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"Dispatching"
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Optimization of A comprehensive dispatching system based on ant colony algorithm and dynamic weight power dispatching strategy
In this study, we explored an optimization method for a comprehensive power dispatching system based on the fusion of ant colony algorithm and dynamic weight scheduling strategy. Firstly, the limitations of the existing scheduling system are introduced. Then, the proposed optimization methods are elaborated in detail, including the basic principle of ant colony algorithm, the design of dynamic weight scheduling strategy, and the fusion mode of the two. A large number of experimental data prove that this method is superior to the traditional scheduling method. Experimental results show that the integrated scheduling system optimization method based on ant colony algorithm and dynamic weight scheduling strategy significantly improves the scheduling efficiency and resource utilization. Specifically, the method reduces the average dispatch time by 20% and improves the resource utilization by 15% when dealing with large-scale power dispatching problems. This indicates that the method has high practical value and can provide strong support for the optimization of scheduling system in related fields.
Journal Article
Airline transport pilot 2023 test prep : study and prepare for your pilot and aircraft dispatcher FAA Knowledge Exams
\"Rely on the time-proven and dependable ASA Airline Transport Pilot Test Prep to prepare for your FAA Knowledge Exam. Test material is expertly organized into chapters based on subject matter and includes introductory text and illustrations, questions, answer choices, answers, explanations (for correct and incorrect answers), and references for further study. This topical study promotes understanding and aids recall to provide an efficient study guide. The ASA Test Prep includes the figures, legends, and full-color charts from the Airman Knowledge Testing Supplement so you'll be familiar with the information you'll be issued at the test center.\"-- Publisher's description.
BOOK
Review of Metaheuristic Optimization Algorithms for Power Systems Problems
Metaheuristic optimization algorithms are tools based on mathematical concepts that are used to solve complicated optimization issues. These algorithms are intended to locate or develop a sufficiently good solution to an optimization issue, particularly when information is sparse or inaccurate or computer capability is restricted. Power systems play a crucial role in promoting environmental sustainability by reducing greenhouse gas emissions and supporting renewable energy sources. Using metaheuristics to optimize the performance of modern power systems is an attractive topic. This research paper investigates the applicability of several metaheuristic optimization algorithms to power system challenges. Firstly, this paper reviews the fundamental concepts of metaheuristic optimization algorithms. Then, six problems regarding the power systems are presented and discussed. These problems are optimizing the power flow in transmission and distribution networks, optimizing the reactive power dispatching, optimizing the combined economic and emission dispatching, optimal Volt/Var controlling in the distribution power systems, and optimizing the size and placement of DGs. A list of several used metaheuristic optimization algorithms is presented and discussed. The relevant results approved the ability of the metaheuristic optimization algorithm to solve the power system problems effectively. This, in particular, explains their wide deployment in this field.
Journal Article
Three-stage Coordinated Dispatching of Wind Power-Photovoltaic-CSP-Thermal Power Combined Generation System
Aiming at the problem that the grid connection of intermittent renewable energy such as wind power and photovoltaics brings great uncertainty to the power system, a three-stage coordinated scheduling strategy of wind power-photovoltaic-concentrated solar energy is proposed. CSP Combined heat and power system. In the first stage, based on the day-ahead forecast data of wind power, photovoltaics and load, a “peak shaving” model of the combination of wind power-photovoltaic-CSP was established. In the second stage, according to the value of the remaining load after optimization in the first stage, a day-ahead economic dispatch model for thermal power units is established. In the third stage, based on the start-stop status and output of thermal power units in the first and second stages, the output of CSP plants and the intraday forecast data of wind power, photovoltaics, and loads, the establishment of an intraday thermal power joint regulation model and the establishment unit and CSP stations are established, and intraday scheduling plans are arranged. Case analysis shows that the proposed CHP system scheduling strategy can be supplemented by thermal power and CSP during load peak and trough periods, thereby minimizing the uncertainty brought by grid integration of wind power and photovoltaics. Introduce.
Journal Article
Research on the Optimal Economic Power Dispatching of a Multi-Microgrid Cooperative Operation
The economic power-dispatching model of a multi-microgrid is comprehensively established in this paper, considering many factors, such as generation cost, discharge cost, power-purchase cost, power sales revenue, and environmental cost. To construct this model, power interactions between the two microgrids and those between the micro- and main grids are considered. Furthermore, the particle swarm optimization (PSO) algorithm is utilized to solve the economic power-dispatching model. To validate the effectiveness of the proposed model as well as the solution algorithm, a practical project case is studied and discussed. In the case study, the impact of multiple scenarios is first analyzed. Then, the system operation economic costs under different scenarios are described in detail. Moreover, according to the optimization power-dispatching results of the multi-microgrid, power interactions between the two microgrids and those between the micro- and main grids are fully discussed.
