Optimal Allocation of Distributed Generations Considering Demand Response and Multi-agent Benefits

2020 ◽  
Author(s):  
Jing Hu ◽  
Tong Ding ◽  
Hongkun Chen ◽  
Chaoyang Xiang
Keyword(s):  
Demand Response ◽  
Optimal Allocation ◽  
Distributed Generations ◽  
Multi Agent

Reliability based optimal allocation of distributed generations in transmission systems under demand response program

2019 ◽  
Vol 176 ◽  
pp. 105952 ◽  
Author(s):  
Hadi Chahkandi Nejad ◽  
Saeed Tavakoli ◽  
Noradin Ghadimi ◽  
Saman Korjani ◽  
Sayyad Nojavan ◽  
...  
Keyword(s):  
Demand Response ◽  
Optimal Allocation ◽  
Transmission Systems ◽  
Distributed Generations ◽  
Demand Response Program

Cross-provincial Cross-region Power Trading Optimization Modeling

2020 ◽  
Vol 13 (8) ◽  
pp. 1183-1189
Author(s):  
Jing-wen Chen ◽  
Yan Xiao ◽  
Hong-she Dang ◽  
Rong Zhang
Keyword(s):  
Network Flow ◽  
Optimal Allocation ◽  
Route Optimization ◽  
Regional Power ◽  
Power Resources ◽  
Gray Theory ◽  
Power Trading ◽  
Study Results ◽  
Multi Agent ◽  
Regional Economic Disparities

Background: China's power resources are unevenly distributed in geography, and the supply-demand imbalance becomes worse due to regional economic disparities. It is essential to optimize the allocation of power resources through cross-provincial and cross-regional power trading. Methods: This paper uses load forecasting, transaction subject data declaration, and route optimization models to achieve optimal allocation of electricity and power resources cross-provincial and cross-regional and maximize social benefits. Gray theory is used to predict the medium and longterm loads, while multi-agent technology is used to report the power trading price. Results: Cross-provincial and cross-regional power trading become a network flow problem, through which we can find the optimized complete trading paths. Conclusion: Numerical case study results has verified the efficiency of the proposed method in optimizing power allocation across provinces and regions.

scholarly journals Co-Simulation Framework for Optimal Allocation and Power Management of DGs in Power Distribution Networks Based on Computational Intelligence Techniques

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1648
Author(s):  
Marinko Barukčić ◽  
Toni Varga ◽  
Vedrana Jerković Jerković Štil ◽  
Tin Benšić
Keyword(s):  
Power System ◽  
Power Management ◽  
Computational Intelligence ◽  
Input Data ◽  
Optimization Problem ◽  
Optimal Allocation ◽  
Distribution Networks ◽  
Distributed Generations ◽  
Data Resolution ◽  
The Impact

The paper researches the impact of the input data resolution on the solution of optimal allocation and power management of controllable and non-controllable renewable energy sources distributed generation in the distribution power system. Computational intelligence techniques and co-simulation approach are used, aiming at more realistic system modeling and solving the complex optimization problem. The optimization problem considers the optimal allocation of all distributed generations and the optimal power control of controllable distributed generations. The co-simulation setup employs a tool for power system analysis and a metaheuristic optimizer to solve the optimization problem. Three different resolutions of input data (generation and load profiles) are used: hourly, daily, and monthly averages over one year. An artificial neural network is used to estimate the optimal output of controllable distributed generations and thus significantly decrease the dimensionality of the optimization problem. The proposed procedure is applied on a 13 node test feeder proposed by the Institute of Electrical and Electronics Engineers. The obtained results show a huge impact of the input data resolution on the optimal allocation of distributed generations. Applying the proposed approach, the energy losses are decreased by over 50–70% by the optimal allocation and control of distributed generations depending on the tested network.

A multi-agent based optimization of residential and industrial demand response aggregators

2019 ◽  
Vol 107 ◽  
pp. 472-485 ◽  
Author(s):  
Hessam Golmohamadi ◽  
Reza Keypour ◽  
Birgitte Bak-Jensen ◽  
Jayakrishnan R. Pillai
Keyword(s):  
Demand Response ◽  
Agent Based ◽  
Multi Agent ◽  
Industrial Demand

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.

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