Efficiency Enhancement of the Electrical Distribution Networks by Different Techniques

The analysis of the conducted studies of the operation of high-voltage power lines (LEP) showed that the maximum power losses per corona are characteristic of increased voltages on high-voltage power lines with their low load, as well as in bad weather. Thus, a 5% increase in voltage at low line load leads to an increase in power losses per corona up to 30%. When it rains, power losses per corona for a 330 kV transmission line increase by 10 times compared to losses in good weather, for a 500 kV transmission line, the increase in losses is 12 times, and for a 750 kV transmission line - 13 times. During frost, the maximum power losses per crown are observed, which for a 330 kV transmission line increase by 23 times compared to losses in good weather, for a 500 kV transmission line, the increase in losses is 25 times, and for a 750 kV transmission line - 21 times. It should be noted that deterioration of weather conditions, in which there is an increase in corona power losses, is observed for more than 20% of the entire period of operation of the transmission lines during the year. Under such conditions, more than 80% of the total power losses per corona in the transmission line occur. The development and implementation of organizational and technical measures aimed at reducing power losses at the crown of power lines is an important practical task, the solution of which will contribute to increasing the efficiency of the electrical networks of Ukraine. Studying the possibility of influencing the amount of power losses due to the use of modern wire designs is an urgent task at the stage of designing power lines. The use of innovative brands of wires can lead to an increase in power losses per corona, due to their design features. Heat-shrinking films can be used to apply an insulating layer to sections of power lines, which will prevent corona and reduce losses associated with it. It is necessary to study the distribution of electric field strength along the span of the transmission line to determine the quantitative indicators of power losses per corona

The continuous increase in power demand and huge power losses in modern power systems have been a growing concern to power utilities. Such phenomenon often results in epileptic power supply, power system instability, supply fluctuations and security problems in many parts of the globe. Identification of suitable places for the installation of reactive power compensators to minimize voltage drop and system power losses in a power system becomes imperative. In this paper, the Newton-Raphson iterative method was used for the power flow solution of the 28 bus Nigerian 330KV grid system. The Generalized Unified Power flow Controller (GUPFC) is installed at identified weak load buses of the Nigerian 28-bus power system to reduce the losses and voltage drop of the system. A comparative analysis of the GUPFC with Load Tap Changing Transformers (LTCT) is also performed. Result obtained shows that the GUPFC can largely (effectively) improve the system power stability and selectively balance the power flow of multi-lines power flows when placed at identified weak buses compared with LTCT. Thus, GUPFC can be used to reduce overall power losses along transmission lines as well as improve stability overall reliability of the power grid system.

Distribution Electric power system is the largest and the most complex system made by the mankind. The distribution network power system is being encountered by quickly rising load demand and it is detected that under certain critical loading circumstances, the distribution system poses maximum power losses and poor voltage profile and collapse in convinced areas. To overcome these problems integrating distributed generation (DGs) on the grid near to the load center is the better solution as compared to others. Though, for the DG to serve its purpose, its location and size have to be determined optimally. In this paper, Grid-Based Multi-Objective Harmony Search Algorithm (GrMHSA) has been utilized to determine the size and location of DG in the distribution system in Debre Markos town. By placing DG optimally, in addition to the reduction of the power loss in the distribution network, the proposed mechanism improves the node (bus) voltage profile of the system under consideration. A MATLAB program is developed to mitigate power losses and improve the voltage profile by optimally sizing and placing a DG in the distribution network. After sizing and placing the DG in the network, the total voltage deviation, active and reactive power losses are reduced by 93.42%, 81.63% and 82.45% for Debre Markos Feeder 3 and 85.20%, 84.94% and 85.73% for Debre Markos Feeder 4 respectively. The performance comparison of GrMHSA and MOPSO has been made and GrMHSA has been found better in terms of reducing voltage deviation and power losses in the system.

