Multi Objective Optimization Algorithm and Large-scale Data Model Analysis in Urban Power Grid Planning

Hippopotamus algorithm for optimal sizing of hybrid renewable energy system

Electric power has become an essential part of daily life: we plug our electronic devices in, switch our lights on, and expect to have power. As the availability of power is usually taken for granted in modern societies, we mostly feel annoyed at its absence and perceive the importance of power during outages which have severe effects on the public order. Blackouts have had disastrous consequences for many countries and they continue to occur frequently. Such examples demonstrate the necessity for careful analysis and planning of power grids, to ultimately increase the reliability of power grids. The power grids have evolved due to economic, environmental and human-caused factors. In addition to the contingency analysis, nowadays, the operation and planning of power grids are facing many other challenges (such as demand growth, targeted attacks, cascading failures, and renewable energy integration). Thus, many questions arise, including: which buses (nodes) to connect with a new line (link)? What are the impacts of malicious attacks on power grids? How may an initial failure result in a cascade of failures? How to prepare for the integration of renewable energy? Answering such questions requires developing new concepts and tools for analysing and planning of power grids. Power grids are one of the largest and the most complex man-made systems on earth. The complex nature of power grids and its underlying structure make it possible to analyse power grids relying on network science. The applications of network science on power grids have shown the promising potential to capture the interdependencies between components and to understand the collective emergent behaviour of complex power grids. This thesis is motivated by the increasing need of reliable power grids and the merits of network science on the investigation of power grids. In this context, relying on network science, we model and analyse the power grid and its near-future challenges in terms of line removals/additions, malicious attacks, cascading failures, and renewable integration.

Analysis and Prediction of Differential Operation and Maintenance Cost of Power Transmission and Transformation

The development of the power grid relies on the development of the city. The target of power gird planning is providing safe, reliable and high quality electrical energy for consumers according to the charging buildings and roads of the city. The layout of buildings and roads is described more precisely, so that reliable basic data for power load forecast and power grid planning is provided by BIM. This paper takes street block as a unit to carry out the point load forecast base on BIM. Then optimal sizing and location model of substations is established with the objective of minimum cost and the constraints on full coverage of power supply, substation load rate and power supply radius. The model is solved by particle swarm optimization algorithm. Finally, the effectiveness of the method is verified by a case study.

Urban grid planning needs to focus on sound investment plans to improve the safety and reliability of power system power supply to meet the growing needs of users. Does not adversely affect the environment. The contradiction in urban power grid and urban planning is an important reason that plagues the rapid development of power grid enterprises. Therefore, under the trend of urbanized dogs, urban power grid construction planning and urban overall planning are required to match. Urban planning needs to consider urban power grid planning as an important component, and match urban development to achieve simultaneous development. The integrated management and distribution system is the platform that contains all the information processing. It can share information and improve the reliability and security of the grid operation. This paper first introduces the integrated system of urban problems and its concept and architecture, focusing on the overall design form and process information management model, system function structure and several aspects of the main functions of the integrated system.

As for the complex integration of power grid planning data and difficulty in meeting the power grid development needs by the current power grid planning simulation and calculation capability, this paper conducted the study on power grid planning data structure system, power grid consistency planning decision-making system by using big data and cloud computing technology. The key technologies, functional architecture and network architecture for the implementation of the power grid consistency planning decision-making system are proposed. The decision-making system for power grid consistency planning is developed to realize the distributed maintenance, structured consistency management and intelligent cloud storage of power grid planning data resources, and realize the dynamic allocation and overall coordination of calculation and verification, which can meet the needs of power grid consistency planning simulation calculations at different management levels and voltage levels, and provide technical support for large-scale power grid planning decision-making. The field application in more than 120 power grid companies illustrates the economic benefits of the developed decision-making system for power grid consistency planning.

This research investigates the integration of renewable energy sources such as solar and wind into Nigeria’s power grid. The main objective is to develop a simulation model that examines how renewable energy systems affect power reliability and supply efficiency under different load and generation conditions using MATLAB. The simulation setup includes solar photovoltaic arrays and wind turbines connected to the grid through inverter systems and controlled using standard power system techniques. Changes in solar radiation and wind speed are introduced during the simulation to reflect real-life variations in renewable energy generation. The results show that, despite their variable nature, solar and wind systems can support the grid effectively when combined with proper control, forecasting, and storage technologies. The study demonstrates that integrating renewable energy into the grid can reduce power shortages, improve electricity access, support a more stable and reliable power supply as well as contribute to sustainable development goals by promoting the use of renewable energy in Nigeria.

Battle Royale Optimizer (BRO) is a recently proposed optimization algorithm that has added a new category named game-based optimization algorithms to the existing categorization of optimization algorithms. Both continuous and binary versions of this algorithm have already been proposed. Generally, optimization problems can be divided into single-objective and multi-objective problems. Although BRO has successfully solved single-objective optimization problems, no multi-objective version has been proposed for it yet. This gap motivated us to design and implement the multi-objective version of BRO (MOBRO). Although there are some multi-objective optimization algorithms in the literature, according to the no-free-lunch theorem, no optimization algorithm can efficiently solve all optimization problems. We applied the proposed algorithm to four benchmark datasets: CEC 2009, CEC 2018, ZDT, and DTLZ. We measured the performance of MOBRO based on three aspects: convergence, spread, and distribution, using three performance criteria: inverted generational distance, maximum spread, and spacing. We also compared its obtained results with those of three state-of-the-art optimization algorithms: the multi-objective Gray Wolf optimization algorithm (MOGWO), the multi-objective particle swarm optimization algorithm (MOPSO), the multi-objective artificial vulture's optimization algorithm (MOAVAO), the optimization algorithm for multi-objective problems (MAOA), and the multi-objective non-dominated sorting genetic algorithm III (NSGA-III). The obtained results approve that MOBRO outperforms the existing optimization algorithms in most of the benchmark suites and operates competitively with them in the others.

