With　the　transformation　of　distributed　energy　management　methods　such　as　microgrids　and　virtual　power　plants,　the　proliferation　of　distributed　energy　resources　presents　technical　challenges.　It　increases　management　complexity　for　power　system　operators.　A　controllable　aggregated　operation　model　of　distributed　energy　resources　can　facilitate　the　efficient　management　of　many　distributed　energy　resources.　Essentially,　the　feasible　region　of　the　aggregated　operation　model　is　the　Minkowski　sum　of　the　polyhedral　feasible　regions　of　all　distributed　energy　resources.　However,　calculating　the　Minkowski　sum　of　two　arbitrary　polyhedra　is　an　NP-hard　problem.　To　accurately　characterize　and　enhance　the　aggregation　flexibility　of　numerous　distributed　energy　resources,　this　paper　firstly　proposes　a　method　for　calculating　the　Minkowski　sum　in　a　general　convex　constraint　space.　The　method　uses　the　convex　hull　of　a　discrete　point　set　to　approximate　the　real　constraint　space　and　then　overlays　the　discrete　point　sets　using　the　Minkowski　sum.　A　discrete　point　set　optimization　algorithm　is　proposed　to　approximate　the　real　constraint　space　as　closely　as　possible.　This　point　set　is　high-dimensional　and　abstract,　but　it　represents　the　operational　characteristics　of　distributed　energy　resources,　which　we　define　as　the　characteristic　point　set.　Next,　a　selection　rule　for　the　characteristic　point　set　is　proposed,　which　can　improve　scheduling　flexibility,　increase　peak-shaving　capability,　and　reduce　the　computational　complexity　of　the　Minkowski　sum.　Furthermore,　an　algorithm　for　simplifying　the　characteristic　point　set　is　proposed,　ensuring　the　constraint　space　is　not　compromised.　Finally,　the　theoretical　rationale　for　using　the　characteristic　point　set　method　in　grid　scheduling　is　explained.　Numerical　simulation　results　demonstrate　that　this　method　has　great　potential　in　enhancing　system　aggregation　flexibility　and　computational　efficiency.　©　2025　Science　Press.　All　rights　reserved.