System Voltage Profile Research Articles

Distributed secondary consensus fault tolerant control method for voltage and frequency restoration and power sharing control in multi-agent microgrid

This paper proposes a distributed secondary consensus fault-tolerant control (FTC) method for the multi-agent microgrid (MG). The proposed controller is applied to compensate for the errors in the system frequency and voltage profiles in the presence of MG faults. The proposed controller also enables the system to ensure an accurate sharing of the active and reactive power among the connected distributed generations (DGs) in MG. The consensus-based controller depends on the information transferring between MG neighbor agents through a graph communication network. The proposed secondary controller improves the primary controllers' performance, including droop control and inner voltage and current controllers. The proposed controller has been verified using a hypothetical multi-agent MG system in MATLAB/Simulink environment. A comparative analysis between the results obtained from applying the proposed controller and the primary droop control method (DCM). The proposed controller's performance is evaluated using the controller response time, the maximum frequency deviation, and the steady-state restoration time. The results show the proposed secondary FTC method's effectiveness in mitigating the faults' effect in multi-agent MG.

Impact of installing renewable energy sources on a small-scale power network in the Caribbean

Many small island states in the Caribbean like Antigua and Barbuda depend heavily on petroleum-based products for power generation. Given the fluctuating oil prices, there is now an urgent push for increased energy security. Antigua is one of the fastest-growing islands for grid-connected Renewable Energy Sources (RES). Whilst the increase in grid-connected RES improves the islands’ energy security, and it is equally important to understand the impact that RES have on the network’s reliability and security. Thus, a base case model of the power network was built, and the following areas were analysed: load flow, contingency analysis, and fault analysis. The Antigua Public Utilities Authority (APUA) 69kV power network is used as a case study for this project. PowerWorld and Homer Energy software have been used to simulate and model the grid. Results from the project show that RES changes the power flow and could help to improve the system voltage profile if placed correctly. Whilst increased penetration of Wind Turbine Generators (WTG) on the grid increases the system fault levels, they also play a key role in active and reactive power control. This means that the APUA network must be more flexible, and system operators must have network visibility to react to changes on the network. The aim of this paper is to investigate the impact that RES (in particular, wind and solar PV) has on the operational, security, or reliability of a small-scale power network.

Particle Swarm Optimization for Optimal Allocation of STATCOM on Transmission Network

Static Synchronous Compensator (STATCOM) is one of the members of flexible alternating current transmission systems (FACTS) devices that controls one or more network parameters to increase system power transfer capability. However, it needs be optimally allocated to fully maximize its usage. Allocation of STATCOM simply refers to optimal placement and size of a STATCOM to solve some of the transmission network problems. This paper therefore utilizes particle swarm optimization (PSO) to allocate STATCOM to enhance the system voltage magnitudes and minimize the active power loss. A Matlab programme was developed for the proposed method and applied to IEEE 14 bus network and the results presented. The results showed that the total active power loss was reduced by 6.90%. The voltage magnitudes at buses 7 and 13, which were above the upper voltage limit, were reduced and brought to within acceptable voltage limits and hence improvement in the system voltage profile. Therefore, the optimal allocation of STATCOM improves the efficiency and operation of the network.

Analysis of interconnected configuration for penetration of distributed generation

This paper visualizes the feasibility of the proposed interconnected distributed power system configuration, which aims at incorporating the electricity generation from renewables and to cater to low voltage areas of radial distribution network. The shortcoming of existing traditional radial systems is inconsistent load distribution and technical viability in incorporating renewable sources without disturbing the power system. Sustainable development is achieved with improvement in the prevailing distribution system. Maximum potential benefits in terms of demand-supply balance and integrating renewables can be achieved by selecting properly placed and optimally sized distributed generation sources in a distribution network. The generation facility is selected as per the geographical profile of the location and placed on the weakest node. The weakest node is the low voltage profile region where the maximum output of the integration of power sources is beneficial. In this paper, the ZIP model-based methodology is applied to feeder loads on the data set of the distribution grid of the National University of Science & Technology (NUST), Islamabad, Pakistan. The comparative analysis is performed on a radial network of NUST distribution grid and compared with a simulated interconnected distribution system of the same distribution network on MATLAB software as a case study to observe the performance of interconnected power systems. This analysis results in better voltage profiles for interconnected networks, compared to radial networks. That said, incorporating a Distributed Generation (DG) source in the interconnected network builds a substantial impact on the distribution system voltage profile. The efficacy of the proposed interconnected system confirms the performance improvement of the distribution power system. The VSI values for interconnected systems give better results which is further justified by the machine learning algorithm, Logistic regression. The simulation results indicate that the Interconnected system encourages penetrations of solar, wind, gas turbine, and other renewable sources near the low voltage end in the distribution system. © 2021 Bilal Asghar Farooqi et al.

