Addressing demand response concentration under dynamic pricing

The impact of intelligent cyber-physical systems on the decarbonization of energy

“…In addition, artificial intelligence (AI) can be combined with CPS to add intelligent decision-making capability, evolving CPS into so-called intelligent CPS; herein shown in Figure 1. This integration of intelligent CPS in energy systems could not only change their design principle and operation regime, but also contribute to their transition in many ways; examples of such intelligent CPS potential benefits include energy efficiency enhancement 31 , operational flexibility in a dynamic environment 32 , resilience of critical infrastructure 29 and more. However, CPS had teething issues and selected examples and their impact will be outlined in this article to illustrates issues.…”

“…Key findings of the project include urban sensor data integration techniques 159 , design of reliable commu-nication networks for sensors 160 and the interaction between behavioural economics and transportation energy consumption 161 . For such a project, it is estimated that peak power demand can be reduced by 20% by deploying the dynamic pricing based on such a demand response 32 Enhanced Management of Industrial Complexes: Increasing the reusability and interoperability of CPS subsystems is another challenge for CPS-enabled large scale energy system applications. J-Park Simulator, a general cross-domain research platform that has been used for energy management of large-scale energy systems based on distributed knowledge graphs and interoperable agents, provides some useful insights 25,162,163 .…”

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

“…To solve this problem, [36] suggested a restriction in the maximum power drawn from each device. In another paper, the authors later proposed penalising the extent of flexibility utilised by the consumers' load [37]. Both the restriction or penalisation strategies are not desirable by the consumers and presents another set of problems for demand response implementation, including limiting the maximum amount of response that can be gotten from a pool of assets and hence reducing the business case.…”

Dynamic pricing for responsive demand to increase distribution network efficiency

“…The degree of flexibility is offered in pricing operations by focusing on dynamic tariffs, which are derived based on the actual costs from the power market. Paper [13] uses dynamic pricing to address the centralised demand response. It augments dynamic pricing with measure design to avoid demand response centralising caused by the combination of consumer's response to dynamic pricing.…”