Nowadays, the electrical power system has become a more complex, interconnected network that is expanding every day. Hence, the power system faces many problems such as increasing power losses, voltage deviation, line overloads, etc. The optimization of real and reactive power due to the installation of energy resources at appropriate buses can minimize the losses and improve the voltage profile, especially for congested networks. As a result, the optimal distributed generation allocation (ODGA) problem is considered a more proper tool for the processes of planning and operation of power systems due to the power grid changes expeditiously based on the type and penetration level of renewable energy sources (RESs). This paper modifies the AO using a quasi-oppositional-based learning operator to address this problem and reduce the burden on the primary grid, making the grid more resilient. To demonstrate the effectiveness of the MAO, the authors first test the algorithm performance on twenty-three competitions on evolutionary computation benchmark functions, considering different dimensions. In addition, the modified Aquila optimizer (MAO) is applied to tackle the optimal distributed generation allocation (ODGA) problem. The proposed ODGA methodology presented in this paper has a multi-objective function that comprises decreasing power loss and total voltage deviation in a distribution system while keeping the system operating and security restrictions in mind. Many publications investigated the effect of expanding the number of DGs, whereas others found out the influence of DG types. Here, this paper examines the effects of different types and capacities of DG units at the same time. The proposed approach is tested on the IEEE 33-bus in different cases with several multiple DG types, including multi-objectives. The obtained simulation results are compared to the Aquila optimizer, particle swarm optimization algorithm, and trader-inspired algorithm. According to the comparison, the suggested approach provides a superior solution for the ODGA problem with faster convergence in the DNs.

Guest Editorial

Power loss reduction, improvement of voltage profile, system reliability and system security are the important objectives that motivated researchers to use custom power devices/FACTS devices in power systems. The existing power quality problems such as power losses, voltage instability, voltage profile problem, load ability issues, energy losses, reliability problems etc. are caused due to continuous load growth and outage of components. The significant qualities of custom power devices /FACTS devices such as power loss reduction, improvement of voltage profile, system reliability and system security have motivated researchers in this area and to implement these devices in power system. The optimal placement and sizing of these devices are determined based on economical viability, required quality, reliability and availability. In published literatures, different algorithms are implemented for optimal placement of these devices based on different conditions. In this paper, the published literatures on this field are comprehensively reviewed and elaborate comparison of various algorithms is compared. The inference of this extensive comparative analysis is presented. In this research, Meta heuristic methods and sensitive index methods are used for determining the optimal location and sizing of custom power devices/FACTS devices. The combination of these two methods are also implemented and presented.

According to the actual requirements, it is necessary to design a line connecting the 150MW hydropower station and the 230KV hydropower station. The first is to plan the overall process of the project, by consulting the data, objectively evaluating the transmission line parameters, combining Matlab and Excel to calculate the transmission line parameters, including barrier current calculation and safety analysis, and finally combining power system simulation and cost calculation, the only one is selected from hundreds of scenarios. Rationale, power flow analysis, and power loss analysis are used to evaluate transmission lines, including series reactors and new transmission lines in parallel. The process reflects the continuous refinement of the initial design to create a transmission line that is both economical and safe.

In modern power system we are very much concern about the power quality of the existing network, i.e. generating ends, distribution ends and consumer end. Now a day’s power congestion in generation end i.e. transmission line can be control by using FACTs devices, DGs placements. To manage congestion in distribution system, implementing these conventional methods, become challenging task. In simple word, Congestion happens due to shortage of production which is overcome by DG placements and in some case due to transmission network failure, can be overcome by using FACTs devices. But that needs proper identification of congested line or nodes. It is also shown that problem solving at the point of occurrence is effective as well as economic. So it becomes necessary to control the congestion in distribution line of the power system. This paper is based on DG placement in congested node of distribution system with the help of forward backward sweep method and Sensitivity factor (LSg). In modified IEEE 33 bus distribution sys power loss at each bus is mathematically calculated by FB sweep method and also compared with simulated data depending on these LSg is calculated to identify the congested line then placing DGs to overcome the critical situation.

This paper examines the impact of a unified power flow controller (UPFC) on power system reliability. The UPFC is employed in the system to adjust the natural power sharing of two different parallel transmission lines and therefore enable the maximum transmission capacity to be utilized. The results of the investigations show a significant improvement in the system reliability by utilizing the UPFC. The improvement is measured using three reliability risk indices, namely, the loss of load expectation (LOLE), the loss of energy expectation (LOEE), and the system minutes (SM). The paper also presents a comparison between the effects of the UPFC and a thyristor controlled series capacitor on the system reliability.

