Distributed energy resources (DERs) can be integrated into a distribution system to provide grid services and enhance the reliability of the power system. For the provision of grid services, DERs, such as photovoltaic (PV) systems and battery energy storage systems (BESSs), need to be aggregated and properly controlled. Particularly, renewable energy resources are intermittent in nature and may require real-time monitoring and control strategies. Uncontrolled power injections from DERs in the DER-integrated distribution system can cause overvoltage and thermal issues, damaging the system components. This paper explores several existing DER aggregation and control strategies in the literature. Moreover, a framework for designing aggregation and control schemes for DERs in the distribution system to provide grid services is presented. In the framework, the distribution system is divided into multiple sections, and rule-based algorithms are used to manage the DERs. Furthermore, the effectiveness of DER aggregation in providing peak shaving and energy services is demonstrated in this paper.

Aggregation and Control of DERs in a Distribution System for the Provision of Grid Services

The high penetration of distributed energy resources (DERs) and the development of the energy internet bring a huge opportunity for distribution system. Although the individual DER capacity and visibility are small, aggregating various DERs can provide more flexibility for distribution system operation. This paper proposes a multi-period two-stage DER aggregation method for different types DERs considering the operating cost minimization. In the day-ahead stage, an aggregator determines the expected power trajectory of the aggregated DERs for energy trading and the optimal interval of flexibility reserve, which are in turn submitted to the distribution system operator (DSO). During the day, with the DSO dispatch signal, the aggregator re-optimizes the scheduling of the aggregated DERs to realize the power adjustment. To handle uncertainty, a stochastic optimization method with conditional value-at-risk is adopted, aiming to achieve the trade-off between power flexibility and operating cost reduction. The proposed method is compared with the conventional method which maximizes the flexibility reserve interval. The simulation results show that the proposed method can achieve a lower operating cost with only 0.6% infeasibility rate, verifying its high efficiency.

Multi-period Two-stage Stochastic DER Aggregation for Power Flexibility Reserve

EE75 The Economic Value of HPV Multi-Genotype Detection Technology

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Multi-period Two-stage Stochastic DER Aggregation for Power Flexibility Reserve

EE75 The Economic Value of HPV Multi-Genotype Detection Technology