Bus voltage control and optimization strategies for power flow analyses using Petri net approach

Large-scale distribution systems (DSs) require an efficient power flow algorithm which can explicitly exploit their characteristics. This paper presents a novel power flow algorithm for radial and weakly meshed distribution systems (WMDSs) using a direct method (DM). The paper also develops a novel approach to simulate the voltage-controlled buses which is becoming increasingly important due to the introduction of distributed generations in DSs. The proposed power flow algorithm is constructed based on simple electrical circuit rules so that only a Z matrix expressing common impedances between loads is required for simulation. For WMDSs, only modification is to use the current divider rule to solve meshes. The simulation of PV-buses is presented using the Newton–Raphson solution algorithm. The validation and comparison of results in different systems show the simplicity and low computations of the proposed method which make it time-saving and very efficient for large-scale DSs.

The use of Distributed Generators (DGs) in distribution system has increased at fast pace in recent times. These DGs can work both as grid connected or standalone mode. Thus when it comes to DG placement, getting the optimal location for its placement and the optimal sizing becomes very important. In this paper, finding the optimal location and optimal size of DGs is dealt keeping active power loss as the objective, considering different load models. A novel method called Backtracking Search Optimization Algorithm is used to find the most significant positions for DG placement. DGs supplying both active and reactive power have been studied. Case studies have been done about the effect of 1, 2 or 3 DGs on the IEEE 69 bus test system for DGs operating at 0.85 pf. on different load models.

With the rapid growth of new energy and flexible load, the random fluctuation of power system operation is enhanced, and the traditional voltage control scheme is limited. In view of the shortcomings of traditional reactive voltage control in matching the dual characteristics of the source and load in new power system, a multi-time scale coordinative strategy of reactive power and voltage control for frequent power flow fluctuation in new power system is proposed, and the reactive power and voltage control is carried out according to the normal and the unexpected large fluctuation of the power flow. The reactive power and voltage coordinated control mode of hour-minute level is used in the normal fluctuation of power flow. The timely adjustment of voltage deviation and the rapid suppression of voltage fluctuation are realized by MPC rolling optimization and dynamic-static reactive power resource substitution, and sufficient dynamic reactive power reserve is reserved for the system. The reactive power and voltage coordinated control mode of second level is used in the case of non-expected large fluctuation of power flow, and the fast decision-making ability of deep reinforcement learning realizes the rapid recovery of over-limit voltage. An example of a regional power grid in eastern China verifies the effectiveness of the proposed method.

One of the main concerns of utilities is to minimise voltage variations along their feeders when they enhance their networks by various distributed generation (DG) systems that have uncertainty in their output. Furthermore, such DG systems can provide reactive power to the grid. Thus, the objective of this study is to optimally allocate locations and capacities of DG systems, particularly photovoltaic systems in this study, on distribution networks that host DG inverters with the capability of reactive power control, in other words, Volt/Var management and control. For this purpose, this study proposes a hybrid method based on optimal reactive power control and genetic algorithms. The proposed method is verified in well‐known test feeders.

This paper proposes a decoupled power control algorithm for grid integration of photovoltaic (PV) systems using quasi-Z-source inverter (qZSI). The proposed controller uses model predictive control (MPC) framework to inject the maximum available power harvested from the PV panels to the grid and also to compensate reactive power required by the grid. Thus, a power electronics interface (PEI) is proposed to integrate the PV panels to the grid and also to work as a reactive power compensator simultaneously. A reliable technique is proposed to regulate the impedance network elements' voltage and current according to the maximum operating point of PV panels and grid voltage/current requirements. The proposed controller features simple structure for practical implementation, fast dynamic response under changing sky condition, and negligible tracking error in steady state condition for decoupled active and reactive power control in a typical distributed generation (DG) systems. The performance of the proposed controller is verified experimentally using dSPACE-DS1007 platform, and the grid-side power quality analysis is provided and evaluated according to IEEE-519 standard.

