Comparison of Different Heuristic Algorithms in a Centralized Implementation of a Distributed Power Flow Control System

The study of power system planning, security and control is crucial for determining optimal power flow (OPF), a highly non-linear complicated issue. The functioning of the power system remains complex when Renewable energy sources are connected to the grid along traditional generators. This review paper describes various techniques applicable to the power system networks accessible in the literature. The conventional optimisation algorithms have been reintroduced, while the power systems have been heavily predisposed over the last few years. The most crucial technical, adaptive and economic tool in this context is OPF. In this paper, we compare OPF approaches related to objective functions. Aside from computational power, the case study network and publication dates for these algorithms are described. Finally, we will address some of the basic challenges that arise from the new OPF approach to the modern grid. Mainly, optimisation techniques are compared in terms of reliability, accurateness, faster convergence and applicability for single and multiple objective functions. Initially, the paper discusses types of networks such as AC or DC, constraints and their objectives on OPF, mathematical and different optimisation techniques reviewed. The heuristic and meta-heuristic algorithms, like genetic algorithm and Jaya algorithm, were compared for various operational parameters. In this work, OPF with single- or multi-objective functions such as voltage stability, voltage deviation, emission, cost and losses, consisting of conventional and renewable energy resources were considered. Additionally, Pseudo-code algorithms were presented for some recently evolved algorithms to ease the understanding of the readers.

This paper focuses on distribution systems featuring renewable energy sources and energy storage devices, and develops an optimal power flow (OPF) approach to optimize the system operation in spite of forecasting errors. The proposed method builds on a chance-constrained multi-period AC OPF formulation, where probabilistic constraints are utilized to enforce voltage regulation with a prescribed probability. To enable a computationally affordable solution approach, a convex reformulation of the OPF task is obtained by resorting to i) suitable linear approximations of the power flow equations, and ii) convex approximations of the chance constraints. Particularly, the approximate chance constraints provide conservative bounds that hold for arbitrary distributions of the forecasting errors. An adaptive optimization strategy is then obtained by embedding the proposed OPF task into a model predictive control framework.

This paper aims to achieve the exact resolution of an optimal power flow (OPF) problem in an electrical network. In the OPF, the goal is to plan the production and distribution of electrical power flows to cover, at minimal fuel cost, the consumption at various points in the network. Three variants of the OPF problem are studied in this manuscript. The first one, OPF corresponds to the case where power production costs in the network are modeled with a quadratic cost. In the second variant, OPF with outages of some lines, we clarify the extent to which power flow is affected by the outages and the increasing number of overloaded lines. Finally, the last variant, secured OPF corresponds to the case where the management of production units can respect the power limit of each line by rescheduling power production units. The study focuses on congestion management in the IEEE 30 bus system by applying a model for OPF, incorporating data from both transmission lines and generators. The research proposes a Hunting Optimization Technique which is named “Multi-Objective Ant Lion Optimizer (MOALO)” to solve single and multi-objective optimization problems to find a solution for management pricing, comparing results with other research methods to show the effectiveness of the applied approach and the mathematical model representing congestion management.

Distributed generators (DGs) are nowadays most commonly used in distribution networks to meet the rising demand. The distribution network power flow is altered as more distributed generations are integrated with the distribution network. Analyzing and researching the network's power flow with distributed generation is an essential element of analyzing the distributed generation's influence on the networks. This study proposed new sites in the test network for the purpose of connecting DGs. Good results were obtained in improving the necessary network elements. Firstly, applying a Newton-Raphson method to measure the distribution network's power flow without distributed generations. Then the optimal power flow approach with DGs is set up based on many goals such as minimizing fuel cost, minimizing losses, voltage deviation, increasing efficiency, and the incremental fuel cost in the network appeared. Eventually, applying Particle Swarm to overcome the optimization problems. In MATLAB software environment and programing MATPOWER version 6.0, the simulation is evaluated and validated using the IEEE30 node method. The test results indicate that optimal power flow analysis with distributed generation will accomplish many networks aims and boost system economy.

