Related papers: Comparative study of microgrid optimal scheduling …
With the rise of distributed energy resources and sector coupling, distributed optimization can be a sensible approach to coordinate decentralized energy resources. Further, district heating, heat pumps, cogeneration, and sharing concepts…
This study presents an integrated energy management strategy for cost optimization in multi-energy community microgrids (MGs). The proposed approach combines storage-based peak shaving, economic dispatch of diesel generators, and efficient…
Cloud resource allocation has emerged as a major challenge in modern computing environments, with organizations struggling to manage complex, dynamic workloads while optimizing performance and cost efficiency. Traditional heuristic…
An operational optimization strategy for microgrid energy storage systems (ESSs) is developed to address practical user-oriented application requirements, and its effectiveness is validated using real-world operational data. First, a…
This article introduces a modified simulated annealing optimization approach for automatically determining optimal energy management strategies in grid-connected, storage-augmented, photovoltaics-supplied prosumer buildings and…
Multi-task learning uses auxiliary data or knowledge from relevant tasks to facilitate the learning in a new task. Multi-task optimization applies multi-task learning to optimization to study how to effectively and efficiently tackle…
Smart grid as the cleaner alternative to the legacy power system can improve technical, economical, and environmental aspects of the system up to a considerable degree. In smart grids, Distributed Generation (DG) units; which play an…
This article focuses on the optimization of a complex system which is composed of several subsystems. On the one hand, these subsystems are subject to multiple objectives, local constraints as well as local variables, and they are…
Electricity, water, and gas systems are critical infrastructures that are sustaining our daily lives. This paper studies the joint operation of these systems through a proposed optimization model and explores the advantage of considering…
Design, architecture and deployment details of a decision support system engineered to minimize operating costs of compressor stations in a gas network are presented. The system employs standard simulation software for pipelines, combined…
In this paper, a new meta-heuristic algorithm, called beetle swarm optimization algorithm, is proposed by enhancing the performance of swarm optimization through beetle foraging principles. The performance of 23 benchmark functions is…
Renewable energy has attracted significant attention over the last decade, conceivably due to its environmental benefits and the recent drops in the development and deployment cost of the technology. The increase in renewable generation,…
We study the renewable energy generations in Hong Kong based on realistic meteorological data, and find that different renewable sources exhibit diverse time-varying and location-dependent profiles. To efficiently explore and utilize the…
Optimal management of thermal and energy grids with fluctuating demand and prices requires to orchestrate the generation units (GU) among all their operating modes. A hierarchical approach is proposed to control coupled energy nonlinear…
Power distribution in remote communities often depends on off-grid microgrids. In order to address the reliability challenges for these microgrids, we develop a mathematical model for topology design, capacity planning, and operation of…
In engineering optimization problems, multiple objectives with a large number of variables under highly nonlinear constraints are usually required to be simultaneously optimized. Significant computing effort are required to find the Pareto…
As database query processing techniques are being used to handle diverse workloads, a key emerging challenge is how to efficiently handle multi-way join queries containing multiple many-to-many joins. While uncommon in traditional…
In recent years, with the development of microarray technique, discovery of useful knowledge from microarray data has become very important. Biclustering is a very useful data mining technique for discovering genes which have similar…
Cloud computing is one of the most used distributed systems for data processing and data storage. Due to the continuous increase in the size of the data processed by cloud computing, scheduling multiple tasks to maintain efficiency while…
The study of robotic flocking has received considerable attention in the past twenty years. As we begin to deploy flocking control algorithms on physical multi-agent and swarm systems, there is an increasing necessity for rigorous promises…