Design of an advanced electric power distribution systems using seeker optimization algorithm

Power distribution system design of the green well-off villages and small towns in East China is studied in this paper. Electricity load forecasting, power distribution and energy-saving systems design, effect of distributed energy accessing to the villages and small towns grid are studied. Finally, the advices are given on the power distribution system design of the green well-off villages and small towns.

Power management in advanced power distribution systems integrated with Photovoltaic (PV) sources, batteries, and Super Capacitors (SCs) plays a vital role in ensuring stable and efficient energy flow. However, these systems often face drawbacks such as increased energy consumption due to inefficient control strategies, higher emissions from backup conventional sources during low PV output, and elevated operational costs from frequent battery cycling and system maintenance, despite efforts to improve efficiency and enhance renewable energy utilization. To overcome these drawbacks, this manuscript proposes an approach for optimal power management in a power distribution system with RES. The suggested method is the combination of both the Greater Cane Rat Algorithm (GrCRA) and Pre-Activated Convolution Residual and Triple Attention Mechanism Network (PCRTAM-Net), termed as the GrCRA-PCRTAM-Net approach. The primary aim of the suggested method is to reduce energy consumption, emissions, and operational cost while maximizing efficiency and renewable energy utilization in an advanced power distribution system. GrCRA optimizes the allocation and scheduling of power resources in advanced power distribution systems. PCRTAM-Net predicts future power demand and renewable energy generation patterns to support optimal power management. Flow Direction Algorithm-Convolutional Neural Network (FDA-CNN), Hippopotamus Optimization Algorithm (HOA), Particle Swarm Optimization (PSO), Spider Wasp Optimizer, and Multi-scale Hypergraph-based Feature Alignment Network (SWO-MHFAN), Golden Jackal Optimization-Progressive Conditional Generative Adversarial Network (GJO-PCGAN) are some of the existing techniques that are compared with the suggested method once it is implemented in MATLAB. An 18.7% overall energy reduction compared to the current methods has been achieved by GrCRA-PCRTAM-Net, which also attained an operational cost of 1505 cents, an emission level of 60.3 ppm, an efficiency of 99.1%, and a reduction in overall energy consumption. This further validates that the hybrid method effectively performed power flow optimization and stability enhancement in power distribution networks with renewable integration.

Current flow in power distribution systems inside an integrated circuit (IC), especially in VLSI and wafer-scale ICs, causes problems of voltage drop and metal migration, leading to logic malfunction, reduction in operating speed, and reduction in the expected life span of a chip. Accurate estimations of currents are needed to design the power distribution systems so that they will withstand the adverse effects of current surges. During fabrication or as a result of aging, the power distribution systems may break at some weak points. As a result, some parts of the systems may have to route excessive amounts of currents. A power distribution system should be designed so that, in the presence of a limited number of these breaks, the system will deliver currents to the macro cells without violating some prescribed limits on voltage drops and without causing metal migration. The author deals with estimating currents in the segments of power distribution systems under fault conditions and develops guidelines for designing the systems so that the voltage drop and metal migration constraints with respect to these current estimates will not be violated.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Feeder reconfiguration has been researched from past few years for optimal planning of primary power distribution system (PDS) with objectives of minimizing the overall system cost and power loss. Till now the research work done for simultaneous reconfiguration of the secondary with primary PDS are very less. The proposed methodology incorporates both primary and secondary reconfiguration simultaneously with a single objective framework (weighted aggregation of both cost and reliability into account) including the position of tie and the sectionalizing switches. In this paper the parameters of a novel human randomized search method called Seeker optimization algorithm (SOA) is used for planning purpose. And, is modified based on position of status of switches by changing the population in a binary array and make a shift operator to change the position of switch to make a new population to construct binary coding SOA for feeder reconfiguration of both primary and secondary network simultaneously. For reliability purpose a contingency-load-loss-index is used. Related results are shown by the use of the proposed methodology for a real case of a residential primary and secondary network consisting of 75 electrical nodes.

