scholarly journals Game-Based Energy Management Method for Hybrid RTG Cranes

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3589 ◽  
Author(s):  
Chen ◽  
Niu ◽  
Gu ◽  
Schofield
Keyword(s):  
Energy Management ◽  
Lithium Battery ◽  
Economic Effect ◽  
Container Terminals ◽  
Multi Agent System ◽  
Diesel Generator ◽  
Investment Cost ◽  
Multi Agent ◽  
Management Method ◽  
Continuous Work

In order to improve the energy efficiency and economic effect of conventional diesel-powered rubber-tired gantry (RTG) cranes in container terminals, various hybrid RTG cranes were studied. However, these current hybrid RTG cranes have several disadvantages, such as high initial investment cost and poor versatility of energy management methods. In this paper, a hybrid RTG crane consisting of a small-sized diesel generator (DG), a ternary material lithium battery, and a supercapacitor (SC) is studied, and a hybrid RTG crane energy management method based on game theory is proposed. The DG, lithium battery, and SC are modeled as three independent agents to participate in the game, and a multi-agent system (MAS) is established. During the RTG crane work process, agents achieve a coordinated and stable working state through the game, i.e., the Nash equilibrium. Three typical crane operation scenarios, the rated load, continuous work, and intermittent work, are simulated and studied. According to the results, combinations of the three devices can meet the power demand and system performance. The power of the DG in the hybrid system is small (only 20 kW), reducing fuel consumption and overall emissions during RTG crane operation.

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 An Embedded Platform for Testbed Implementation of Multi-Agent System in Building Energy Management System

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3655 ◽  
Author(s):  
Aryuanto Soetedjo ◽  
Yusuf Ismail Nakhoda ◽  
Choirul Saleh
Keyword(s):  
Energy Management ◽  
Management System ◽  
Fuzzy Logic Controller ◽  
Optimization Technique ◽  
Building Energy ◽  
Energy Management System ◽  
Multi Agent System ◽  
Agent System ◽  
Building Energy Management ◽  
Multi Agent

This paper presents a hardware testbed for testing the building energy management system (BEMS) based-on the multi agent system (MAS). The objective of BEMS is to maximize user comfort while minimizing the energy extracted from the grid. The proposed system implements a multi-objective optimization technique using a genetic algorithm (GA) and the fuzzy logic controller (FLC) to control the room temperature and illumination setpoints. The agents are implemented on the low cost embedded systems equipped with the WiFi communication for communicating between the agents. The photovoltaic (PV)-battery system, the air conditioning system, the lighting system, and the electrical loads are modeled and simulated on the embedded hardware. The popular communication protocols such as Message Queuing Telemetry Transport (MQTT) and Modbus TCP/IP are adopted for integrating the proposed MAS with the existing infrastructures and devices. The experimental results show that the sampling time of the proposed system is 16.50 s. Therefore it is suitable for implementing the BEMS in a real-time where the data are updated in an hourly or minutely basis. Further, the proposed optimization technique shows better results in optimizing the comfort index and the energy extracted from the grid compared to the existing methods.

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