Improving Power Quality and Mitigation of Harmonic Distortion Impact at Photovoltaic Electric Vehicle Charging System

This article offers a clear and realistic design for an active power filter to increase reliability and power quality of the photovoltaic charging system and a high-penetration electric vehicle distribution system. The MOPSO algorithm is used as the basis for problems with optimization and filter tuning. A typical regular load curve is used to model the warped power grid over a 24-hour cycle to estimate the total harmonic distortion (THD). For structures with high penetration of electric cars, the probability of minimizing THD (for example to five percent) is explored via optimum capacity active shunt filters and shunt capacitors. To maximize general performance of the charging system, the switching systems are re-scheduled. Moreover, to increase the current control accuracy of shunt active filter, the fuzzy logic controller is utilized. The major drawback to new system is that it would have unrestricted billing for entire day to cope with voltage interruption. In MATLAB / SIMULINK, detailed machine setup and control algorithm experiments are simulated. The simulation findings confirm the efficiency and viability of projected shunt active filter to enhance voltage profile and track power performance of photovoltaic charging system.

Leveraging a Genetic Algorithm for the Optimal Placement of Distributed Generation and the Need for Energy Management Strategies Using a Fuzzy Inference System

With the rising load demand and power losses, the equipment in the utility network often operates close to its marginal limits, creating a dire need for the installation of new Distributed Generators (DGs). Their proper placement is one of the prerequisites for fully achieving the benefits; otherwise, this may result in the worsening of their performance. This could even lead to further deterioration if an effective Energy Management System (EMS) is not installed. Firstly, addressing these issues, this research exploits a Genetic Algorithm (GA) for the proper placement of new DGs in a distribution system. This approach is based on the system losses, voltage profiles, and phase angle jump variations. Secondly, the energy management models are designed using a fuzzy inference system. The models are then analyzed under heavy loading and fault conditions. This research is conducted on a six bus radial test system in a simulated environment together with a real-time Power Hardware-In-the-Loop (PHIL) setup. It is concluded that the optimal placement of a 3.33 MVA synchronous DG is near the load center, and the robustness of the proposed EMS is proven by mitigating the distinct contingencies within the approximately 2.5 cycles of the operating period.

Comprehensive analysis of distributed energy resource penetration and placement using probabilistic framework

Integration of distributed energy resources (DERs) affect system performance in multitude of ways such as reliability, losses and voltage profile. Thus, increasing distributed energy resource penetration necessitates impact assessment particularly when DERs comprise of stochastic RES based distributed generators (DGs) and storage system. This paper presents a formulation for the analysis of DER penetration and placement on system losses and voltage profile in probabilistic framework. Penetration level has been defined, giving due consideration to stochastic behaviour of RES based distributed generators. The work presented incorporates analysis and consideration of two important factors in placement problem, that is, intermittent nature of RES based distributed generators and dual nature of storage units. In order to account for uncertainties inherently present in RES, probabilistic load flow has been used in this work. Placement problem is solved for three different penetration levels, that is, 20%, 40% and 60% using utterfly particle swarm optimisation. The impact of seasonal effect on system losses and voltage profile in correlation with penetration levels has also been investigated. Results provide useful insights for identification of optimum penetration level.

An Efficient Mathematical Model for Distribution System Reconfiguration Using AMPL

Distribution network is an essential part of electric power system, which however has higher power losses than transmission system. Distribution losses directly affect the operational cost of the system. Therefore, power loss reduction in distribution network is very important for distribution system users and connected customers. One of the commonly used ways for reducing losses is distribution system reconfiguration (DSR). In this process, configuration of distribution network changes by opening and closing sectional and tie switches in order to achieve the lowest level of power losses, while the network has to maintain its radial configuration and nodal voltage limits, and supply all connected loads. The DSR aiming loss reduction is a complex mixed-integer optimization problem with a quadratic term of power losses in the objective function and a set of linear and non-linear constraints. Accordingly, distribution network researchers have dedicated their efforts to developing efficient models and methodologies in order to find optimal solutions for loss reduction via DSR. In this paper, an efficient mathematical model for loss minimization in distribution network reconfiguration considering the system voltage profile is presented. The model can be solved by commercially available solvers. In the paper, the proposed model is applied to several test systems and real distribution networks showing its high efficiency and effectiveness for distribution systems reconfiguration.