This paper presents a new framework to analyze the penetration of distributed generation (DG) in distribution systems (DS) based on modified Monte Carlo simulation. The placement and capacity of DG are generated as random variables with probability density functions following the optimality principle of the system. The method of power flows analysis is employed to evaluate the economic and technical aspect of the network both with and without DG sources inside. The results in different scenarios are combined with weighted factors to form the performance indices. The proposed framework is testified in a practical 15 MVA, 22 kV, 48-bus DS in Thai Nguyen, Vietnam. The simulation result shows that many advantages can be achieved with DG such as lower power losses, smaller voltage deviation, over-load reduction, etc. The proposed framework can serve as a platform for DS planning with DG sources in practice.

The interline power flow controller (IPFC & UPFC) is one of the latest generation flexible AC transmission systems (FACTS) controller used to control power flows of multiple transmission lines. The main objective of this paper is detailed study about a new real and reactive power coordination controller for a interline power flow controller (IPFC & UPFC). The basic control for the IPFC is such that the series converter of the UPFC controls the transmission line real/reactive power flow and the shunt converter of the (IPFC & UPFC) controls the bus voltage/shunt reactive power and the DC link capacitor voltage. Because of the common link, any inverter within the (IPFC & UPFC) is able to transfer real power to any other and thereby facilitate real power transfer among the lines of the transmission system. Since each inverter is able to provide reactive compensation, the (IPFC & UPFC) is able to carry out an overall real and reactive power compensation of the total transmission system. This capability makes it possible to equalize both real and reactive power flow between the lines, transfer power from overloaded to under loaded lines, compensate against reactive voltage drops and corresponding reactive line power and to increase the effectiveness of the compensating system against dynamic disturbances. A simulation in MATLAB has been done in order to extend conventional algorithm based on this model.

Voltage violations are the main problem faced in distribution networks (DN) with a higher penetration of inverter-based generations (IBG). Active and reactive power control from smart inverters (SI) can mitigate such violations. Optimal power flow (OPF)-based control provides more accurate operating set points for the coordinated operation of SIs. Therefore, this paper presents a three-phase OPF-based control on SI-enriched unbalanced distribution networks. To consider this, first three-phase model using the current injection model (CIM) is developed. Later, the optimal active and reactive power set points for SIs are obtained by solving a quasi-dynamic optimization problem. The uniqueness of the proposed method is that it regulates the voltage at the affected nodes by obtaining the optimal set points for the smart inverter. The OPF is implemented with a mathematical CIM in Pyomo and solved using the Knitro solver. The proposed method is compared with the sensitivity-based Volt-Var Control (VVC), Volt-Watt Control (VWC), and combined VVC and VWC methods. The effectiveness of the proposed method is verified in a European low-voltage and CIGRE medium-voltage distribution network with 100% penetration. The analysis shows that the OPF-based control optimizes with less network loss and can maintain voltage violations with less reactive power support.

Increase in the market share of wind energy in total electricity generation and its impact to power grid has imposed new challenges to the stability of each wind turbine generator (WTG) unit. In the case of power undersupply, the problem on voltage stability and voltage collapse will eventually occur. In this paper, the impact of reactive power control in improving the performance of squirrel cage induction generator-based (SCIG-based) WTGs is presented. In the asynchronous operation of induction machine, the increment of wind power generation is feasible by absorption of more reactive power. Increasing the reactive power consumption of induction generator results in reduction of voltage in the bus connected to the wind farm from the grid. In this scenario, inadequate reactive power control can lead to instability in the power network. The studies conducted in this paper are based on the quasi-static time-domain simulations (QSTDS) and continuation power flow (CPF) algorithm framework. The results obtained indicate that with increment of wind power penetration in a power system, adequate reactive power support is required to maintain stability, else the stable performance of the wind farm will be threatened and will lead to over-speeding of SCIGs. The use of SVC and STATCOM as a practical solution in improvement of wind farms-based power system stability is investigated and presented.

