Multi - Agent Task Allocation to Minimize Costs of Energy Consumption in the Presence of a Price-Based Demand Response Program

2019 ◽  
Author(s):  
Ali B. Bahgat ◽  
Mohamed Lotfi ◽  
Omar M. Shehata ◽  
Elsayed I. Morgan ◽  
Joao P.S. Catalao
Keyword(s):  
Energy Consumption ◽  
Demand Response ◽  
Task Allocation ◽  
Demand Response Program ◽  
Multi Agent ◽  
Minimize Costs

Energy trading and control of islanded DC microgrid using multi-agent systems

2021 ◽  
Vol 17 (2) ◽  
pp. 113-128
Author(s):  
Diana Rwegasira ◽  
Imed Ben Dhaou ◽  
Masoumeh Ebrahimi ◽  
Anders Hallén ◽  
Nerey Mvungi ◽  
...  
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Dynamic Pricing ◽  
Energy Sector ◽  
Load Shedding ◽  
Dc Microgrid ◽  
Energy Trading ◽  
Development Framework ◽  
Demand Response Program ◽  
Multi Agent

The energy sector is experiencing a revolution that is fuelled by a multitude of factors. Among them are the aging grid system, the need for cleaner energy and the increasing demands on energy sector. The demand-response program is an advanced feature in smart grid that strives to match suppliers to their demands using price-based and incentive programs. The objective of the work is to analyse the performance of the load shedding technique using dynamic pricing algorithm. The system was designed using multi-agent system (MAS) for a DC microgrid capable of real-time monitoring and controlling of power using price-based demand-response program. As a proof of concept, the system was implemented using intelligent physical agents, Java Agent Development Framework (JADE), and agent simulation platform (REPAST) with two residential houses (non-critical loads) and one hospital (critical load). The architecture has been implemented using embedded devices, relays, and sensors to control the operations of load shedding and energy trading in residential areas that have no access to electricity. The measured results show that the system can shed the load with the latency of less than 600 ms, and energy cost saving with an individual houses by 80% of the total cost with 2USD per day. The outcome of the studies demonstrates the effectiveness of the proposed multi-agent approach for real-time operation of a microgrid and the implementation of demand-response program.

scholarly journals Agilometer: An Effective Implementation of Internet of Things for Agile Demand Response

2017 ◽  
Vol 2 (2) ◽  
pp. 58
Author(s):  
Muhammad Babar ◽  
J. Grela ◽  
A. Ozadowicz ◽  
P.H. Nguyen ◽  
Z. Hanzelka ◽  
...  
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Energy System ◽  
Evaluation Study ◽  
Energy Management Systems ◽  
Effective Implementation ◽  
Demand Response Program ◽  
Multi Agent ◽  
Functional Blocks ◽  
Market Driven

Transactive based control mechanism (TCM) needs the IoT environment to fully explore flexibility potential from the end-users to offer to involved actors of the smart energy system. On the other hand, many IoT based energy management systems are already available to a market. This paper presents an ap-proach to connect the current demand-driven (top-down) energy management system (EMS) with a market-driven (bottom-up) demand response program. To this end, this paper considers multi-agent system (MAS) to realize the approach and introduces the concept and standardize design of Agilometer. It is described as an elemental agent of the approach. Proposed by authors Agilometer consists of three different functional blocks, which are formulated as an IoT platform according to the LonWorks standard. Moreover, the paper also performs an evaluation study in order to validate the proposed concept and design.

Ant Colony Optimization for task allocation in Multi-Agent Systems

2013 ◽  
Vol 10 (3) ◽  
pp. 125-132 ◽  
Author(s):  
Lu Wang ◽  
Zhiliang Wang ◽  
Siquan Hu ◽  
Lei Liu
Keyword(s):  
Ant Colony Optimization ◽  
Task Allocation ◽  
Ant Colony ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

scholarly journals Techno-Economic Planning and Operation of the Microgrid Considering Real-Time Pricing Demand Response Program

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4597
Author(s):  
Zi-Xuan Yu ◽  
Meng-Shi Li ◽  
Yi-Peng Xu ◽  
Sheraz Aslam ◽  
Yuan-Kang Li
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Positive Impact ◽  
Environmental Aspects ◽  
Component Size ◽  
Cost Of Energy ◽  
Four Seasons ◽  
Demand Response Program ◽  
Real Time Pricing

The optimal planning of grid-connected microgrids (MGs) has been extensively studied in recent years. While most of the previous studies have used fixed or time-of-use (TOU) prices for the optimal sizing of MGs, this work introduces real-time pricing (RTP) for implementing a demand response (DR) program according to the national grid prices of Iran. In addition to the long-term planning of MG, the day-ahead operation of MG is also analyzed to get a better understanding of the DR program for daily electricity dispatch. For this purpose, four different days corresponding to the four seasons are selected for further analysis. In addition, various impacts of the proposed DR program on the MG planning results, including sizing and best configuration, net present cost (NPC) and cost of energy (COE), and emission generation by the utility grid, are investigated. The optimization results show that the implementation of the DR program has a positive impact on the technical, economic, and environmental aspects of MG. The NPC and COE are reduced by about USD 3700 and USD 0.0025/kWh, respectively. The component size is also reduced, resulting in a reduction in the initial cost. Carbon emissions are also reduced by 185 kg/year.

A persuasive multi-agent simulator to improve electrical energy consumption

2021 ◽  
pp. 1-15
Author(s):  
Fernanda P. Mota ◽  
Cristiano R. Steffens ◽  
Diana F. Adamatti ◽  
Silvia S. Da C Botelho ◽  
Vagner Rosa
Keyword(s):  
Energy Consumption ◽  
Electrical Energy ◽  
Electrical Energy Consumption ◽  
Multi Agent

scholarly journals Assessing the Value of Demand Response in Microgrids

2021 ◽  
Vol 13 (11) ◽  
pp. 5848
Author(s):  
Isaías Gomes ◽  
Rui Melicio ◽  
Victor M. F. Mendes
Keyword(s):  
Decision Making ◽  
Energy Consumption ◽  
Energy Storage ◽  
Case Studies ◽  
Demand Response ◽  
Storage Systems ◽  
Computer Application ◽  
Market Prices ◽  
Proper Formulation ◽  
Operation Case

This paper presents a computer application to assist in decisions about sustainability enhancement due to the effect of shifting demand from less favorable periods to periods that are more convenient for the operation of a microgrid. Specifically, assessing how the decisions affect the economic participation of the aggregating agent of the microgrid bidding in an electricity day-ahead market. The aggregating agent must manage microturbines, wind systems, photovoltaic systems, energy storage systems, and loads, facing load uncertainty and further uncertainties due to the use of renewable sources of energy and participation in the day-ahead market. These uncertainties cannot be removed from the decision making, and, therefore, require proper formulation, and the proposed approach customizes a stochastic programming problem for this operation. Case studies show that under these uncertainties and the shifting of demand to convenient periods, there are opportunities to make decisions that lead to significant enhancements of the expected profit. These enhancements are due to better bidding in the day-ahead market and shifting energy consumption in periods of favorable market prices for exporting energy. Through the case studies it is concluded that the proposed approach is useful for the operation of a microgrid.

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