Advanced Control and Operation of Microgrids and Power Distribution Systems

Large-scale integration of rooftop solar power generation is transforming traditionally passive power distribution systems into active ones. High penetration of such devices creates new dynamics for which the current power distribution systems are inadequate. The changing paradigm of power distribution system requires it to be operated as cyber-physical system. A goal-based holonic multiagent system (HMAS) is presented in this paper to achieve this objective. This paper provides details on design of the HMAS for operation of power distribution systems. Various operating modes and associated goals are discussed. Finally, the role of HMAS is demonstrated for two applications in distribution systems. The first one is associated with control of reactive power at solar photovoltaic installations at individual homes for optimal operation of the system. The second deals with the state estimation of the system leveraging different measurements available from smart meters at homes.

Blockchain for decentralized transactive energy management system in networked microgrids

Network reconfiguration is an alternative to reduce power losses and optimize the operation of power distribution systems. In this paper, an encoding scheme for evolutionary algorithms is proposed in order to search efficiently for the Pareto-optimal solutions during the reconfiguration of power distribution systems considering multiobjective optimization. The encoding scheme is based on the edge window decoder (EWD) technique, which was embedded in the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and the Nondominated Sorting Genetic Algorithm II (NSGA-II). The effectiveness of the encoding scheme was proved by solving a test problem for which the true Pareto-optimal solutions are known in advance. In order to prove the practicability of the encoding scheme, a real distribution system was used to find the near Pareto-optimal solutions for different objective functions to optimize.

With increasing penetrations of renewable energy in power distribution systems, operators is facing challenges on reducing renewable energy curtailment, which is caused by supply-demand mismatch, feeder congestion, and nodal voltage limits. Converting surplus renewable electricity into hydrogen by electrolyzors has been recognized a potential way to address this. To this end, we proposed a coordinated operation approach for hydrogen and power distribution systems, considering distribution level power and hydrogen pipeline flows, as well as storage capabilities provided by linepack. The proposed approach can be used to investigate the benefits from our coordinated approach on the basis of current separated practice. Our numerical simulations show that the proposed coordinated dispatch model can utilize the benefit of renewable power to minimum the total cost and improve the utilization of transmission lines.

The growth of photovoltaic distributed generation has introduced significant challenges to both the operation and planning of power distribution systems. Currently, operational problems, power quality issues, and protection concerns are very common, directly associated with the high penetration of solar photovoltaic generation systems. Among the most commonly faced problems are voltage violations, exceeding thermal limits of transformers and conductors, increased voltage unbalances and harmonic distortions, as well as high technical losses and improper operation of overcurrent protection systems. In this context, this work aims to present contributions to the analysis of the impacts of photovoltaic distributed generation on power distribution systems through: (a) characterization, through experimental tests, of inverters used in photovoltaic distributed generation, in terms of harmonic and inter-harmonic emissivity, injection of direct current, and short-circuit contribution, since such information is rarely found in manufacturer catalogs; (b) development and construction of a voltage sag generator for conducting short-circuit contribution tests of the tested inverters; (c) development of a methodology for analyzing the hosting capacity of photovoltaic distributed generation considering a stochastic allocation approach in low-voltage circuits involving the most frequently encountered impacts in the distribution system, as well as the application of traditionally adopted mitigation methods; (d) development of a computational tool with a graphical interface for processing hosting capacity analyses; (e) development of a methodology for studying the impact of photovoltaic distributed generation on the protection of power distribution systems, considering a time-domain approach. As a result, important solutions and discussions are presented to assist engineers in better planning and management of photovoltaic distributed generation, contributing to the sustainability and efficiency of distribution networks in the face of the growing use of photovoltaic solar energy.

This paper proposes a new algorithm to effectively detect distortions and evaluate the perceptual quality of 3D reconstructed images, with a primary application context in detecting blurring, deformation, and other issues in the reconstruction of operation and maintenance images of power transmission and distribution systems. Combining the Gabor transform and convolutional neural network, distortion classification is applied to large-scale 3D reconstructed images to optimize the reconstruction process, improve efficiency, and improve classification accuracy and model robustness by handling class imbalance and distortion degree for reclassification. By optimizing the collaborative computation of large-scale 3D reconstructed images through distortion classification and correlation analysis, and utilizing rotation invariant feature descriptors and multi-resolution matching strategies, the accuracy and efficiency of image matching have been improved. A quality grading evaluation standard was established based on the descriptor association threshold to objectively quantify the quality of reconstructed images. The results indicate that the proposed method outperforms traditional methods in both accuracy and computational speed, validating the effectiveness of the method.

The urban rail transit traction power supply cable bears the important tasks such as power connection and power transmission among the main substation, the traction and buck stations. Due to the greater length of the power supply cable, the series parallel resonance problem caused by the charging capacitor is a serious threat to the safe and stable operation of the rail transit system. In order to ensure the safe and stable operation of power supply and distribution system of urban rail transit system, this paper studies the design and selection of traction power supply cable for urban rail transit under the harmonic constraint. The method can effectively avoid the safety problem of the harmonic series-parallel resonance due to cable charging capacitance in the traction power supply system for urban rail transit users. At the same time, it also has guiding significance for the design of cable length and charging capacity of other power supply and distribution system.