Proliferation of Distributed Energy Resources (DERs) and Phasor Measurement Units (PMUs) into electric power distribution grids presents new opportunities for utility operators to manage distribution systems more effectively. In this work we formulate an Optimal Power Flow (OPF) approach that manages DER power injections to minimize the voltage phasor difference between two nodes on a distribution network with the goal of enabling efficient network reconfiguration. To accomplish this, we develop a linear model that relates voltage phase angles to active and reactive power flows in unbalanced distribution systems. Used in conjunction with existing linearizations relating voltage magnitudes to power flows, we formulate an OPF capable of minimizing the voltage phasor difference between two points in a network. In simulations, we explore the use of the developed approach to minimize the phasor difference across switches to be closed, thereby providing an opportunity to automate and increase the speed of reconfiguration in unbalanced distribution grids.

The increasing penetration of wind generation in electric power systems has made evident the necessity of a unified energy infrastructure interdependency analysis, in order to explore the optimal use of fossil fuel-based generation and the security constraints associated with different energy infrastructures. In this context, the optimal generation dispatch of online generating units is important in the daily operation planning. This paper proposes a multi-energy day-ahead optimal power flow (OPF) approach in order to assess the wind energy penetration in an electric power system and its impact on the fossil fuel-based generation management. The applicability of the proposed approach is demonstrated by integrating a 15-node natural gas network and a 4-node coal distribution system with the IEEE 118-bus power system.

This study presents two approaches to handling under‐frequency regulation in isolated microgrids. The first one is a governor power flow (PF) model in which the generators steady‐state governor equations are modeled into a full Newton PF formulation resulting in an augmented sparse linearised system of equations to be solved at each iteration. As a result, it is possible to evaluate the under frequency problem in the case of microgrid islanding as well as to set the reference bus angle to evaluate the possibility of reconnection to the main grid. The second approach presents an optimal PF (OPF) formulation in which the generators governor equations are considered as additional equality constraints to determine the minimum amount of load shedding to keep the system frequency between specified limits. In both methods, it is also used an equation that provides voltage regulation in a droop‐based control. The reactive power generation limits in the OPF approach are bounded by a proposed complementarity constraint‐based method adapted for the generators' droop‐controlled terminal voltage. The proposed approaches are evaluated and validated through the study of the EHV1 Network, a 61‐bus 33/11‐kV radial distribution system, and the New England test system.

This paper develops an effective control framework for DC voltage control and power-sharing of Multi-Terminal DC (MTDC) grids based on an Optimal Power Flow (OPF) procedure and the voltage-droop control. In the proposed approach, an OPF algorithm is executed at the secondary level to find optimal reference of DC voltages and active powers of all voltage-regulating converters. Then, the voltage droop characteristics of voltage-regulating converters, at the primary level, are tuned based on the OPF results such that the operating point of the MTDC grid lies on the voltage droop characteristics. Consequently, the optimally-tuned voltage droop controller leads to the optimal operation of the MTDC grid. In case of variation in load or generation of the grid, a new stable operating point is achieved based on the voltage droop characteristics. By execution of a new OPF, the voltage droop characteristics are re-tuned for optimal operation of the MTDC grid after the occurrence of the load or generation variations. The results of simulation on a grid inspired by CIGRE B4 DC grid test system demonstrate efficient grid performance under the proposed control strategy.

This paper proposes an approach for optimal power flow considering several contingency states. Initially, contingency selection is conducted to measure how much a specific contingency may affect the operation cost. Then, some severe contingencies are incorporated into optimal power flow problem. All considered states, normal and contingency states, are simulated simultaneously. Thus, if contingency occurs, it can be ensured that all constraints such as generation limit, transmission limit and ramp rate will be satisfied. To solve the problem, quadratic programming is applied. IEEE 30 bus system is used as test system to show the ability of the proposed approach.

