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

Abstract

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.

Agile Development Process and User-centric Data Driven Design for an Integrated Energy System

“…With the advancements in smart grid technologies, including advanced ICT infrastructure, IoT, DERs, domotics and local flexibility markets, have been driving innovative ideas for research and development. Researchers have been incorporating the demand flexibility from domestic consumers/prosumers through transactive energy frameworks with different scopes and aims [6], [9]. Moreover, retail electricity markets have already been identified as one of the most promising alternatives for ancillary services like overall system balancing [10], [11] and network congestion management [12], [13].…”