In　a　conventional　electricity　market,　trading　is　conducted　based　on　power　forecasts　in　the　day-ahead　market,　while　the　power　imbalance　is　regulated　in　the　real-time　market,　which　is　a　separate　trading　scheme.　With　large-scale　wind　power　connected　into　the　power　grid,　power　forecast　errors　increase　in　the　day-ahead　market　which　lowers　the　economic　efficiency　of　the　separate　trading　scheme.　This　paper　proposes　a　robust　unified　trading　model　that　includes　the　forecasts　of　real-time　prices　and　imbalance　power　into　the　day-ahead　trading　scheme.　The　model　is　developed　based　on　robust　optimization　in　view　of　the　undefined　probability　distribution　of　clearing　prices　of　the　real-time　market.　For　the　model　to　be　used　efficiently,　an　improved　quantum-behaved　particle　swarm　algorithm　(IQPSO)　is　presented　in　the　paper　based　on　an　in-depth　analysis　of　the　limitations　of　the　static　character　of　quantum-behaved　particle　swarm　algorithm　(QPSO).　Finally,　the　impacts　of　associated　parameters　on　the　separate　trading　and　unified　trading　model　are　analyzed　to　verify　the　superiority　of　the　proposed　model　and　algorithm.　©　2017　by　the　authors;　licensee　MDPI,　Basel,　Switzerland.