The reliability and efficiency of transformers are crucial for the stable operation of power distribution systems. This project focuses on the Condition Monitoring of Transformers Based on IoT Technology, enabling real-time monitoring of critical parameters such as temperature, oil level, voltage. By integrating sensors, Arduino Uno, and the NodeMCU ESP8266 WiFi module, the system continuously collects data and transmits it to a cloud-based platform for remote monitoring and analysis. The implementation of IoT technology enhances predictive maintenance, reducing unexpected failures and minimizing downtime. Additionally, data-driven insights help optimize transformer performance, extend its lifespan, and reduce maintenance costs. This approach ensures a more efficient, reliable, and cost-effective power distribution network.

This paper solves a daily multiobjective optimization model for efficient operation of power distribution systems. The model aims to minimize the voltage deviations, minimize power losses and minimize the energy costs of the distributed generators. The model is implemented on a modified 33 bus distribution system by including: two voltage regulators and four distributed generators. Three different simulation sets are performed: the first one includes only voltage regulators and the second one includes only distributed generators and the third one includes both voltage regulators and distributed generators. When the simulation results are compared, results show that better voltage profiles with less power losses and costs might be obtained by using both voltage regulators and distributed generators.

CHP system with Energy saving, environmental protection, economic and other characteristics,have good prospects for the development and application value.This paper directe a micro grid system consisted by photovoltaic cells, wind turbines, fuel cells, microturbines, auxiliary boilers, thermal energy storage systems and batteries and heat load and electrical load.Considering various distributed power generation costs, environmental costs and micro-grid equipment maintenance costs,To meet the constraints of micro-grid operation, optimization of the different micro-grid distributed power and energy storage system power output, make the system's total operating costs are minimized.This paper analyzes the economic and environmental of micro-grid optimal operation characteristics, given a model of CHP micro-grid.For the cost of power generation and emissions of different weights, using bacterial foraging optimization(BFO) algorithm,through a numerical example verified the Correctness and effectiveness of mathematical model and optimization algorithm .

Energy storage systems (ESS) exhibit high flexibility and rapid response capabilities, effectively mitigating load fluctuations and voltage instability caused by renewable integration. This paper proposes a hierarchical dispatch strategy for active distribution networks utilizing ESS. The upper-level model minimizes load curve volatility and maximizes ESS arbitrage revenue, optimizing the total charge/discharge power of the ESS across all time periods, while the lower-level model minimizes active power loss costs. Implemented on a modified IEEE 33 node test system, the Moth-Flame Optimization (MFO) algorithm solves this bilevel problem, with simulations validating the strategy's efficacy.

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.

The selection of power sub-station location and distribution line routing in power systems is one of the important strategic decisions for both private and public sectors. In general, contradictory factors such as availability, and cost, affects the appropriate selection which adheres to vague and inexact data. The work presented in this research deals with the development of models and techniques for planning and operation of power distribution system. The work comprises a wider framework from the siting of a sub-station to load flow analysis. Work done also shows the application of quantum- geographic information system (Q-GIS) in finding load point coordinates and existing sub-station locations. The proposed integrated approach provides realistic and reliable results, and facilitates decision makers to handle multiple contradictory decision perspectives. To accredit the proposed model, it is implemented for power distribution planning in Bihar which consists of 9 divisions. A Cubic Spline Function-based load flow analysis method is developed to validate the proposal.

This paper presents an impact study of energy storage on a micro-grid system consisting of a very small power producer of a biomass type. The energy storage used in this paper is a battery bank. It comprises a combination between shunt and series battery cells in order to implement a sufficient battery storage system. To verify the simulated battery storage system, one day operation of an electric power distribution system was tested. This simulation was performed using MATLAB software in order to support and also to balance the energy exchange between the generation (drawn from both substation and renewable energy plants) and the power demand of the entire system. With the energy storage plant of battery banks, a simple 6-bus test system with a total power generation of 6 MW is situated for test. Considering of four test cases (case 1: without energy storage installation and neglecting power losses, case 2: without energy storage installation but considering power losses, case 3: with energy storage installation but power losses neglected, case 4: with energy storage installation and also considering power losses). Power transmission losses used in this paper can be determined by using Newton-Raphson power flow solution method. The simulation of the test system was carried out by performing one day simulation with energy storage and energizing stored energy by using an appropriate algorithm. The results showed that the system with energy storage can lead to efficient energy usage and power loss reduction.

Coastal cities often face typhoons and urban water logs, which can cause power outages and significant economic losses. Therefore, it is necessary to study the impact of these disasters on urban distribution networks and improve their flexibility. This paper presents a method for predicting power-grid failure rates in typhoons and water logs and suggests a strategy for improving network elasticity after the disaster. It is crucial for the operation and maintenance of power distribution systems during typhoon and water-logging disasters. By mapping the wind speed and water depth at the corresponding positions in the evolution of wind and water logging disasters to the vulnerability curve, the failure probability of the corresponding nodes is obtained, the fault scenario is generated randomly, and the proposed dynamic reconstruction method, which can react in real-time to the damage the distribution system received, has been tested on a modified 33-node and a 118-node distribution network, with 3 and 11 distribution generators loaded, respectively. The results proved that this method can effectively improve the resiliency of the distribution network after a disaster compared with the traditional static reconstruction method, especially in the case of long-lasting wind and flood disasters that have complex and significant impacts on the distribution system, with about 26% load supply for the 33-node system and nearly 95% for the 118-node system.