Abstract

The carbon allowance trading mechanism provides an economic basis to facilitate emission reductions for market participants. As a compliance mechanism, allowance-based emission control demands emitter to surrender the same amount of carbon allowances as it emits during the accounting period, the duration of which is often set to one year by the administrators. This requires emitters to determine the upper limit of annual emissions and allocate it to each day based on the current carbon price to minimize their overall operating costs over the longer carbon accounting period. This paper proposes a low-carbon economic dispatch for IES with CCUS considering multi-time-scale allocation of carbon allowance. In the upper level, a scenario-based stochastic optimization is adopted to decide the annual allowance and complete the allocation from year to month and then from month to day. The lower level is a Wasserstein ambiguity set-based two-stage distributionally robust optimization (TSDRO) model to find the optimal dispatch strategy of each day. The uncertainty from the long-term available renewable energy resources and user demands and from the short-term forecasting errors is both considered. Simulation results show that the proposed model can realize reasonable carbon allocation and decrease the annual operation costs.

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