In this paper two loss allocation (LA) schemes based on the principle of equivalent bilateral exchanges (EBEs) and the network Z-bus matrix are compared with each other. The modified IEEE 14-bus network has been selected as case study. Several operating conditions such as, load increment and system congestions are applied to the test system in order to evaluate the loss allocation methods. In the case of network congestions optimal power flow is used based on a P.S.O. method. An economic analysis with these LA methods is also carried out. Results show that these economic indexes are very close to the marginal costs derived from an optimal power flow (OPF) approach with the advantage of reducing volatility. They also indicate that the allocation schemes produce loss allocations that are appropriate and they behave in a physically reasonable manner while the congestion is occurred.

Based on the forecasted power demand, energy generated by the powerindustries, is lost on their path to users via the transmission and distribution networks. This is consistently one of the most predominant issues facing the power industries. In view of the expansion of the distribution system, most power losses occur in such networks. So, there has a great need to reduce the losses. In this paper, an Optimal Power Flow (OPF) approach is implemented by minimizing the total system losses. And also, the impacts of Wind and D-STATCOM on loss reduction and voltage profile improvement are studied by placing them individually and simultaneously at optimal location. Sensitivity based methods are used to find optimal location. In addition, the annual energy savings and energy loss costs obtained using Deterministic load is compared with Probabilistic load. The entire case study was carried out on a standard IEEE 69 bus Radial Distribution System (RDS) using General Algebraic Modeling System (GAMS) software.

The application of the Newton optimal power flow (OPF) approach to the assessment of VAR controllers on voltage security in the Taiwan Power Company (TPC) is presented in the paper. Important functions in the developed OPF package were achieved to satisfy dispatching requirements. Cases were studied through use of these functions for the purpose of assessing the effect of the various types of VAR controller while considering control sequences. The weakness of traditional OPF packages is pinpointed in that they only obtain an equilibrium solution without the consideration of a proper control sequence. Several significant comments are suggested, on the basis of these results, to set up useful criteria for the security dispatch. A practical 251-busbar system (Taipower) is used to illustrate the test results.

With transportation electrification, the power systems and traffic systems are more and more interdependent on each other. To analysis this interdependence more concisely, an optimal traffic power flow problem is formulated with the help of alternating current (AC) optimal power flow and vehicle routing problem (VPR). These two problems are integrated into an unified time-space network (TSN), as a mixed integer programming problem. To solve the meso-scale level problems with multiple oriented destination pairs, the random permuted alternating direction method of multipliers is adopted to solve the formulated problem distributed. The case study is performed on the modified IEEE-30 and Sioux fall networks, and the results verify the effectiveness of the proposed scheme.

This study proposes an improved particle swarm optimization method to find optimal power flow by using the power transmission loss as an objective function. In the literature, PSO is a well — known intelligent search method to handle the solution of optimal power flow problem. A novel scheme which is called Improved PSO (IPSO) is defined by modifying the initialization step of PSO algorithm and choosing the load bus voltages, generator active and reactive powers, line flow capacities as penalty functions in the objective function. PSO and IPSO-based optimal power flow solutions are compared with each other on IEEE 118 and 300 bus systems. According to the test results, the power loss obtained by IPSO-based solution has less power loss than PSO-based solution. This proposed method can be used to obtain faster desirable solutions and better power loss results for the optimal power flow problem in case of power loss minimization.

Flexible AC Transmission Systems (FACTS) play a vital role in enhancing the stability, efficiency, and reliability of modern power systems. With the increasing complexity of power grids due to the integration of renewable energy sources, effective control of power flow, voltage regulation, and stability improvement are critical challenges. FACTS devices, such as Static Synchronous Compensator (STATCOM), Unified Power Flow Controller (UPFC), and Thyristor- Controlled Series Capacitor (TCSC), offer advanced solutions to mitigate these challenges by providing dynamic voltage control, reactive power compensation, and congestion management. This paper presents a comprehensive analysis of various FACTS devices, focusing on their control strategies, applications, and impact on improving power system performance. Simulation results demonstrate the effectiveness of FACTS devices in maintaining voltage stability, optimizing power flow, and minimizing transmission losses, ultimately contributing to a more efficient and resilient power grid.