Testability design of power distribution system considering noise immunity characteristics

In an all-electric ship, a high level of service continuity to equipment loads is of paramount importance to both mission success and personnel well-being. The objective of this paper is to investigate the reliability improvements obtained due to the design of a three-dimensional shipboard power distribution system (SPS). Several three-dimensional architectures are designed based on the following notional distribution system topologies namely, ring bus and breaker-and-a-half. Three-dimensional topologies are simulated by supplying equipment loads using both upper and lower levels of the shipboard power system connected using vertical tie-buses. The reliability indices obtained for three-dimensional topologies are compared to that of the notional planar topologies. The results conclude that for each notional topology, a more reliable shipboard power system is obtained by designing a three-dimensional architecture.

Distributed Generations (DGs) are most commonly used in Advanced Power Distribution System (APDS) for improving the voltage level and minimizing the power loss in distribution system. This paper represents a modified Teaching Learning Based Optimization Technique (TLBO) to reconfigure the distribution system and find the optimal placement and sizing of DGs to minimize the total system loss simultaneously. In modified TLBO radial trees are consider as a initial population and possible paths between nodes are considered as design variables for finding the optimal reconfigured route. A shift operator is used to change the switch position in order to find the desired switch combination. A simultaneous reconfiguration with DG placement is done by the proposed method with different sizes of DGs in search of optimal solution. Proposed approach is illustrated on the standard IEEE-33 bus test system considering real-time design practices.

A new approach for diminution of side lobe Ratio or level (SLL)maximum with half power beam width (HPBW) of thinned large multiple concentric circular antenna of the uniformly exuberated isotropic element, is proposed. Itis a novel optimization algorithm based on Seeker Optimization Algorithm (SOA) is used. Concentric Circular Antenna Array (CCAA) has been greatly recognized within subject of base radio station of the radio and telecommunications system. Since it has a 360-degree scan around its focus, beam pattern and all-azimuth scan capability, it has numerous advantages over other array geometries. A 9 ringed CCAA with a central element feeding is taken into consideration. CCAA which is having isotropic elements is examined by this algorithm and is shown appropriate.. Optimization efficiency is justified by antenna array synthesis, which is the result of themassive simulation. In all the cases mentioned in the paper, relative sidelobe level (SLL) is less than −20 dB with fixed HPBW compared to case of a uniform array. By using SOA with isotropic elements, the results of the simulation depict the amount of effective antenna elements can be pared from 279 to 120 with consistent abatement in side lobe ratio by 21.04 dB relative to that of the main beam with a fixed HPBW. Standard Particle Swarm Optimization (PSO) is used here to scrutinize outcome of SOA.

The increasing of distributed generators and high demand of customer service quality of recent years keep challenging the design and operation of electric power distribution systems. The future smart distribution grid is envisioned to be a large complex cyber‐physical distribution system (CPDS), where physical grid components are monitored and controlled based on the interactions on the cyber space. As sensors and controllers, smart feeder remote terminal units (FRTUs) transfer necessary data to the control centre for situational awareness, and receive orders from the control centre for dynamic controlling. This study introduces an analytical FRTU deployment approach for the reliability improvement of integrated CPDSs. The FRTU deployment problem is modelled as a mixed‐integer non‐linear programming problem, which aims to minimise the total cost with the reliability index of average service available index as the constraint. Two kinds of distribution feeders (overhead and underground) are considered. The total cost includes the life cycle cost of FRTUs in addition to customer interruption cost. The proposed model can be solved by large‐scale commercial solvers in an efficient manner. Test results of the RBTS‐BUS4 distribution system and a China Southern Power Grid 62‐bus distribution system validate the accuracy and effectiveness of the approach. Comparison with the genetic algorithm also shows its great efficiency.

There are numerous approaches being used to reduce power losses in the distribution system. In this work, the concept of network reconfiguration is used in an effort to provide new algorithms to decrease distribution system losses. The network reconfiguration issue must be solved with effective distribution load flow (DLF). Two key components are required for the Optimal Network Reconfiguration (ONR) strategy to reduce losses: first, promising radiality for the reconfigured network, and second, providing optimal losses for the final reconfigured network. The complex computational problem of network reconfiguration is addressed using five meta-heuristic techniques: Genetic Algorithm (GA), Shuffled Frog Leap Algorithm (SFLA), Particle Swarm Optimization (PSO), Pigeon Inspired Optimization (PIO), and Jaya Optimization algorithm. These techniques take into account equality and inequality constraints to find the best network reconfiguration with the minimum power losses in the system. The IEEE 33 bus distribution system is used as a test case, and the test system is subjected to network reconfiguration. Results of different algorithms were included. Over the other algorithms, the Pigeon Inspired Optimization (PIO) algorithm outperforms them.

