Behavior-Aware Aggregation of Distributed Energy Resources for Risk-Aware Operational Scheduling of Distribution Systems

Mingyue He, Zahra Soltani, Mojdeh Khorsand (), Aaron Dock, Patrick Malaty and Masoud Esmaili
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Mingyue He: Department of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287, USA
Zahra Soltani: Department of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287, USA
Mojdeh Khorsand: Department of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287, USA
Aaron Dock: Salt River Project (SRP) Power and Water, 1500 N. Mill Ave., Tempe, AZ 85288, USA
Patrick Malaty: Salt River Project (SRP) Power and Water, 1500 N. Mill Ave., Tempe, AZ 85288, USA
Masoud Esmaili: Department of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287, USA

Energies, 2022, vol. 15, issue 24, 1-18

Abstract: Recently there has been a considerable increase in the penetration level of distributed energy resources (DERs) due to various factors, such as the increasing affordability of these resources, the global movement towards sustainable energy, and the energy democracy movement. However, the uncertainty and variability of DERs introduce new challenges for power system operations. Advanced techniques that account for the characteristics of DERs, i.e., their intermittency and human-in-the-loop factors, are essential to improving distribution system operations. This paper proposes a behavior-aware approach to analyze and aggregate prosumers’ participation in demand response (DR) programs. A convexified AC optimal power flow (ACOPF) via a second-order cone programming (SOCP) technique is used for system scheduling with DERs. A chance-constrained framework for the system operation is constructed as an iterative two-stage algorithm that can integrate loads, DERs’ uncertainty, and SOCP-based ACOPF into one framework to manage the violation probability of the distribution system’s security limits. The benefits of the analyzed prosumers’ behaviors are shown in this paper by comparing the optimal system scheduling with socially aware and non-socially aware approaches. The case study illustrates that the socially aware approach within the chance-constrained framework can utilize up to 43% more PV generation and improve the reliability and operation of distribution systems.

Keywords: AC optimal power flow; chance constraints; distributed energy resources; human-in-the-loop; risk aware; socially aware; sociodemographic information (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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