Self-organizing Prediction in Smart Grids through Delegate Multi-Agent Systems
نویسندگان
چکیده
This paper discusses a contribution to software and system engineering for smart grids, which comprises multi-agent application domain modeling and delegate multi-agent systems. In this contribution, domain models are software components – agents offering executable services – that become part of the multiagent software as it will be deployed. These domain models crystalize relevant power engineering knowhow and expertise, thus building bridges between the power engineering and the software engineering communities. The longevity of the real-world counterparts of these domain models ensures their technical feasibility and economic value. By mirroring real-world counterparts throughout their full life cycle, re-configurability is ensured and, in combination with the evaporate-and-refresh mechanisms of the delegate multi-agent systems, even becomes business-as-usual. The paper’s main contribution originates from research addressing self-organizing prediction of smart grid operations.
منابع مشابه
Robust Agent Based Distribution System Restoration with Uncertainty in Loads in Smart Grids
This paper presents a comprehensive robust distributed intelligent control for optimum self-healing activities in smart distribution systems considering the uncertainty in loads. The presented agent based framework obviates the requirements for a central control method and improves the reliability of the self-healing mechanism. Agents possess three characteristics including local views, decentr...
متن کاملApproach to Organizing the Functioning of Smart Elements in the Multi-Agent “Smart House” System
A research was conducted to form an approach to the design and implementation of a multi-agent control system of smart elements for a “Smart house”. The system was built on the example of three intelligent robots. In the architecture of the system under development, the main part is the subject-independent multi-agent kernel, which includes the following basic components: direct access service,...
متن کاملDecentralised Multi-Agent Reinforcement Learning for Dynamic and Uncertain Environments
Multi-Agent Reinforcement Learning (MARL) is a widely used technique for optimization in decentralised control problems. However, most applications of MARL are in static environments, and are not suitable when agent behaviour and environment conditions are dynamic and uncertain. Addressing uncertainty in such environments remains a challenging problem for MARL-based systems. The dynamic nature ...
متن کاملA Fuzzy Multi-Objective Optimization Model for Production and Consumption Management in Energy Micro Smart Grids
Electricity is one of the most important carriers of energy used in buildings. By introducing energy smart grids (SG) and energy micro smart grids (MSGs) alongside smart buildings, a good platform has been provided for optimal planning of electricity production and consumption. In this paper, an MSG consists of renewable resources, diesel generators and cell batteries in bidirectional connectio...
متن کاملFIoT: An agent-based framework for self-adaptive and self-organizing applications based on the Internet of Things
Billions of resources, such as cars, clothes, household appliances and even food are being connected to the Internet forming the Internet of Things (IoT). Subsets of these resources can work together to create new self-regulating IoT applications such as smart health, smart communities and smart homes. However, several challenging issues need to be addressed before this vision of applications b...
متن کامل