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A heterarchic hybrid coordination strategy for congestion management and market optimization using the DREAM framework

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Author: Kamphuis, I.G. · Wijbenga, J.P. · Veen, J.S. van der
Publisher: Institution of Engineering and Technology
Source:CIRED Workshop 2016. 14 June 2016 through 15 June 2016, CP686
IET Conference Publications
Identifier: 575657
Keywords: Charging (batteries) · Commerce · Economics · Electric energy storage · Heat pump systems · Heat storage · Heating · Pumps · Software agents · Virtual storage · Charging strategies · Congestion management · Coordination strategy · Electricity storages · Framework architecture · Heat and electricity · Micro-economic theory · Virtual power plants · Electric load shedding · ICT · MCS - Monitoring & Control Services · TS - Technical Sciences


Software agent-based strategies using micro-economic theory like PowerMatcher[1] have been utilized to coordinate demand and supply matching for electricity. Virtual power plants (VPPs) using these strategies have been tested in living lab environments on a scale of up to hundreds of households. So far, the coordination configuration of a VPP is fixed in these settings. The DREAM [2] framework architecture uses heterarchies to make parts of a VPP flexible in coordination strategy depending on the current operational grid status. In this way, a sub-VPP, serving one coordination objective, can decouple from and couple to an overarching VPP with another coordination objective dynamically. In this paper a grid congestion simulation with an overarching VPP coordinating demand and supply for electricity market optimization [3] and a sub-VPP reacting to a heat-pump congestion event in winter and a PV overproduction event in summer is described. The simulation was run in a static simulator [4]. The LVsegment consisted of 'flameless' residential areas with well-insulated homes with primarily heat pumps for heating and some renovated homes with local gas-fired co-generators of heat and electricity. Households additionally had solar cells, batteries and EV charging units. The goal of the additional coordination sub-VPP was to solve grid stability issues like congestion due to heat pump loads in winter and overproduction by PV in summer in this physical part locally, while the rest of the cluster remained unaffected and still optimizing for the commercial goal. The results were analyzed in terms of infringement of comfort parameters and performance in adapting the flexible load and generation. It appeared, substantial load shedding and load shifting of devices is possible to show the synergy in solving the grid stability issues evenly sharing the discomfort to the individual heating devices. By changing their charging strategy, the new algorithm also showed heat storage and electricity storage devices providing additional support.