Consensus-based Nodal Pricing Mechanism for Automated Demand Response Considering Congestion Management on Distribution Networks

Author(s):  
Gang Luo ◽  
Yijing Chen ◽  
Yue Zhao ◽  
Yujun He ◽  
Chao Gong ◽  
...  
Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6085
Author(s):  
Osaru Agbonaye ◽  
Patrick Keatley ◽  
Ye Huang ◽  
Motasem Bani Mustafa ◽  
Neil Hewitt

Decarbonisation of heat and transport will cause congestion issues in distribution networks. To avoid expensive network investments, demand flexibility is necessary to move loads from peak to off-peak periods. We provide a method and metric for assessing and selecting the optimal demand response strategy for a given network congestion scenario and applied it to a case study network in Coleraine, Northern Ireland. We proposed a Price Approximation/Mean Grouping strategy to deal with the issue of congestions occurring at the lowest-price period in real-time pricing schemes. The Mean Grouping strategy increased the average lowest-price hours from 1.32 to 3.76. We show that a three-cluster tariff is effective in solving medium congestion issues in Northern Ireland and could save consumers an average of £117/year on their heating bill. However, for networks with low headroom suffering from serious congestion issues, a smart control strategy is needed.


2019 ◽  
Vol 17 ◽  
pp. 100185 ◽  
Author(s):  
Mohammad Ali Fotouhi Ghazvini ◽  
Gianluca Lipari ◽  
Marco Pau ◽  
Ferdinanda Ponci ◽  
Antonello Monti ◽  
...  

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 318
Author(s):  
Niyam Haque ◽  
Anuradha Tomar ◽  
Phuong Nguyen ◽  
Guus Pemen

Capacity challenges are becoming more frequent phenomena in residential distribution networks with new forms of loads, distributed renewable energy resources (RES) and price-responsive applications. Different types of demand response programs have been introduced to tackle these challenges through iterative changes in price and/or contractual participations based on incentives. In this research, a dynamic network tariff-based demand response program is proposed to address congestion problems in low-voltage (LV) networks. The formulation takes advantage of the scalable architecture of the agent-based systems that allows local decision making with limited communication. Energy consumption schedules are developed on a day-ahead basis depending on the expected cost of overloading for a number of probable scenarios. The performance of the proposed approach has been tested through simulations in the unbalanced IEEE European LV test feeder. Simulation results reveal up to 82% reduction in congestion on a monthly basis, while maintaining the quality of supply in the network.


2018 ◽  
Vol 33 (2) ◽  
pp. 1496-1506 ◽  
Author(s):  
Kallisthenis I. Sgouras ◽  
Dimitrios I. Dimitrelos ◽  
Anastasios G. Bakirtzis ◽  
Dimitris P. Labridis

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