When asymmetric longitudinal fault occurs in parallel transmission lines, the shift of load current and mutual inductance may produce large zero-sequence current in the healthy line, leading to the improper operation of pilot zero-sequence directional component with voltage compensation. This paper takes four parallel transmission lines under different voltage levels as research object, analyzing the zero-sequence fault characteristics and pilot zero-sequence directional protection performance in longitudinal fault, considering the influence of the potential transformer position, the electrical connection between different lines, the zero-sequence impedance of systems, and the partial coupling effect. Then the improper operation mechanism of pilot zero-sequence directional protection in the healthy line, which has a strong or weak electrical connection with the faulty line, is presented respectively. Moreover, potential solutions based on negative-sequence components, transmission power and smart substation are proposed.

Ensuring the provision of high-quality and dependable power supply to customers stands as a paramount responsibility within the realm of power systems. The concept of restructuring the power system emerges as an efficient approach to deliver economically viable and uninterrupted power supply. The assessment of power system reliability hinges on various factors, with the reliability index serving as a pivotal metric, dependent on both system security and adequacy. To enhance the reliability index, strategically locating FACTS devices becomes essential, a task facilitated through power flow analysis with specified constraints, pinpointing the weakest points through Genetic Algorithm-driven fast-acting device placement. The correlation between DG establishment and the reliability index was meticulously calculated, further bolstered by the introduction of a Derated Forced Outage Rate for enhanced performance assessment. In the pursuit of heightened power system reliability, sequential simulations prove invaluable, particularly in minimizing Expected Energy Not Supplied (EENS) and improving overall system reliability. The results obtained through sequential simulations underscore the effectiveness of this approach within bulk electrical systems. The installation of multiple FACTS devices in the system's weakest areas facilitated EENS computation, coupled with the assessment of related reliability indices such as system frequency and system duration. This approach not only enhances system reliability but also promotes the economic operation of both transmission and distribution.The simulation results substantiate the alignment of power system reliability objectives in deregulated power systems with the required standards, advocating for the restructuring of power networks. The reliability assessments, driven by the optimal placement of DGs and FACTS devices, reveal substantial improvements in system reliability, underscoring the pivotal role of these technologies in enhancing overall power system dependability.

The constant failure in cyber security in power systems and substation automation that has crippled business activities that mostly depend on power to run their routine activities are caused by Lack of Adequate Security Measures, Human Error, Outdated Software and Hardware, Insufficient Training and Awareness, Insider Threats, Weak Access Control Mechanisms, Inadequate Network Segmentation, Failure to Patch Vulnerabilities, Complexity of the System, Third-Party Vendor Risks and Denial of Service (DoS) Vulnerabilities. This is surmounted by introducing improved cyber security in power systems and substation automation using intelligent based system. To achieve this, it is done in this procedure characterizing and establishing the causes of failure in cyber security in power systems and substation automation, designing a SIMULINK model for cyber security in power systems and substation automation, designing a rule base that will reduce the causes of failure in cyber security in power systems and substation automation,training ANN in the rule base for effective reduction of causes of failure in cyber security in power systems and substation automation, developing an algorithm for the process, designing a SIMULINK model for improving cyber security in power systems and substation automation using intelligent based system and validating and justifying the percentage of improvement in the reduction of causes of failure in cyber security in power systems and substation automation. The results obtained were the conventional Lack of Adequate Security Measures that cause failure in improving cyber security in power systems and substation automation was 25%. On the other hand, when an intelligent based system was incorporated into the system, it drastically reduce the cause failure in improving cyber security in power systems and substation automation to 21.53%, the conventional outdated software and hardware that cause failure in improving cyber security in power systems and substation automation was 15%. Meanwhile, when an intelligent based system was inculcated in the system, it became reduced to 12.92% thereby enhancing the performance of cyber security in power systems and substation automation by 2.08%, the conventional Weak Access Control Mechanisms that cause failure in improving cyber security in power systems and substation automation was 8%. However, when an intelligent based system was integrated in the system, it was reduced to 6.9% and the conventional Denial of Service (DoS) Vulnerabilities that cause failure in improving cyber security in power systems and substation automation was 2% while when an intelligent based system was incorporated in the system, it automatically reduced to 1.7%. Finally, with these results obtained, It vehemently shows that the percentage improvement in cyber security in power systems and substation automation was 0.3%.

