This paper presents a new approach for estimating and improving voltage stability margin from phase and magnitude profiles of bus voltages using sensitivity analysis of Voltage Stability Assessment Neural Network (VSANN). Bus voltage profile contains useful information about system stability margin including the effect of loadgeneration pattern, line outage and reactive power compensation, so it is adopted as input pattern of VSANN. In fact, VSANN establishes a functionality for VSM with respect to voltage profile. Sensitivity analysis of VSM with respect to voltage profile and reactive power compensation extracted from information stored in the weighting factor of VSANN is the most dominant feature of the proposed approach. Sensitivity of VSM helps one to select the most effective buses for reactive power compensation aimed enhancing VSM. The proposed approach has been applied to IEEE 39-bus test system which demonstrated applicability of the proposed approach.

Improving reliability indices, increasing the grid production capacity, reducing power loss during peak periods and fuel cost, and economic and environmental considerations on the one hand, and the progresses made in the field of semiconductor devices on the other hand, are some of the factors that increase the penetration of the renewable energy sources to the distributed network. When the photovoltaic panels are present at the level of the distribution network, there are periods of time when the voltage exceeds its allowable area. Regarding this issue, it is necessary to consider solutions to overcome this challenge. This paper suggests an online dynamic voltage restorer whose control algorithm is designed according to the genetic algorithm. The simulations are carried out according to the voltage profile of a part of Mashhad. They have been investigated by DIgSILENT software. For this purpose, the real data of energy consumption in the residential sector with a time step of one hour has been used and the simulations have been implemented in the form of three scenarios. The first scenario is when there is no solar cell. The second is when the solar cell is online. And the third state is when both the cell and the dynamic voltage recovery in the line help the stability of the system and improve its power quality. According to the obtained results, by applying the mentioned control method, not only more than 7% of the range of voltage variations is reduced, but by reducing the level of voltage imbalance, the level of efficiency and reliability of the network is also increased.

In a de-regulated open access environment, reactive power is one of the ancillary services which must be provided by an Independent System Operator (ISO). In this paper, a new algorithm is proposed in which reactive power resources areinitially so tuned that optimum security in terms of voltage profile and voltage stability are achieved while at the same time, the system losses are minimized. The resulting optimization case is solved as an Extended Multi-objective Optimal Power Flow (EMOPF) problem using Lexico Graphic Method (LGM). Thereafter, using the concept of Fair Resource Allocation (FRA), the reactive powers generated are distributed among existing transactions so that the costs incurred are properly and fairly recovered. The algorithm is successfully tested on a typical power system.

In this paper, a distributed method for reactive power management in a distribution system has been presented. The proposed method focuses on the voltage rise where the distribution systems are equipped with a considerable number of photovoltaic units. This paper proposes the alternating direction method of multipliers (ADMMs) approach for solving the optimal voltage control problem in a distributed manner in a distribution system with high penetration of PVs. Also, the proposed method uses a clustering approach to divide the network into partitions based on the coupling degrees among different node. The optimal reactive power control strategy is conducted in each partition and integrated using ADMM. The proposed method is tested on a real distribution test system. The result evidence that the proposed method has used the lower reactive power if compared to the conventional method.

Improving transient voltage stability is one of the most important issues that must be provided by doubly fed induction generator (DFIG)-based wind farms (WFs) according to the grid code requirement. This paper proposes adjusted DC-link chopper based passive voltage compensator and modified transient voltage controller (MTVC) based active voltage compensator for improving transient voltage stability. MTVC is a controller-based approach, in which by following a voltage dip (VD) condition, the voltage stability for the WF can be improved. In this approach, a voltage dip index (VDI) is proposed to activate/deactivate the control strategy, in which, two threshold values are used. In the active mode, the active and reactive power are changed to decrease the rotor current and boost the PCC voltage, respectively. Based on the control strategy, in a faulty grid, DFIG not only will be able to smooth DC-link voltage fluctuations and reduces rotor overcurrents but also it will increase the voltage of point of common coupling (PCC). Therefore, it improves transient voltage stability. The simulation results show the effectiveness of the proposed strategy for improving voltage stability in the DFIG.

Daring recent years, voltage stability has received attention in literarure. Reactive power resources while influencing voltage Stability, affect voltage profile A the grid. In this paper, a new approach based on Genetic Algorithm is proposed in which proper rective resources are allocated throughout the system so that both voltage profile and stability are optimized. Due to their important effects, optimal allocation of ULTC'S are also considered

Distributed Generations (DGs) are utilized to supply the active and reactive power in the transmission and distribution systems. These types of power sources have many benefits such as power quality enhancement, voltage deviation reduction, power loss reduction, load shedding reduction, reliability improvement, etc. In order to reach the above benefits, the optimal placement and sizing of DG is significant. In this regard, this paper gets use of the Bacteria Foraging Algorithm (BFA) and Binary Genetic Algorithm (BGA) to investigate the DG placement with the purpose of power loss and voltage deviation reduction. The proposed method is applied on the 33-bus and 69-bus IEEE test systems and the optimal place and size of DGs from the power losses and voltage deviation minimization are assessed. Also, the performance of the above two algorithms are compared with each other.

The use of photovoltaic-static compensators (PV-STATCOM) to improve the system voltage profile has recently received much attention. This paper proposes coordinated control of multiple PV-STATCOM systems using fuzzy logic. The main feature of the proposed controller is that it can be operated in different modes: full-PV, partial-STATCOM and full-STATCOM in both capacitive and inductive compensation. In this strategy, when a disturbance occurs, depending on its severity, one or more PV-STATCOM systems go to the partial-STATCOM or full-STATCOM modes to optimize the reactive power compensation at the load bus. Then, after fixing the problem, the system returns to the full-PV power generation mode. To evaluate the system performance, different operating conditions were simulated with EMTDC/PSCAD software. The results confirm that the proposed fuzzy controller can improve the voltage profile dynamics.

Considering the significant role of electrical energy in economic and social development, as well as the substantial investments in the power industry, particularly in distribution networks, practical strategies to reduce losses and enhance the efficiency of existing facilities are essential. This paper investigates and compares the impact of all available methods on loss reduction and voltage profile improvement from both technical and economic perspectives on a real network. Additionally, to achieve more accurate results, the uncertainties in distributed generation resources and network loads are accounted for using scenario generation methods. The study evaluates all possible methods to determine the optimal location and capacity of equipment as the problem-solving algorithm. Load forecasting is incorporated to assess the effectiveness of the proposed methods for future years. Furthermore, a novel idea of reactive power injection by a solar power plant is considered and compared with the case of a solar power plant without reactive power injection. The proposed methods are simulated on five real high-loss distribution feeders in Iran using DIgSILENT software and Python programming. The simulation results indicate that the optimal placement of a solar power plant with reactive power injection provides the best technical performance, while capacitor placement offers the highest economic efficiency.