To manage the microgrid effectively, it is important to get the power information among multiple distributed generation (DG) units. However, when the droop control method is adopted, as the corresponding DG units cannot be simply modeled as VF or PQ buses, the conventional power flow algorithm may become inapplicable. To solve this issue, a time domain iteration (TDI) based power flow algorithm is hereby proposed. Firstly, a microgrid model is prepared, containing a network model and several DG unit models. Then, the proposed TDI is executed for power flow calculation, which mimics the real-time operation of microgrids. In each iteration, the DG unit models input voltages and currents to the network model; then the network model changes its state accordingly and feeds related parameters back to those DG unit models. As the DG unit models simulate the behavior of actual DG units, the proposed algorithm is not limited to the droop control governed microgrids. Moreover, as the TDI has definite physical meaning, convergence problems can be avoided. Finally, the validity of the proposed power flow algorithm is verified through the Matlab simulation results from an 8-bus microgrid system.

With the rise in electricity demand, various additional sources of generation, known as Distributed Generation (DG), have been introduced to boost the performance of power systems. A hybrid multi-objective Evolutionary Programming-Firefly Algorithm (MOEPFA) technique is presented in this study for solving multi-objective power system problems which are minimizing total active and reactive power losses and improving voltage profile while considering the cost of energy losses. This MOEPFA is developed by embedding Firefly Algorithm (FA) features into the conventional EP method. The analysis in this study considered DG with 4 different scenarios. Scenario 1 is the base case or without DG, scenario 2 is for DG with injected active power, scenario 3 is for DG injected with reactive power only and scenario 4 is for DG injected with both active and reactive power. The IEEE 69-bus test system is applied to validate the suggested technique.

This paper proposes the Black widow optimization algorithm (BWOA), a nature-inspired technique for the optimal allocation of a distributed generation (DG) in a 69-bus distribution system. The main aim of this paper is to reduce overall real power loss in distribution systems as much as possible. The effect of DG placement on total device reactive power loss, individual branch loadings, and voltage magnitude at each distribution bus is also investigated. The steady state power flow solutions are determined using load flow technique. In comparison to some of the other approaches listed in the study, the proposed BWOA achieves lower total active power loss.

In this study, an intelligent controlled distributed generator (DG) system is proposed for tracking control and islanding detection. First, a DC/AC inverter with DC power supply is adopted to emulate a DG system and control the active and reactive power outputs. Moreover, in order to comply with the standard for interconnection with the power grid, a novel active islanding detection method is proposed for the inverter-based DG system. In the proposed active islanding detection method, a perturbation signal is designed to inject into the d-axis current of the DG system which causes the frequency at the terminal of the RLC load to deviate when the power grid breaks down. The feasibility of the proposed active islanding detection method is verified according to the UL 1741 test configuration. Furthermore, in order to improve the tracking control of the active and reactive powers of the inverter-based DG system, and to effectively reduce the detection time of islanding phenomenon, two probabilistic fuzzy neural network (PFNN) controllers are adopted to take the place of the conventional proportional-integral (PI) controllers. In addition, the network structure and the online learning algorithm of the adopted PFNN are presented in details. Finally, some experimental results of the proposed active islanding detection method using PFNN controllers are proposed to validate the effectiveness and feasibility of the tracking control and islanding detection.

The escalating demand of reactive power consumption by the load in the grid connected system usually causes the following problems 1) Voltage sag and swell at the point of common coupling (PCC) 2) Harmonic distortion of the grid current 4) low power factor etc. More over, to meet the rising reactive power load demand, distributed generation (DG) is a viable option. For that, usually current regulated PWM voltage-source inverters (VSI) are used to inter face DG with utility grid in order to ensure the grid stability. In this paper, reactive power compensation for inverter interfaced DG system based on hysteresis with proportional integral (PI) controller is proposed along with independent control of active and reactive power of the grid. The hysteresis with PI controller can largely reduce the current harmonics at PCC considerably which ensures lower total harmonic distortion (THD) during reactive power load demand increases. The performance indices include THD of the grid current, fast current tracking during steady state and transient conditions. The studied system is modeled and simulated in the MATLAB Simulink environment. Further, an experimental work has been carried out in the laboratory set-up in the discrete-domain via TMS320F2812 digital signal processor (DSP) and we could find there is an effective validation with simulated results.

Comprehensive review of the requirements of AC transmission grid codes and the role of FACTS devices in integrating renewable power plants