Techno-Economic Analysis of Increasing PV-Wind based DG Penetration in Sub-Transmission System

This paper deals with techno-economic impact of increasing photovoltaic and wind power distributed generation in sub-transmission system. This paper suggests a new approach to interpret a multi-objective problem of integrating different types of distributed generation using an improved elephant herding optimization method. The main aim of this paper is to minimize the power losses and elevate the voltage profile of the electrical system. The effectiveness of improved elephant herding optimization had been tested on IEEE 30 bus sub-transmission system and is compared with results obtained with Particle Swarm Optimization method. In this paper, three cases have been considered where different types of distributed generation are integrated into the system and the best results have been obtained for case 3 where both photovoltaic and wind power are penetrated in system network. The optimal solutions obtained are compared with particle swarm optimisation and base case. The comparison shows that the proposed optimization method is favourable. The economic analysis of the corresponding distributed generation has been presented in this paper.

Improving the Voltage Quality and Power Transfer Capability of Transmission System Using FACTS Controller

One of the main challenges of the future in the utility sector is constructing the new transmission line corridor. This is due to the fact that land compensation cost associated with the expansion of a new transmission line corridor becomes very expensive and also power transmission efficency is very low. In addition to that, the high carbon emission, which is the major challenge of the world right now, related to the additional conventional energy-based power generation to meet dramatically increased electricity demand and the volatility nature of the existing transmission networks are some of the main drivers to implement FACTS controller in transmission network for flexible, reliable, efficient and stable power transmission. This study accounts modeling of static VAR compensator (SVC), static synchronous compensator (STATCOM), unified power flow controller (UPFC) in a 5-bus transmission system to enhance transmission efficency and the quality of power supplied to the costomer. FACTS devices for improving the transmission line capacity and voltage profile of the power system. The three FACTS controllers are modeled for the standard 5 bus IEEE system based on Newton Raphson algorithm using NEPLAN simulation software in order to investigate their impacts on transmission line capacity and voltage profile improvement. Based on the simulation result, the voltage profile as well as the capacity of the IEEE 5 bus system is improved well by using each of the FACTS controller. From the simulation result we can conclude that the STATCOM and SVC are very efficent in voltge profile improvement whereas the UPFC is well performed for the power transmission capability of the transmission network.

Optimal Allocation of a Hybrid Wind Energy-Fuel Cell System Using Different Optimization Techniques in the Egyptian Distribution Network

This paper presents an optimal proposed allocating procedure for hybrid wind energy combined with proton exchange membrane fuel cell (WE/PEMFC) system to improve the operation performance of the electrical distribution system (EDS). Egypt has an excellent wind regime with wind speeds of about 10 m/s at many areas. The disadvantage of wind energy is its seasonal variations. So, if wind power is to supply a significant portion of the demand, either backup power or electrical energy storage (EES) system is needed to ensure that loads will be supplied in reliable way. So, the hybrid WE/PEMFC system is designed to completely supply a part of the Egyptian distribution system, in attempt to isolate it from the grid. However, the optimal allocation of the hybrid units is obtained, in order to enhance their benefits in the distribution networks. The critical buses that are necessary to install the hybrid WE/ PEMFC system, are chosen using sensitivity analysis. Then, the binary Crow search algorithm (BCSA), discrete Jaya algorithm (DJA) and binary particle swarm optimization (BPSO) techniques are proposed to determine the optimal operation of power systems using single and multi-objective functions (SOF/MOF). Then, the results of the three optimization techniques are compared with each other. Three sensitivity factors are employed in this paper, which are voltage sensitivity factor (VSF), active losses sensitivity factor (ALSF) and reactive losses sensitivity factor (RLSF). The effects of the sensitivity factors (SFs) on the SOF/MOF are studied. The improvement of voltage profile and minimizing active and reactive power losses of the EDS are considered as objective functions. Backward/forward sweep (BFS) method is used for the load flow calculations. The system load demand is predicted up to year 2022 for Mersi-Matrouh City as a part of Egyptian distribution network, and the design of the hybrid WE/PEMFC system is applied. The PEMFC system is designed considering simplified mathematical expressions. The economics of operation of both WE and PEMFC system are also presented. The results prove the capability of the proposed procedure to find the optimal allocation for the hybrid WE/PEMFC system to improve the system voltage profile and to minimize both active and reactive power losses for the EDS of Mersi-Matrough City.

