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1. Optimal Grid – Distributed Energy Resource Coordination: Distribution Locational Marginal Costs and Hierarchical Decomposition

   https://doi.org/10.1109/ALLERTON.2019.8919689  

   Andrianesis, Panagiotis ; Caramanis, Michael C. ( September 2019 , 57th Allerton Conference on Communication, Control, and Computing. Allerton, September 24-27, 2019)

   null (Ed.)

   We consider radial distribution networks hosting Distributed Energy Resources (DERs), including Solar Photo­voltaic (PV) and storage-like loads, such as Electric Vehicles (EVs). We employ short-run dynamic Distribution Locational Marginal Costs (DLMCs) of real and reactive power to co­optimize distribution network and DER schedules. Striking a balance between centralized control and distributed self­dispatch, we present a novel hierarchical decomposition ap­proach that is based on centralized AC Optimal Power Flow (OPF) interacting with DER self-dispatch that adapts to real and reactive power DLMCs. The proposed approach is designed to be highly scalable for massive DER Grid integration with high model fidelity incorporating rigorous network component dynamics and costs and reffecting them in DLMCs. We illustrate the use of an Enhanced AC OPF to discover spatiotemporally varying DLMCs enabling optimal Grid-DER coordination in­corporating congestion and asset (transformer) degradation. We employ an actual distribution feeder to exemplify the use of DLMCs as financial incentives conveying sufficient information to optimize Distribution Network and DER (PV and EV) operation, and we discuss the applicability and tractability of the proposed approach, while modeling the full complexity of spatiotemporal DER capabilities and preferences. 

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2. Grid-aware aggregation and realtime disaggregation of distributed energy resources in radial networks

   https://doi.org/10.1109/TPWRS.2021.3121215  

   Nazir, Nawaf ; Almassalkhi, Mads ( October 2021 , IEEE Transactions on Power Systems)

   Dispatching a large fleet of distributed energy resources (DERs) in response to wholesale energy market or regional grid signals requires solving a challenging disaggregation problem when the DERs are located within a distribution network. This manuscript presents a computationally tractable convex inner approximation for the optimal power flow (OPF) problem that characterizes a feeders aggregate DERs hosting capacity and enables a realtime, grid-aware dispatch of DERs for radial distribution networks. The inner approximation is derived by considering convex envelopes on the nonlinear terms in the AC power flow equations. The resulting convex formulation is then used to derive provable nodal injection limits, such that any combination of DER dispatches within their respective nodal limits is guaranteed to be AC admissible. These nodal injection limits are then used to construct a realtime, open-loop control policy for dispatching DERs at each location in the network to collectively deliver grid services. The IEEE-37 distribution network is used to validate the technical results and highlight various use-cases. 

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3. On Efficient Aggregation of Distributed Energy Resources

   https://doi.org/10.1109/CDC45484.2021.9683117  

   Gao, Zuguang ; Alshehri, Khaled ; Birge, John R. ( December 2021 , 2021 60th IEEE Conference on Decision and Control (CDC))

   The rapid growth of distributed energy resources (DERs) is one of the most significant changes to electricity systems around the world. Examples of DERs include solar panels, small natural gas-fueled generators, combined heat and power plants, etc. Due to the small supply capacities of these DERs, it is impractical for them to participate directly in the wholesale electricity market. We study in this paper an efficient aggregation model where a profit-maximizing aggregator procures electricity from DERs, and sells them in the wholesale market. The interaction between the aggregator and the DER owners is modeled as a Stackelberg game: the aggregator adopts two-part pricing by announcing a participation fee and a per-unit price of procurement for each DER owner, and the DER owner responds by choosing her payoff-maximizing energy supplies. We show that our proposed model preserves full market efficiency, i.e., the social welfare achieved by the aggregation model is the same as that when DERs participate directly in the wholesale market. 

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4. