Power Flow Technique Research Articles

Towards carbon‐free electricity: A flow‐based framework for power grid carbon accounting and decarbonization

AbstractThis study introduces a comprehensive framework aimed at advancing research and policy development in the realm of decarbonization within electric power systems. The framework focuses on three key aspects—carbon accounting, carbon‐aware decision making, and carbon‐electricity market design—and proposes solutions to existing problems. In contrast to traditional pool‐based emission models, this framework proposes a novel flow‐based emission model that incorporates the underlying physical power grid and power flows. Thus, the framework allows accurate carbon accounting at both the temporal and spatial scales, thereby facilitating informed decision‐making to achieve grid decarbonization goals. The framework is built on a flow‐based carbon accounting methodology and utilizes the carbon‐aware optimal power flow technique as a theoretical foundation for decarbonization decision‐making. Additionally, this study explores the potential design of carbon‐electricity markets and pricing mechanisms to incentivize decentralized decarbonization actions. Critical issues of data availability, infrastructure development, fairness and equity considerations are also discussed.

Multi-faceted sustainability improvement in low voltage power distribution network employing DG and capacitor bank

Efficient distribution of active and reactive power in distribution networks is crucial for ensuring that consumer demand is met and that electrical power quality is maintained. This requires careful planning, particularly in terms of optimally placing and sizing distributed generator (DG) and capacitor bank (CB) units. These units play a key role in minimizing power losses and voltage fluctuations within the network. However, implementing DG and CB units in unbalanced distribution networks presents unique challenges due to inherent system unbalances. To address these challenges, this article proposes a method for allocating and sizing DG and CB units in unbalanced distribution networks. The approach accounts for the network's unbalance and targets multiple objectives, such as reducing power losses, improving multi-phase voltage stability, and minimizing phase-to-phase voltage unbalance. The fast and flexible radial power flow (FFRPF) technique is employed to model complex interactions and constraints within the network, leading to a multi-objective optimization problem. This optimization problem is solved using the weight aggregated particle swarm optimization (WA-PSO) method, a variant of particle swarm optimization tailored for multi-objective functions. WA-PSO simplifies the process by combining multiple objectives into a single function using weighted aggregation. The efficacy of this approach is validated on 19, 34, and 123-node unbalanced radial distribution networks (URDNs). The results show significant improvements in power delivery efficiency across all tested networks, especially when DG and CB units are operated simultaneously. Specifically, DG and CB integration led to a reduction in system losses by 89.90 %, 88.42 %, and 86.87 %, and a decrease in three-phase voltage unbalance indices by 88.75 %, 81.68 %, and 39.05 %, for the 19, 34, and 123-node systems, respectively, while maintaining voltage stability within acceptable limits. Additionally, CO2 emissions were reduced by 52 %, 62 %, and 53 % when microturbines were utilized instead of coal-based thermal power plants, further highlighting the environmental benefits of the proposed approach.

Methods to mitigate voltage-rise issues in transmission systems

This paper proposes some novel methods for mitigating undesired voltage rises in modern-day power systems. Some older approaches are also revisited in the light of new developments including the proliferation of power-electronic interfaced equipment. The analysis is performed using both power flow technique as well as long-term simulation employing quasi-steady-state approximation of short-term dynamics. Guidelines and mitigation countermeasures that may be utilized during either system planning or operation are investigated, such as optimal placement of new reactor installations, special transformer load-tap-changer (LTC) controls and reactive power absorption by renewable energy sources, such as wind farms connected through power converters in distribution feeders. Several case studies are investigated in two test systems: a sub-transmission area of the French Transmission Grid, and the Hellenic transmission power system, for which a number of different operating points is considered.

A Real-Time Zbus-based Method for Peer-to-Peer Energy Transactions in The Energy Internet

The Energy Internet (EI) has emerged as a promising field within smart grids, addressing capacity limitations and discrepancies in energy resources. It facilitates a peer-to-peer (P2P) energy trading environment for EI prosumers and consumers, reducing reliance on the main grid. To ensure an efficient P2P trading process, it is essential to route energy through the path with minimal power loss optimally. The Energy Router (ER) plays a pivotal role in governing power flow through EI. This paper presents the development of a novel real-time Zbus-based method for directing P2P energy transactions within the EI considering congestion management. The proposed method depends on bus impedance matrix in forming the routing matrix. Firstly, the ER’s structure and function are outlined in relation to the network, and then to design the EI’s topology using an adjacency matrix representation. Secondly, the proposed method methodology is presented in steps and explained on simple 7-bus microgrid. Additionally, a novel congestion management method is integrated into the routing algorithm, considering transmission line loading and available capacity during route selection. Furthermore, the paper applies a power flow technique to the selected routes to optimize power flow performance. The proposed method demonstrates enhanced directness and accuracy compared to existing approaches. Its efficiency is validated by testing a modified IEEE 14-bus system and the standard IEEE 30-bus system. Importantly, the method successfully identifies the minimum loss path, despite the unnecessity of power loss calculations in the routing algorithm. The key contribution of this research lies in providing a comprehensive and practical solution for P2P energy transactions in the EI, showcasing substantial improvements in accuracy, efficiency, and congestion management compared to previous methods.

Optimal Allocation of Distributed Generation Using Improved Cuckoo Search Algorithm

This work presents an improved cuckoo search algorithm based on Success Rate (CSA-SR) for optimal allocation of Distributed Generation (DG). This is necessary in order to improve the power quality of the distribution system by minimizing power loss and improving voltage stability. Voltage Stability Index (VSI) is applied to identify restricted unhealthy buses/areas in the distribution networks. The work is implemented on standard IEEE 33 Bus test systems. Newton Raphson Power Flow (NRPF) technique is used in MATLAB R2019b environment for the power flow analysis. The overall IEEE 33 Bus system real power loss obtained from the simulation result is found to be 202.7071MW at the base case. Following the application of 3 DGs using CSA-SR, the real power loss is found to be 113.9630 MW which shows a reduction of 88.441MW which is equivalent to 43.77% as related to the base case. The results minimized the system losses while significantly enhancing the voltage profile of the bus voltages as a result of optimal siting and sizing of the DG. These show that the CSA-SR technique outperformed PSO, which was used to ascertain the effectiveness of the developed scheme.

Improving voltage collapse point under transmission line outage by optimal placement and sizing of SVC using genetic algorithm

In many power systems, voltage instability can increase the risk of voltage collapse and, as a result, turn the power system toward a blackout. Therefore, increasing the voltage collapse point is required. A transmission line outage is an emergency condition in power systems that can lead to voltage instability and voltage collapse. Thus, it is expected to employ shunt-connected flexible AC transmission systems (FACTS) such as the static var compensator (SVC) to increase the voltage collapse point when lines outage. This paper presents the genetic algorithm (GA) application to optimal placement and sizing of an SVC for increasing voltage collapse points following lines outage. The continuation power flow (CPF) technique has been used to determine the maximum loading point (MLP) corresponding to the point of voltage collapse. Also, to reduce the number of scenarios when line outages occur, a list in ascending order is established based on the line outage priority (LOP). The IEEE 14-bus test system is chosen to carry out simulations, and an SVC will be installed in the system based on the GA results. Simulation results confirm the effectiveness of an SVC for improving voltage stability as well as increasing voltage profile.

A proposed PMU-based voltage stability and critical bus detection method using artificial neural network

Voltage stability detection is currently still becoming the main issue in the modern integrated renewable energy power systems. To assess the voltage stability, the classical methods based on continuation power flow (CPF) technique were used to show nose curve. However, the classical methods require complete model of power system and long computation time. Data driven analysis and synchronized real time measurement technologies currently are developing in power systems monitoring, including the stability detection. The detection method is built based on the historical event model and uses the real time measurement as an input. For that reason, the algorithm to detect the voltage instability and critical bus is proposed using the artificial neural network (ANN) technique to represent the historical event model using the PMU measurement data. The ANN model architecture for this application is developed by creating seven hidden layers consisting of one normalization, four rectifier linear unit, one softmax and one sigmoid layer. To warrant the accuracy, the k-fold cross-validation is used. The algorithm is simulated on modified IEEE 14 test system which consider different loading scenario, line contingency, number of PMU and Photovoltaic (PV) integration. To mimic the actual historical data, the synthetic data is generated and labelled. The result shows that the proposed method can represent the complete power system model by giving high accuracy which for voltage stability detection is > 97% and critical buses detection is > 96% for all scenarios. Moreover, the required computation time is between 16 and 18 s per detection which makes the scalability to the real time detection is reasonable.

Optimal Contracting of Transmission System Usage Combined With Subtransmission Planning via Cross-Entropy Method

Local power distribution companies (DISCOs) are not self-sufficient in electricity to serve their customers and require importing additional energy supply from the interconnected bulk power systems. In Brazil, they annually carry out the contracting process for the amount of transmission system usage (ATSU) for the next four years. This process is a real example of a task that involves decisions under uncertainty with a high impact on the productivity of DISCOs and the electricity sector in general. The task becomes even more complex in face of the increasing variability associated with the generation of renewable energy and the changing profile of the consumer. In this work, the main objective is to develop a methodology based on probabilistic power flow and cross-entropy techniques to assess the optimal contracting under uncertainty of the ATSU, combined with the expansion plan for the subtransmission network. As the robustness of the network influences the power import by the DISCO, there are real measurable benefits to assessing contracts and grid expansion altogether. Results with academic and real systems show that the proposals reduce the total costs with ATSU contracts.

Optimal Power Control in Distributed Generation Units in an Islanded Microgrid

This article studies the effect of new optimization techniques with the aim of finding the best solution using a fuzzy approach for operating an independent microgrid. The power flow technique is used to model and solve the problem of optimal active and reactive power control of distributed generation units (DGs) in an island microgrid (MG), while taking into account the improvement of the voltage profile and the voltage stability index by regulating the droop characteristics of DG sources. The suggested algorithms, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Harmony Search (HS), Hybrid HS-GA, and Teaching-Learning Based Optimization, solve the optimization issue (TLBO). The numerical results of optimization algorithms are compared in terms of best solution, number of iterations, and convergence rate. Regarding multi-objective nature of the problem, the non-dominated sorting method is used to obtain the Pareto front for all algorithms. Finally, the best solution is selected from Pareto solutions using proposed fuzzy approach. Simulation results on the standard IEEE 33-bus network in MATLAB show that the TLBO algorithm has higher efficiency, and faster convergence rate compared to other methods in this study.

A Review of State-of-the-Art Techniques for Power Flow Analysis

This paper presents a review of the State-of-the-Art Techniques for Power Flow Analysis (PFA) that are newly proposed. However, some of the existing classical methods for the Power Flow Analysis such as Newton-Raphson method, Gauss-Siedel method, and Fast Decoupled Power Flow Technique were also discussed so as to give a background and a wider view of the improvements recorded so far. From the findings, the State-of-the-Art Techniques such as Particle Swamp Optimization Algorithm for optimal Power Flow Incorporating Wind Farms, Hybrid Firefly and Particle Swamp Optimization Algorithm, Mann Iteration Process Technique for III-Conditioned System, and A New Approach Newton-Raphson Load Flow Analysis in Power System Networks with STATCOM have shown superiority over and above the existing classical methods in terms of accuracy, speed of convergence and overall efficiency. Particularly, there are two newly proposed methods for dc grids: Direct Matrix–Current application (DM-CA) and Direct Matrix-Impedance Approximation (DM-IA) methods that stand out with respect to accuracy, convergence and computational effort which means they can be used for planning, optimization and analysis purposes of practical dc grids.

Optimal Configuration of Extreme Fast Charging Stations Integrated with Energy Storage System and Photovoltaic Panels in Distribution Networks

Extreme fast charging (XFC) for electric vehicles (EVs) has emerged recently because of the short charging period. However, the extreme high charging power of EVs at XFC stations may severely impact distribution networks. This paper addresses the estimation of the charging power demand of XFC stations and the design of multiple XFC stations with renewable energy resources in current distribution networks. First, a Monte Carlo (MC) simulation tool was created utilizing the EV arrival time and state-of-charge (SOC) distributions obtained from the dataset of vehicle travel surveys. Various impact factors are considered to obtain a realistic estimation of the charging power demand of XFC stations. Then, a method for determining the optimal energy capacity of the energy storage system (ESS), ESS rated power, and size of photovoltaic (PV) panels for multiple XFC stations in a distribution network is presented, with the goal of achieving an optimal configuration. The optimal power flow technique is applied to this optimization so that the optimal solutions meet not only the charging demand but also the operational constraints related to XFC, ESS, PV panels, and distribution networks. Simulation results of a use case indicate that the presented MC simulation can estimate approximate real-world XFC charging demand, and the optimized ESS and PV units in multiple XFC stations in the distribution network can reduce the annual total cost of XFC stations and improve the performance of the distribution network.

Real-Time Estimation of Support Provision Capability for Poor-Observable Distribution Networks

An indispensable step towards coordinating the actions of distribution and transmission system operators ( <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dso</small> s- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">tso</small> ) is to estimate the range of flexibility that can be offered to the <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">tso</small> by <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dso</small> s. Within this context, a data-driven probabilistic approach is proposed to evaluate the capability of a distribution network in providing active and reactive power support in real-time. To this end, in an offline phase, a linear discriminant analysis model, together with a piecewise linear model of the distribution network are trained to delineate the boundary of a region representing the adherence to distribution network operational constraints. In the implementation phase, this region comprises the feasible set of a series of optimization problems, formulated to determine the support provision capability. These optimization problems are of iterative linear programming type, which allows for real-time applicability. The evaluated support capability can be deemed as the available reserve in real-time transmission operation, which enables providing a coordinated response towards unexpected events, and facilitates the participation of distributed resources in the balancing market by granting an up-to-date estimation of available supports. This approach is tested on the IEEE 123-node system and verified through comparison with an AC optimal power flow technique.

Design and Implementation of a PV-Fed Grid-Integrated Wireless Electric Vehicle Battery Charger Present in a Residential Environment

The power transfer technique used to charge electric vehicles (EVs) has gone through a large development lately. Developing a purely autonomous vehicle has motivated researchers to implement the wireless power transfer technique to charge the EV battery. Previously developed EV used a pure grid-dependent charging system, increasing the net energy consumption from the grid. The vehicle weight also reduces the vehicle's reliability with the increase in the size of the battery. This limitation is eliminated by the proposed technique that uses a wireless EV battery charging system with a utility grid. This article presents an improved system for supplying photovoltaic (PV) power to an EV used in a grid-interfaced residential system. This power electronic converter-based interfacing system facilitates a bidirectional power flow technique for feeding extra PV panel power to the grid and charging the EV using utility grid power during the unavailability of solar power. A bidirectional cycloconverter is employed, which delivers a variable frequency concerning modes of operation of the system. The experimental prototype employs an opal-RT real-time simulator for integrating the proposed system into the grid. This article presents the comparison of the simulation and experimentation results of the wireless EV charging system.

A Dynamic Real Time Interphase Power Flow Technique of Railway Platform Rooftop Solar Power Interface with 25 KV Oh Traction

Indian Railways has planned to tap 1000 MW solar energy in ensuing five years.500 MW from railway platform roof tops &amp; rest from other official ancillary complexes to supplement traction load. Roof-Top spaces are ample considering long &amp; wide railway platform at stations in India. TSS in railway traction power supply is placed for each 50 to 90 km segment along railway track for UP &amp; DOWN routes. It is possible to design suitable scheme that can be interfaced for direct connection to 25 kV AC system at TSS locations on 4 to 5 average railway platforms from Bhusawal via Jalgaon, Pachora Nandgaon, Manmad, Lasalgaon, Niphad, Nashik Road ,Igatpuri &amp; Kasara Stations. Considering roof top area of 1000 to 5000 sq-metre, it is possible to install solar panels which can generate 100 kW to 500 kW. Saving with conventional Energy intake from utility to the tune of 30 to 40 %. It has been physically seen on live train passing that the load varies from few hundred kW to 3 or 4 MW for duration of few seconds to minutes. Neutral sections facilitate balanced loading on all three phases of utility as the phases R, Y &amp; B are loaded in sequence. This paper explores the ever-tried model of direct solar power feed from railway platform rooftops to 25 kV AC traction supply using dynamic inter-phase power flow technique in real time with all associated balance of equipment’s.

Optimal Power Flow Technique for Distribution System Considering Distributed Energy Resources (DER)

Modern electric power systems consist of large-scale, highly complex interconnected systems projected to match the intense demand growth for electrical energy. This involves the decision of generation, transmission, and distribution of resources at different time horizons. They also face challenges in incorporating new forms of generation, distributed generations, which are located close to consumer centers, and new loads such as electric vehicles. Traditionally, the nonlinear Newton–Raphson optimization method is used to support operational decisions in such systems, known as Optimal Power Flow (OPF). Although OPF is one of the most practically important and well-researched sub-fields of constrained nonlinear optimization and has a rich history of research, it faces the convergence difficulties associated with all problems represented using non-linear power flow constraints. The proposal is to present an approach in a software component in cloud Application Programming Interface (API) format, with alternative modeling of the electrical optimization problem as a non-linear objective function and representing electric network constraints modeled through both current and voltage Kirchhoff linear equations. This representation overcomes the non-linearity of the OPF problem considering Distributed Energy Resources (DER). The robustness, scalability, and availability of the method are tested on the IEEE-34 bus system with several modifications to accommodate the DER testing under conditions and in radial or meshed distribution systems under different load scenarios.

Consensus-based distributed optimal power flow using gradient tracking technique for short-term power fluctuations

This paper proposes a consensus-based distributed optimal power flow (CD-OPF) scheme to fast track the sub-optimal operating point, considering the power systems’ state deviance caused by short-term fluctuations of renewable generations. By combining the chance-constraint optimal power flow (CC-OPF) and gradient tracking technique (GTT), the proposed scheme could achieve more precise optimization for power system. Firstly, for a time interval, the optimal power flow is applied to obtain the optimal state by chance-constrained programming according to the measured operating states. Then, for the moments within the time interval, a communication-less distributed GTT is performed at each local renewable generation unit to track the sub-optimal point considering its generation fluctuations. Next, the CD-OPF is achieved based on the consensus that each renewable generation unit performs its own tracking optimization by GTT independently, so as to reduce the dependence on global information and fast communication. Finally, the simulations on the IEEE-39 bus power system, the IEEE-118 bus power systems and the wind farm validate the effectiveness of proposed scheme. The results show that the proposed method can decrease the power loss, prevent the voltage violation, and reduce the time-cost.

Comparison of different power flow techniques for power grid vulnerability assessment against symmetrical faults using bus impedance matrix

Due to the widespread proliferation of distributed generation resources and the current market situation, ensuring the security and reliability of power grids against fault events has become a more challenging task. The aim of this paper is to compare different power flow techniques for power grid vulnerability assessment against symmetrical fault incidents using bus impedance matrix. In this study, first, the relationship of the post-fault voltage phasor at each bus with the pre-fault voltage phasors at that bus and the faulted bus, impedance matrix elements, and fault impedance is investigated through power system analysis under pre-fault and post-fault circumstances. Subsequently, the accuracy of different iterative and non-iterative power flow algorithms, i.e. Newton Raphson (NR), Fast Decoupled (FD), and Direct Current (DC) methods, for the power grid vulnerability assessment is compared. To achieve this, the fault analysis at each bus is performed commencing with a very large fault impedance and ending with the fault impedance at which one of the buses reaches the low voltage violation limit. Finally, to appraise the proposed strategy, several simulations have been undertaken on IEEE 14 bus system using MATLAB software. The simulation results indicate that the power grid vulnerability against symmetrical faults is highly influenced by the type of applied power flow technique.

Using OPF-Based Operating Envelopes to Facilitate Residential DER Services

The proliferation of residential distributed energy resources (DER), such as solar PV and batteries, is creating opportunities for DER owners to provide system-level services through aggregators. However, if this aggregated response is not adequately managed by distribution companies, the simultaneous active power exports (or imports) can result in voltages and currents well beyond the limits of their networks. But the big barrier is that, often, distribution companies cannot directly manage DER or aggregators. This work proposes the use of operating envelopes—time-varying, meter-level export/import limits that a distribution company issues to aggregators—to ensure network integrity while facilitating residential DER services. The operating envelopes are calculated using a linearised, three-phase optimal power flow (OPF) technique that also exploits controllable network assets (e.g., on-load tap changers). Using a realistic Australian MV-LV network with 4,600+ residential customers, results show that network integrity can be ensured without the need for distribution companies to directly control DER. Furthermore, existing on-load tap changers create additional voltage headroom and, thus, larger operating envelopes (and potential services). Given that distribution companies do not know the ultimate exports/imports of customers providing services, a probabilistic testing of the operating envelopes confirms that they are adequate for most plausible scenarios.

Optimal Location and Sizing of PV Generation Units in Electrical Networks to Reduce the Total Annual Operating Costs: An Application of the Crow Search Algorithm

This study presents a master–slave methodology to solve the problem of optimally locating and sizing photovoltaic (PV) generation units in electrical networks. This problem is represented by means of a Mixed-Integer Nonlinear Programming (MINLP) model, whose objective function is to reduce the total annual operating costs of a network for a 20-year planning period. Such costs include (i) the costs of purchasing energy at the conventional generators (the main supply node in this particular case), (ii) the investment in the PV generation units, and (iii) their corresponding operation and maintenance costs. In the proposed master–slave method, the master stage uses the Discrete–Continuous version of the Crow Search Algorithm (DCCSA) to define the set of nodes where the PV generation units will be installed (location), as well as their nominal power (sizing), and the slave stage employs the successive approximation power flow technique to find the value of the objective function of each individual provided by the master stage. The numerical results obtained in the 33- and 69-node test systems demonstrated its applicability, efficiency, and robustness when compared to other methods reported in the specialized literature, such as the vortex search algorithm, the generalized normal distribution optimizer, and the particle swarm optimization algorithm. All simulations were performed in MATLAB using our own scripts.

A Comparative Study of Compensate Schemes of Loop Power System Affecting to Total Power Losses

This paper presents the compensate schemes consisting of series scheme, shunt scheme and combine scheme of power system. The power system of Nakhonpathom Rajabhat University, which is the loop system while connected with 90% of rated transformer as the load, is chosen as case study. In addition, the Newton Raphson method is the power flow technique for simulation via ETAP programming. This paper focuses on comparing the total power losses in each scheme. Moreover, the suitable scheme is analyzed in term of voltage magnitude and total power losses in transmission line. The reactive power converting to compensate impedance is the technique that starts from 20 MVAr to 200 MVAr of both series and shunt compensate schemes. In term of combine compensation will be constant of 140 MVAr to 200 MVAr as the shunt compensate while the series compensate will be changed from 140 MVAr to 200 MVAr in each case. The simulation compares the total power losses of the original system without compensation and the new system compensated with three schemes. Nevertheless, the results show that the shunt compensation with reactive power start from 140 MVAr can decrease a total power loss of transmission line while the series compensation can only increase the voltage magnitude but the total power losses will be increased together. In addition, the combined compensation can increase the voltage magnitude and the total power losses. Therefore, this is the choice for the scheme for increasing the voltage magnitude and the total power losses. On the other hand, in terms of manufacturing there are many factors to determine such as sizing, insulator characteristic and installation.