Congestion management with improved real power transfer using TCSC in 30 bus system

Secure operation and reliable utilisation of transmission lines is a challenging issue in deregulated power system. The scheduled power transactions are difficult due to the overloading of transmission lines in restructured power system as the electricity market has become more competitive. Due to congestion of transmission lines, the transfer of real power and the power system voltage profile are greatly affected in the power system. The aim of this research work is to increase the real power and the reactive power flowing in the lines of multibus system using thyristor controlled series compensator (TCSC). Real power transfer with reduced losses and improved voltage stability is an important factor in the present global scenario. This paper deals with the improvement of power flow in power transmission lines by series compensation device in 30 bus system with reduced congestion. The 30 bus system without and with thyristor controlled series compensation device (TCSC) is modelled and simulated and the results are presented. The simulation studies indicate a significant improvement in the real and the reactive power flow with the introduction of TCSC. The advantages of the proposed system include the smooth variations of the real and the reactive powers.

Optimal planning of RDGs in electrical distribution networks using hybrid SAPSO algorithm

The impact of the renewable distributed generations (RDGs), such as photovoltaic (PV) and wind turbine (WT) systems can be positive or negative on the system, based on the location and size of the DG. So, the correct location and size of DG in the distribution network remain an obstacle to achieving their full possible benefits. Therefore, the future distribution networks with the high penetration of DG power must be planned and operated to improve their efficiency. Thus, this paper presents a new methodology for integrated of renewable energy-based DG units with electrical distribution network. Since the main objective of the proposed methodology is to reduce the power losses and improve the voltage profile of the radial distribution system (RDS). In this regard, the optimization problem was formulated using loss sensitivity factor (LSF), simulated annealing (SA), particle swarm optimization (PSO) and a combination of loss sensitivity index (LSI) with SA & PSO (LSISA, LSIPSO) respectively. This paper contributes a new methodology SAPSO, which prevents the defects of SA & PSO. Optimal placement and sizing of renewable energy-based DG tested on 33-bus system. The results demonstrate the reliability and robustness of the proposed SAPSO algorithm to find the near-optimal position and size of the DG units to mitigate the power losses and improve the radial distribution system's voltage profile.

Multi-objective Pareto based Optimal Placement and Sizing of Solar PV and Wind Generation System

Appropriate placement and sizing of distributed generation is required for reducing power loss and improvement in voltage profile of power system. Solar photovoltaic (PV) and wind energy are two prominent sources of distributed generation. In this paper, the authors propose a novel method to analyze the optimal placement and sizing of the solar PV and wind generation system in a radial distribution system. A multi objective function is selected for optimal siting and sizing. A 33-bus distribution system has been considered for testing the developed algorithm. Optimal location is obtained by placing DG source at each bus and satisfying objective function. Jaya algorithm is implemented for optimal sizing of PV and wind system. Also the system has been analyzed by placing the solar PV and Wind generation system independently and then simultaneously.

An Optimal Phase Arrangement of Distribution Transformers under Risk Assessment

This paper presents a phase arrangement procedure for distribution transformers to improve system unbalance and voltage profile of distribution systems, while considering the location and uncertainties of the wind turbine (WT) and photovoltaics (PV). Based on historical data, the Monte Carlo method is used to calculate the power generation value-at-risk (VAR) of WTs/PVs installed under a given level of confidence. The main target of this paper is to reduce the line loss and unbalance factor during 24-hour intervals. Assessing the various confidence levels of risk, a feasible particle swarm optimization (FPSO) is proposed to solve the optimal location of WTs/PVs installed and transformer load arrangement. A three-phase power flow with equivalent current injection (ECI) is analyzed to demonstrate the operating efficiency of the FPSO in a Taipower feeder. Simulation results will support the planner in the proper location of WTs/PVs installed to reduce system losses and maintain the voltage profile. They can also provide more risk information for handing uncertainties when the renewable energy is connected to the distribution system.