Journal Article
Multi-Objective Order Scheduling via Reinforcement Learning
Order scheduling is of a great significance in the internet and communication industries. With the rapid development of the communication industry and the increasing variety of user demands, the number of work orders for communication operators has grown exponentially. Most of the research that tries to solve the order scheduling problem has focused on improving assignment rules based on real-time performance. However, these traditional methods face challenges such as poor real-time performance, high human resource consumption, and low efficiency. Therefore, it is crucial to solve multi-objective problems in order to obtain a robust order scheduling policy to meet the multiple requirements of order scheduling in real problems. The priority dispatching rule (PDR) is a heuristic method that is widely used in real-world scheduling systems In this paper, we propose an approach to automatically optimize the Priority Dispatching Rule (PDR) using a deep multiple-objective reinforcement learning agent and to optimize the weighted vector with a convex hull to obtain the most objective and efficient weights. The convex hull method is employed to calculate the maximal linearly scalarized value, enabling us to determine the optimal weight vector objectively and achieve a balanced optimization of each objective rather than relying on subjective weight settings based on personal experience. Experimental results on multiple datasets demonstrate that our proposed algorithm achieves competitive performance compared to existing state-of-the-art order scheduling algorithms.
Journal Article
Research on Safe-Economic Dispatch Strategy for Renewable Energy Power Stations Based on Game-Fairness Empowerment
The optimal dispatching of renewable energy power stations is particularly crucial in scenarios where the stations face energy rationing due to the large proportion of renewable energy integrated into the power system. In order to achieve safe, economical, and fair scheduling of renewable energy power stations, this paper proposes a two-stage scheduling framework. Specifically, in the initial stage, the maximum consumption space of renewable energy for the system can be optimized by optimizing the formulated safe-economic dispatch model. In the second stage, the fair allocation mechanism of renewable energy power stations is proposed based on the game-fairness empowerment approach. In order to obtain a comprehensive evaluation of renewable energy power stations, an evaluation index system is constructed considering equipment performance, output characteristics, reliability, flexibility, and economy. Subsequently, the cooperative game weighting method is proposed to rank the performance of renewable energy power stations as the basis for fair dispatching. Simulation results show that the proposed scheduling strategy can effectively ensure the priority of renewable energy power stations based on their comprehensive ranking, and improve the safety, economy, and fairness of power station participation in scheduling.
Journal Article
Combined Heat and Power Economic Dispatching within Energy Network using Hybrid Metaheuristic Technique
Combined heat and power (CHP) plants have opportunities to work as distributed power generation for providing heat and power demand. Furthermore, CHP plants contribute effectively to overcoming the intermittence of renewable energy sources as well as load dynamics. CHP plants need optimal solution(s) for providing electrical and heat energy demand simultaneously within the smart network environment. CHP or cogeneration plant operations need appropriate techno-economic dispatching of combined heat and power with minimising produced energy cost. The interrelationship between heat and power development in a CHP unit, the valve point loading effect, and forbidden working regions of a thermal power plant make the CHP economic dispatch’s (CHPED) objective function discontinuous. It adds complexity in the CHPED optimisation process. The key objective of the CHPED is operating cost minimisation while meeting the desired power and heat demand. To optimise the dispatch operation, three different algorithms, like Jaya algorithm, Rao 3 algorithm, and hybrid CHPED algorithm (based on first two) are adopted containing different equality and inequality restrictions of generating units. The hybrid CHPED algorithm is developed by the authors, and it can handle all of the constraints. The success of the suggested algorithms is assessed on two test systems; 5-units and 24-unit power plants.
Journal Article
Study of an Economic Dispatch by Fletcher and Broyden Method
In this paper, we will compare two methods of optimization of an objective function that derive from quasi-Newtonian methods. Both methods, the Fletcher and the Broyden method will be applied to a cost-effective dispatching on an IEEE 30 Bus system. We used two cases: the first one is to keep total power losses constant and the second case where a formulation of total power losses as a function of the power generated in linear form has been applied. The global optimal cost is practically the same for both methods, whereas for the second case, the Broyden method gives a better overall optimal cost and a minimization of total active losses of about 30 % for both methods A study of influence of the penalty factor on global optimal cost and total power losses was made.
Journal Article