The analysis is based on a newly developed capacity expan-sion model incorporating both low carbon policy constraints anda full set of chronological flexibility constraints. The proposedmodel determines in a single optimization both the investmentcapacities for every type of generator in every region, and thecommitment and dispatch decisions for the 8760-hour operation.The investment decisions are linked directly to the dispatch de-cisions, and the hourly power balance optimizes commitmentand dispatch for thermal units applying the full set of flexibilityconstraints (minimal on/off time, ramping, minimal output level,reserve constraints), with respect to interprovincial transmissionlimitations, variations of renewables (from hourly to seasonal)and power demand. The optimization model also incorporateslow carbon policy constraints, such as RPS, renewable produc-tion tax credits, carbon taxes, and carbon cap-and-trade.The decision variables and flexibility constraints related tohourly system operation are formulated linearly in this paperadopting unit clustering techniques. This modeling formulationaccelerates markedly the computational speed, which makes themulti-region, 8760-hour simulation computationally feasible inthe single optimization model. The improved computationalspeed is important also for incorporation of full-year energybinding low carbon policies such as RPS and carbon cap-and-trade systems.Anovellinearmodelisdevelopedfortheoptimizedinvestment and operation of storage technologies. In makinginvestment decisions, we take into account diverse storage tech-nologies, differences for energy/power related costs, variationsof geographical areas and life-time watt-hours. In simulatingthe operation of storage systems, the model considers thecontributions of energy storage for both power balance andprovision of reserve. We also differentiate efficiency or lossfor the charging, discharging and self-discharge. Particularattention is directed to the relationship between the storagemodeling and renewable policies.Results indicate that the generation mix for thermal units willchange drastically when introducing flexibility constraints athigher renewable levels. With the increase of renewable pen-etration, the geographical allocation of renewable investmentswill be distributed more evenly across regions and the opti-mal investment of thermal power will shift from high efficiencylarge coal units, to more flexible mid-size coal fired units andgas-fired units. Solar power will be deployed only after the re-newable penetration reaches 55%. The carbon reduction cost at35% of RPS is acceptable compared to the social cost of carbon,while a further increase of renewable penetration is expensiveand sensitive to the price of energy storage.
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