scholarly journals Design, Valuation and Comparison of Demand Response Strategies for Congestion Management

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6085
Author(s):  
Osaru Agbonaye ◽  
Patrick Keatley ◽  
Ye Huang ◽  
Motasem Bani Mustafa ◽  
Neil Hewitt
Keyword(s):  
Northern Ireland ◽  
Demand Response ◽  
Distribution Networks ◽  
Congestion Management ◽  
Response Strategy ◽  
Response Strategies ◽  
Grouping Strategy ◽  
Smart Control ◽  
Pricing Schemes

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.

Should I stay or should I go? Customers’ reactions faced with the deterioration of a business relationship

2016 ◽  
Vol 31 (1) ◽  
pp. 47-58 ◽  
Author(s):  
David Vidal ◽  
Hervé Fenneteau ◽  
Gilles Paché
Keyword(s):  
Degradation Process ◽  
Response Strategy ◽  
Business Relationship ◽  
Structured Interviews ◽  
Content Type ◽  
Staff Members ◽  
Response Strategies ◽  
Customer Commitment ◽  
Business Sectors

Purpose – This paper aims to develop a framework helping managers to understand reactions, adopting the supplier perspective, and starting from the idea that the outcome of the degradation process is mainly determined by customers’ reactions. Inter-organisational relationships are sometimes subject to degradation. When incidents arise, and relationship attractiveness decreases, its evolution becomes uncertain. Design/methodology/approach – A case study carried out with a large French industrial company (FabIndus) specialised in the production of supplies destined to a large variety of business sectors. In all, 26 semi-structured interviews were conducted with staff members of FabIndus and clients’ representatives identified as having recently been confronted with deterioration in their relationship. Findings – The paper finds that customers’ reactions vary according to the nature of the business relationship and the customer commitment when degradation begins. Using two types of commitment and the exit–voice–loyalty–neglect model, it is possible to identify four types of reactions in the situation of the deterioration of a relationship. For each one of the reactions, the paper defines the response strategy that suppliers may take on. Originality/value – The paper underlines the importance of a segmented view of business behaviours faced with the deterioration of a relationship. This can be helpful to elaborate differentiated response strategies, to avoid mutual misunderstandings.

scholarly journals Fair and Balance Demand Response application in Distribution Networks

2020 ◽  
Vol sceeer (3d) ◽  
pp. 139-151
Author(s):  
Ibrahim Al-Kharsan ◽  
Ali Marhoon ◽  
Jawad Mahmood
Keyword(s):  
Demand Response ◽  
Financial Incentives ◽  
Real Data ◽  
Distribution Networks ◽  
Response Strategy ◽  
Smart Meters ◽  
Consumption Behavior ◽  
Direct Load Control ◽  
Distribution Transformers ◽  
Modern Solution

The unprogrammed penetration for the loads in the distribution networks make it work in an unbalancing situation that leads to unstable operation for those networks. the instability coming from the imbalance can cause many serious problems like the inefficient use of the feeders and the heat increased in the distribution transformers. The demands response can be regarded as a modern solution for the problem by offering a program to decreasing the consumption behavior for the program's participators in exchange for financial incentives in specific studied duration according to a direct order from the utility. The paper uses a new suggested algorithm to satisfy the direct load control demand response strategy that can be used in solving the unbalancing problem in distribution networks. The algorithm procedure has been simulated in MATLAB 2018 to real data collected from the smart meters that have been installed recently in Baghdad. The simulation results of applying the proposed algorithm on different cases of unbalancing showed that it is efficient in curing the unbalancing issue based on using the demand response strategy.

scholarly journals Residential Demand Response Strategy Based on Deep Deterministic Policy Gradient

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 660
Author(s):  
Chunyu Deng ◽  
Kehe Wu
Keyword(s):  
Demand Response ◽  
Electricity Market ◽  
Power Distribution ◽  
Peak Load ◽  
Electricity Consumption ◽  
Response Strategy ◽  
Response Strategies ◽  
Policy Gradient ◽  
Incentive Policies ◽  
Residential Demand

With the continuous improvement of the power system and the deepening of electricity market reform, the trend of users’ active participation in power distribution is more and more significant. Demand response has become the promising focus of smart grid research. Providing reasonable incentive strategies for power grid companies and demand response strategies for customers plays a crucial role in maximizing the benefits of different participants. To meet different expectations of multiple agents in the same environment, deep reinforcement learning was adopted. The generative model of residential demand response strategy under different incentive policies can be trained iteratively through real-time interactions with the environmental conditions. In this paper, a novel optimization model of residential demand response strategy, based on a deep deterministic policy gradient (DDPG) algorithm, was proposed. The proposed work was validated with the actual electricity consumption data of a certain area in China. The results showed that the DDPG model could optimize residential demand response strategy under certain incentive policies. In addition, the overall goal of peak load-cutting and valley filling can be achieved, which reflects promising prospects of the electricity market.

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