Optimal location and capacity of DG systems in distribution network using genetic algorithm

The assimilation of distributed generators (DG) does play a critical role in modern distribution networks. Due to increasing demand for electrical energy, the DG sources are becoming more significant in distribution systems. The position and size of DG units will have an impact on losses and voltage profile of the distribution system. This work proposes implementing the Genetic Algorithm approach to determine the optimal site as well as the size of DG units in the distribution network to mitigate actual power losses and enhance the voltage profile. The optimal position and optimal capacity of DG unit is computed by GA algorithm and by using three indices namely PLRI, VDI and MORI we determine three solutions one for exclusively reduction in system loss, the second one for improvement of voltage profile and third one for combined benefit in minimization of losses and improved performance of the bus voltages, the proposed method is applied to the IEEE-33 bus test system. The programming is executed in the software MATLAB 2018α.

Optimal sizing and placement of multiple renewable distribution generation and DSTATCOM in radial distribution systems using hybrid lightning search algorithm‐simplex method optimization algorithm

AbstractIn this literature, the simultaneous placement of both the Renewable Distribution Generation (DG) and Distribution STATCOM (DSTATCOM) in the Radial Distribution System (RDS) for Power Loss Minimization (PLM) is discussed. Loss Sensitivity Factor (LSF) is initially applied to discover the candidate location of DG and DSTATCOM in RDS. The effective Hybrid Lightning Search Algorithm‐Simplex Method (LSA‐SM) is used to compute the optimal sizing of DG and D‐STATCOM. The performance of the proposed method is tested separately on both IEEE33 and IEEE69 RDS test systems. The improvement in system Voltage Profile and operational stability before and after the allocation of DG and DSTATCOM is discussed. The improved system Voltage Stability Index values for different cases are plotted. The performance of the proposed method is compared with similar existing methods.

Voltage control using smart transformer via dynamic optimal setpoints and limit tolerance in a residential distribution network with PV sources

Uncertainities and variations of power generation through photovoltaic (PV) sources are major challenges for their integration with the distribution grid. Voltage rise and voltage drop issues limit the increase in PV penetration and loading levels, respectively. Moreover, it is important to maintain voltage levels as per grid code while ensuring that the PV power generation is not curtailed. In this paper, a voltage control method using smart transformer (ST) via dynamic optimal setpoints and limit tolerance is proposed in a residential distribution network. Performance indicators are developed to understand the impact of the proposed method on the system voltage profile. A method to determine the optimal inputs for voltage control methods depending on the day-ahead predictions of load demand and PV power profiles is developed. Further, a voltage control method of switching among three setpoints based on the voltage that determines the load side ac reference voltages for ST is proposed. The proposed method is compared with the method of switching between two setpoints based on current. The proposed method provides an improved voltage profile in the distribution network, which is tested on a CIGRE low voltage residential distribution network using PSCAD

Localización óptima de plantas virtuales de generación en sistemas eléctricos de potencia basados en flujos óptimos de potencia

El presente trabajo determina la ubicación óptima de plantas virtuales de generación analizando el comportamiento en estado estacionario del sistema, la planta virtual de generación combina una amplia variedad de recursos energéticos distribuidos y los opera como un sistema unificado. Se identificará la localización óptima de plantas virtuales de generación para mejorar el perfil de tensión nodal del sistema de potencia basado en flujos óptimos de potencia de corriente directa con restricciones económicas. El análisis de sistema eléctrico se realiza mediante flujos óptimos de potencia de corriente continua basado en programación lineal entera mixta respetando restricciones económicas, ambientales, cargabilidad de las líneas de transmisión, el manejo de las demandas, nivel de sobrecarga, desviación angular y perfil de tensión. Se realiza una revisión literaria plantas virtuales de generación la cual tiene una serie de ventajas competitivas como el uso de tecnologías renovables y de alta eficiencia energética. También dispone de información para el desarrollo del flujo óptimo de corriente continua.

Allocation of PV unit in Distribution Network using Analytical Method

Inappropriate selection of location and corresponding size of Distributed Generator (DGs) in electrical network may have increased power losses in the system. Application of incorporating DG in system has eased the problem of high power losses, voltage stability, low reliability and poor power quality. This paper suggests a simple and efficient load flow technique known as direct load flow method to find the optimal allocation of Type-3 DG in the distribution system. The presented method was developed and tested in two distribution networks with varying size and complexities and the effect of size and location of DG with respect to real power losses while maintaining the voltage profile of system within limits is examined with verification and discussed in detail.