paper proposes a novel reliability-based probabilistic network pricing method considering demand uncertainty. Network reliability performance, including probabilistic contingency power flow (PCPF) and tolerance loss of load (TLoL), are used to assess the impact of demand uncertainty on actual network investment cost, where PCPF is formulated by the combined cumulant and series expansion. The tail value at risk (TVaR) is used to generate analytical solutions to determine network reinforcement horizons. Then, final network charges are calculated based on the core of the Long-run incremental cost (LRIC) algorithm. A 15-bus system is employed to demonstrate the proposed method. Results indicate that the pricing signal is sensitive to both demand uncertainty and network reliability, incentivising demand to reduce uncertainties. This is the first-ever network pricing method that determines network investment costs considering both supply reliability and demand uncertainties. It can guide better sitting and sizing of future flexible demand in distribution systems to minimise investment costs and reduce network charges, thus enabling a more efficient system planning and cheaper integration.

A tailored broadband terahertz metamaterial absorber based on the thermal expansion feature of liquid metal

In this paper, a novel temperature field tailored broadband terahertz absorber is proposed, which consists of the metallic mercury resonance units. When the ambient temperature (T) alters, the mercury can be expanded through the vertebral body channel, middle cross glass cavities, cylindrical hole and fill the upper cross glass cavities of such an absorber, which leads to the absorption bands changed. The simulated results indicate that when T = −30 ℃, the wideband absorption (WBA) regions over 90% can be achieved, which are located at 4.53–5.79 THz and 8.15–9.49 THz, and their relative bandwidths (RBs) are 24% and 15.5%, respectively. If T is increased to 300 ℃, such two WBA areas will move to 2.83–3.39 THz and 5.90–7.74 THz, whose RBs are changed to 18% and 13.3%. To investigate the performance of such an absorber, the effects of incident angle, polarization angle and structural parameters on the absorption are discussed. Similarly, the electric and magnetic field intensity distributions, the surface current distributions, power flow and power loss density of the presented absorber are also given to expound the physical mechanism of absorption. The scheme put forward in this paper will provide a new idea for the study of tunable absorbers.

A General Fast Power Flow Algorithm for Transmission and Distribution Networks

Fast power flow calculation is generally required in static security analysis and power system optimal planning. And the classical DC power flow algorithm, due to its simple mathematical model, linearized equation, and rapid solving speed, is widely utilized. However, the classical DC power flow algorithm has been found to be only suitable for high voltage transmission networks with small branch impedance ratio. To address this issue, a general fast power flow algorithm is proposed. Utilizing this method, the classical DC power flow algorithm is firstly performed to obtain the initial values of the branch active power flow. And the nodal voltage angles are then calculated by the established node-injected reactive power equations. Secondly, through the identical transformation and approximate treatment of the node power flow equation, a voltage offset calculation method for PQ nodes is proposed. Finally, the active power flow and active power loss can be calculated based on the corrected phase angles and node voltages. Simulation studies on standard IEEE power systems, such as the IEEE 33-bus and IEEE 118-bus systems, etc., were conducted by the presented algorithm, compared with those by the back/forward sweep, classical DC power flow and Newton-Raphson algorithms. It is indicated that, the proposed power flow algorithm has the superiority in satisfactory calculation speed and non-sensitivity on the network impedance ratio.

Grid-Specific Co-Optimization of Incentive for Generation Planning in Power Systems With Renewable Energy Sources

Enhancement in efficiency of renewable energy sources, raised concern about greenhouse gas emission, significant power losses within transmission and distribution networks, unpredictable and unreliable fossil fuel cost, and expansion of reliable communication infrastructure offered by smart grids have all contributed to an increasing interest in deployment of renewable energy sources in energy mix. However, the widespread utilization of renewable energy sources in an open energy market without proper grid-based incentives for aimed contribution levels is uncertain. This article proposes a co-optimization algorithm to find the minimum incentives that result in the desired level of renewable energy source penetration in energy supply chain and optimal distribution of power sources in the electric power grid. The algorithm first finds the proper incentive based on the power-flow losses, then it uses a novel optimization approach to solve a mixed integer non-linear programming optimization of generation planning to minimize the energy cost. Unlike other incentive design methodologies, the proposed algorithm is not only supply specific, but also it depends on the demand and the structures of the grid. The method finds an exclusively designed set of incentives for electric energy supplies that do not emit greenhouse gases or heat to the atmosphere.