Low-carbon economic optimization scheduling in distributed energy systems considering carbon emission responsibility and demand response

Abstract

Incorporating carbon quotas into the carbon market has effectively curbed carbon emissions from the generation side of the energy system to certain extent. With abundant adjustable resources on the demand side, however, the distributed energy system (DES) has a more profound impact on carbon emissions reduction. Thus, to clarify the carbon emission responsibilities of multiple agents of load aggregators (LAs) within the distribution system, a bi-level optimization scheduling method is proposed in this study for economic low-carbon operation. This model utilizes Shapley value method to allocate carbon emission responsibilities of LAs, ensuring equitable carbon reduction benefits for the system. First, the carbon emission flow (CEF) model is applied to precisely calculate the carbon flow rates and intensities of nodes within the system. Second, the Shapley value method is adopted to fairly distribute the carbon emission responsibilities among LAs participating in the carbon market and demand response (DR) events, and then an incentive-based carbon trading model is introduced. Finally, a dual-layer model considering system and aggregator operational constraints is established to achieve the system’s optimal scheduling to minimize operational and carbon emission costs. A case study is conducted using an improved IEEE 33-node model incorporating distributed renewables with real measured data. The results demonstrate that utilizing demand-side regulation resources, multiple LAs’ coordination optimization efforts can effectively reduce system carbon emissions and total costs. With simultaneous participation in carbon trading and DR events, the optimal operation scheme for LAs achieves a 4.53% decrease in total costs and an 8.37% decrease in carbon emissions. This approach provides an effective solution and practical guidance for achieving low-carbon goals and enhancing the economic efficiency and stability of the DES.© 2017 Elsevier Inc. All rights reserved.

Keywords

• Carbon emission responsibility
• Shapley value
• Load aggregation agent
• Demand response
• Carbon trading