In the condition of strong magnetic storm, geo-magnetically induced current (GIC) flowing through the neutral point of the transformer, causing the increase of reactive power loss of the transformer, which leads to overload of the reactive power compensation device, drop of the bus voltage and occurrence of a chain fault, which in turn causes a blackout of the system. Considering the suddenness of the geomagnetic storm, but at the same time it has the characteristics of short time and large range. The paper studies the transient voltage response and the change of the reactive power output of the generator. The IEEE9 nodes model is built in PowerWorld software, and nine different geomagnetic storm environments are set up. The conclusions are as follows: 1) Under the same induced geoelectric field amplitude, the steady state value of each bus voltage of the system is located in safe and stable operation. In the interval, but in the transient process, the transient value of some bus voltage may be lower than the safe and stable operating range. If there is a load sensitive to voltage changes in the system, the transient power quality needs to be paid attention. 2) The reactive output of the generator will increase instantaneously when the magnetic storm comes. Compared with its steady state value, the maximum value in the transient process should be paid more attention. 3) Under the condition of the same induced ground electric field amplitude, if the rate of change is different, the bus voltage of the system and the reactive output of the generator will also have different responses. The conclusions obtained can lay a certain foundation for further research on the impact of geomagnetic storms on the power system.

The power grid has significant power losses, unstable voltage, and large voltage drops during high demand due to its high resistance. One way to reduce power loss is by strategically placing and sizing Distributed Generation (DG) within the distribution network. However, improper installation of DG can increase power loss. To address this issue, various optimization techniques have been used, but finding the best solution and dealing with complex issues has been challenging. It is important to make efforts to optimally place and size DG in the distribution network to minimize power loss. To this end, a research study aimed to minimize power loss and improve the voltage profile on the DG network using the Whale Optimization Algorithm (WOA) was done. Objective functions were formulated and integrated into WOA, and power flow analysis on the standard IEEE 33-bus and 33-bus Ilorin industrial distribution feeder with and without DG was conducted using the forward and backward sweep distribution load flow algorithm. The optimal size and location of DG for power network loss reduction using sensitivity analysis (SA) and the whale optimization algorithm were determined. The results of the power flow analysis indicated that the total active losses and reactive power losses were reduced to varying extents with the integration of DG using both SA and WOA. The validation results showed that WOA is more efficient and provides high-quality solutions in terms of system loss reduction and best placement for DG in power systems compared to the application of SA. Additionally, WOA was found to offer accurate and high-quality solutions for power loss reduction compared to other existing techniques such as Loss Sensitivity Analysis (LSA), Grey Wolf Optimizer (GWO), Adaptive Shuffled Frogs Leaping Algorithm (ASFLA), and One Rank Cuckoo Search Algorithm (ORCSA). Keywords: Optimization, Distributed Generation (DG), Whale Optimization Algorithm (WOA), Sensitivity Analysis (SA)

The Point of Common Coupling (PCC) where suppliers’ responsibility and customers demand meet is of great concern due to increase degree of voltage variation assessment; valuable indicator of system conditions (voltage profile). Unstable condition of the power system outside operational or statutory limit, an adverse effect of nonlinear loads usually generate harmonics as well as fundamental frequency voltage variations and increase rate of power losses. These loads need to be compensated for. The major concerns of utility operations is to mitigate adverse effect of this system conditions. This research work focuses on optimal siting and sizing of Distributed Generation (DG) in a 43 bus distribution system. Power losses coupled with voltage deviation, considering objective function that compute present percentage losses in 11kV Dikko feeder, Abuja Electricity Distribution Company (AEDC), Suleja Distribution Network, Nigeria. We identified buses with poor voltage profile without DG installation and determined optimal sizing and siting of DGs where losses can be mitigated and power quality improved. ETAP version 12.6 2014 was used for load flow analysis to establish a decisive based case. The total load of the system considered was (3490 + j2700) kVA. Active and Reactive power losses in the system before DG installation were 246.300 kW and 289.903 kVAR respectively. DGs installation in the case study, has a considerable effects on loss reduction in the network. It is observed that 8.10% and 7.20% active and reactive power loss reduction was achieved while bus voltage improved by 0.4%. Genetic Algorithm Optimization techniques programmed in MATLAB 2015 software was used for optimal placement and sizing of the DG in the system.