With the continuous development of social economy, the demand for electricity is increasing day by day. Power users have higher and higher requirements on the reliability of power supply. In case of grid failure, The impact on businesses and individuals is also growing. The reliability of medium voltage power supply system has been paid more and more attention. The reliability of medium voltage power supply has a direct impact on users’ satisfaction with electricity consumption. Power supply reliability has become an important index to reflect the continuous power supply capacity of enterprises. Power supply enterprises pay more attention to power supply reliability year by year. Improving the reliability of power supply for medium voltage users has become an important part of reliability management. The author summarizes the work experience, the main factors affecting the reliability of medium voltage supply are analyzed. The measures and methods to improve the reliability of medium voltage power supply are put forward.

Keeping networks security has never been such an imperative task as today. In this paper, by combining particle swarm optimization and clustering algorithm, a new detection method, Intrusion Detection based on Unsupervised Clustering and PSO algorithm (IDCPSO), is proposed. Particle swarm optimization algorithm is used to optimize the clustering results and obtain the optimal detection result. IDCPSO needs unlabeled data for training and automatically establish clusters and detect intruders by labeling normal and abnormal groups. Computer experiment results with KDD cup show that this algorithm is effective for intrusion detection.

As the basis for the construction and development of the power grid industry, power grid planning not only affects the development direction of power grid enterprises, but also determines the economic level, social stability and quality of life of urban residents. In the construction and development of the new era, the digital transformation of power grid planning business is an important part of the construction and improvement of the digital power grid system, which will guide the power grid planning business to develop stably in the direction of intelligence, automation and information, actively create a safe and reliable smart grid, and lay a solid foundation for improving the development level of power grid enterprises. Therefore, after understanding the current digital transformation goals and development status of power grid planning business, this paper mainly explores the specific plan for the transformation of power grid planning business of a regional power enterprise according to the structure and transformation requirements of the new power system, and finally explores the practical significance of digital transformation according to the construction effect and development goals, providing a reference for the reform and development of the power industry.

PurposeA set of routers that are connected over communication channels can from network-on-chip (NoC). High performance, scalability, modularity and the ability to parallel the structure of the communications are some of its advantages. Because of the growing number of cores of NoC, their arrangement has got more valuable. The mapping action is done based on assigning different functional units to different nodes on the NoC, and the way it is done contains a significant effect on implementation and network power utilization. The NoC mapping issue is one of the NP-hard problems. Therefore, for achieving optimal or near-optimal answers, meta-heuristic algorithms are the perfect choices. The purpose of this paper is to design a novel procedure for mapping process cores for reducing communication delays and cost parameters. A multi-objective particle swarm optimization algorithm standing on crowding distance (MOPSO-CD) has been used for this purpose.Design/methodology/approachIn the proposed approach, in which the two-dimensional mesh topology has been used as base construction, the mapping operation is divided into two stages as follows: allocating the tasks to suitable cores of intellectual property; and plotting the map of these cores in a specific tile on the platform of NoC.FindingsThe proposed method has dramatically improved the related problems and limitations of meta-heuristic algorithms. This algorithm performs better than the particle swarm optimization (PSO) and genetic algorithm in convergence to the Pareto, producing a proficiently divided collection of solving ways and the computational time. The results of the simulation also show that the delay parameter of the proposed method is 1.1 per cent better than the genetic algorithm and 0.5 per cent better than the PSO algorithm. Also, in the communication cost parameter, the proposed method has 2.7 per cent better action than a genetic algorithm and 0.16 per cent better action than the PSO algorithm.Originality/valueAs yet, the MOPSO-CD algorithm has not been used for solving the task mapping issue in the NoC.

The paper studies the optimal configuration of pumped storage power station and new energy units in the power grid with the help of HOMER software. Firstly, summarize the power grid planning with pumped storage power stations and new energy units. Secondly, sort out the objectives of power grid planning, and clarify the boundary conditions and related constraints of the problem. Then, describe the operation principle of the Homer software briefly. Finally, list 3~5 power grid coordinated schemes of pumped storage power station and new energy units, analysis each scheme with running the HOMER model. When running the HOMER, input load demand data, power generation resource data as well as the technical parameters of power grid components. According to the calculation results of HOMER, the optimal power grid coordinated scheme of pumped storage power station and new energy units under specific scenarios is obtained.

Distributed generation provides a new opportunity for modern power supply, but it also impacts on the operation and management of distribution network. Distributed power connected to the distribution network has changed the mode of operation of the distribution network from the original radiation type to a multiple power supplies network. The power flow direction of the traditional distribution network is from transformer substation to load. The access on Distributed power makes the power flow direction no longer only from power resource to the user side and increases the complexity and uncertainty of the distribution system, and it will bring about great influence on power grid planning, relay protection, power quality, scheduling management, the operation of the power grid and security of distribution network.

Collaborative beamforming in wireless sensor networks using a novel particle swarm optimization algorithm variant