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

Osaru Agbonaye, Patrick Keatley, Ye Huang, Motasem Bani Mustafa, Neil Hewitt

2020Energies34 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

Congestion managementTariffDemand responseNetwork congestionValuation (finance)Computer scienceOperations researchPeak demandEnvironmental economicsDemand managementEconomicsDatabase transactionMicroeconomicsEconometricsMathematical optimizationComputer networkElectricityEngineeringMathematicsFinancePower (physics)PhysicsMacroeconomicsInternational tradeNetwork packetElectric power systemProgramming languageElectrical engineeringQuantum mechanicsSmart Grid Energy ManagementPower Line Communications and NoiseElectric Power System Optimization
Design, Valuation and Comparison of Demand Response Strategies for Congestion Management | Litcius