A multi-agent system for energy management in smart microgrids with distributed energy storage and demand response

2016 ◽  
Author(s):  
H S V S Kumar Nunna ◽  
Dipti Srinivasan
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Demand Response ◽  
Multi Agent System ◽  
Distributed Energy ◽  
Agent System ◽  
Distributed Energy Storage ◽  
Multi Agent

Fuzzy-Based Multi-Agent System for Distributed Energy Management in Smart Grids

2016 ◽  
Vol 24 (05) ◽  
pp. 781-803 ◽  
Author(s):  
Bharat Menon Radhakrishnan ◽  
Dipti Srinivasan ◽  
Rahul Mehta
Keyword(s):  
Energy Management ◽  
Smart Grids ◽  
Test System ◽  
Small Scale ◽  
Multi Agent System ◽  
Distributed Energy ◽  
Agent System ◽  
Renewable Sources ◽  
Distributed Energy Management ◽  
Multi Agent

Energy Management Systems have become an imperative aspect of smart grids, owing to the enormous challenges imposed due to real-time pricing, distributed generation and integration of intermittent renewables. Due to the uncertainty associated with renewable sources and prominent fluctuations in the load demand, it is extremely important to maintain the overall energy balance in such grids. In this paper, the distributed energy management is achieved using a Multi-agent System which provides a flexible and reliable solution to control and manage smart grids. Adaptive fuzzy systems are designed to instill intelligent decision making capability in the agents of multi-agent system. When renewable sources are inadequate, the sustainability of the system is not guaranteed and multi-agent system is capable of deciding the mode of operation such that the system reliability and performance is not compromised. The proposed algorithm maintains power balance in the system and also sustains desired values for the State of Charge of storage units in order to guarantee extended battery life. The Energy management system also implements a cost optimization algorithm based on the Particle Swarm Optimization technique, to minimize operating costs and maximize profits earned by the grid. The proposed energy management algorithm is tested and validated on a practical test system which inherits most of the features of a small-scale smart grid.

scholarly journals A Multi-Agent-Based Optimization Model for Microgrid Operation Using Dynamic Guiding Chaotic Search Particle Swarm Optimization

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3286
Author(s):  
Jicheng Liu ◽  
Fangqiu Xu ◽  
Shuaishuai Lin ◽  
Hua Cai ◽  
Suli Yan
Keyword(s):  
Particle Swarm Optimization ◽  
Energy Storage ◽  
Demand Response ◽  
Optimization Model ◽  
Particle Swarm ◽  
Multi Agent System ◽  
Agent System ◽  
Swarm Optimization ◽  
Chaotic Search ◽  
Multi Agent

The optimal operation of microgrids is a comprehensive and complex energy utilization and management problem. In order to guarantee the efficient and economic operation of microgrids, a three-layer multi-agent system including distributed management system agent, microgrid central control agent and microgrid control element agent is proposed considering energy storage units and demand response. Then, based on this multi-agent system and with the objective of cost minimization, an operation optimization model for microgrids is constructed from three aspects: operation cost, environmental impact and security. To solve this model, dynamic guiding chaotic search particle swarm optimization is adopted and three scenarios including basic scenario, energy storage participation and demand response participation are simulated and analyzed. The results show that both energy storage unit and demand response can effectively reduce the cost of microgrid, improve the operation and management level and ensure the safety and stability of power supply and utilization.

Implementation of an energy management algorithm in DC MGs using multi‐agent system

2018 ◽  
Vol 29 (4) ◽  
pp. e2790 ◽  
Author(s):  
Emad G. Shehata ◽  
Maged S. Gaber ◽  
Khalil Ali Ahmed ◽  
Gerges M. Salama
Keyword(s):  
Energy Management ◽  
Multi Agent System ◽  
Agent System ◽  
Management Algorithm ◽  
Multi Agent

Renewable Energy Management with a Multi-Agent System

2015 ◽  
Vol 4 (3) ◽  
pp. 49-59
Author(s):  
Wahiba Ben Abdessalem ◽  
Sami Karaa ◽  
Amira S. Ashour
Keyword(s):  
Renewable Energy ◽  
Energy Management ◽  
Energy Generation ◽  
Multi Agent System ◽  
Renewable Electricity ◽  
Agent System ◽  
World Energy ◽  
Multi Agent ◽  
Electric Generation ◽  
Renewable Energy Generation

Renewable energy generation (Wind, solar …) is rising rapidly around the world. Energy storage is being today realistic with some kind of variable renewable electricity sources such as the Pumped Hydraulic Storage (PHS). The incorporation of the PHS requires different policies since there are a variety of electric generation technologies that can be exploited commonly with the PHS. The energy management system, the scheduling of the generation units is a crucial problem for which adequate solutions can optimize the energy supply. This paper focuses on the applicability of the PHS technology in the development of renewable energy generation in Tunisia. This paper proposes also a multi agent system that can be implemented to simulate the exploitation of the PHS, commonly with other energy sources: conventional energy, wind energy, photovoltaic energy etc.

scholarly journals A Demand-Response Scheme Using Multi-Agent System for Smart DC Microgrid

2019 ◽  
Vol 10 (1) ◽  
pp. 48-68 ◽  
Author(s):  
Diana Severine Rwegasira ◽  
Imed Saad Ben Dhaou ◽  
Aron Kondoro ◽  
Anastasia Anagnostou ◽  
Amleset Kelati ◽  
...  
Keyword(s):  
Demand Response ◽  
Dynamic Pricing ◽  
Supply And Demand ◽  
Load Shedding ◽  
Multi Agent System ◽  
Solar Panels ◽  
Remote Communities ◽  
Agent System ◽  
Dc Microgrid ◽  
Multi Agent

This article describes a framework for load shedding techniques using dynamic pricing and multi-agent system. The islanded microgrid uses solar panels and battery energy management system as a source of energy to serve remote communities who have no access to the grid with a randomized type of power in terms of individual load. The generated framework includes modeling of solar panels, battery storage and loads to optimize the energy usage and reduce the electricity bills. In this work, the loads are classified as critical and non-critical. The agents are designed in a decentralized manner, which includes solar agent, storage agent and load agent. The load shedding experiment of the framework is mapped with the manual operation done at Kisiju village, Pwani, Tanzania. Experiment results show that the use of pricing factor as a demand response makes the microgrid sustainable as it manages to control and monitor its supply and demand, hence, the load being capable of shedding its own appliances when the power supplied is not enough.

Sign in / Sign up

Export Citation Format

Share Document