The power supply efficiency in industrial parks directly impacts production stability and energy costs for enterprises. Traditional decentralized distribution often leads to redundant equipment configuration, increased transmission losses, and complex multi-site dispatch challenges, undermining overall operational efficiency. When facilities with differing characteristics coexist within the same park, pronounced load fluctuation variations emerge, heightening demands for power supply reliability and increasing energy management complexity. This necessitates establishing a unified power supply and distribution optimization plan. Therefore, this paper explores the design of a joint power supply and distribution system for multi-site facilities, aiming to enhance the economic viability and practicality of industrial cluster power supply and distribution systems.

High-speed digital devices require multiple voltage and frequency domains to accommodate the core logic and the input/output (I/O) circuitry for multiple interfaces. In addition, some of these interfaces are programmable to various speeds and signaling modes and they require multiple power supply voltages. These requirements create complex power delivery and signal distribution solutions. This paper proposes a design methodology for fast transient point of load (POL) power distribution architectures for microprocessors and fast switching logic. This paper presents an efficient power distribution system (PDS) design methodology that models the load, its point of load power converter, and the transporting system so that the entire system can be efficiently implemented in circuit simulation as a complete integrated setup for design optimization. Models for the voltage regulator module (VRM) and its transient response and stability, the active load with multiple power supply domains, and the power planes are discussed in detail. System voltage noise margin budgeting is also emphasized.

Reactive power optimization is a mixed integer nonlinear programming problem where metaheuristics techniques have proven suitable for providing optimal solutions. Optimal reactive power dispatch (ORPD) is a key instrument to achieve secure and economic operation of power systems. Due to complex characteristics of ORPD, heuristic optimization has become an effective solver. In this paper, swarm and evolutionary algorithm have been applied for reactive power optimization. A two-phase hybrid particle swarm optimization (PSO) approach is used to solve optimal reactive power dispatch (ORPD) problem has been presented in this paper. In this hybrid approach, PSO is used to explore the optimal region and direct search is used as local optimization technique for finer convergence. This paper also presents a particle swarm optimization for reactive power and voltage control considering voltage stability. The proposed method determines a control strategy with continuous and discrete control variables such as AVR operating values, OLTC tap positions, and the amount of reactive power compensation equipment. A novel heuristic optimization algorithm namely the Mean-Variance Mapping Optimization (MVMO) is proposed to handle the ORPD problem. The objective of the proposed PSO is to minimize the total support cost from generators and reactive compensators. It is achieved by maintaining the whole system power loss as minimum thereby reducing cost allocation.

This study proposes a distributed load restoration method to effectively model and solve the load restoration problem of integrated power distribution and natural gas systems (IDGSs) after faults for resilient operation. The IDGS load restoration problem is devised as a mixed-integer second-order cone programming (MISOCP) model to minimize the total load loss cost of IDGS. This model considers distribution network reconfiguration and the coupling effect between the power distribution system (PDS) and natural gas system (NGS). Moreover, a bidirectional gas flow model is used to offer more flexibility for load restoration when the NGS is faulty. By considering the independent management and information privacy of each energy subsystem, the proposed model is solved using an alternating direction method of multipliers (ADMM) algorithm in a distributed manner. Furthermore, an adaptive-ADMM algorithm is used for convergence acceleration. Finally, numerical studies are conducted to validate the proposed methods effectiveness.

Green energy conservation is the mainstream trend in the current development of the construction industry. The application of energy-saving technology in building electrical system design can effectively reduce energy consumption, avoid unnecessary energy consumption, and truly achieve energy conservation and environmental protection. Based on this, the article elaborates on the principles of energy-saving design in building electrical systems, and actively explores the application of energy-saving technologies from different perspectives such as optimizing power supply and distribution system design, adopting high-efficiency energy-saving lighting equipment, applying renewable energy, promoting smart home technology, and improving the efficiency of building electrical equipment.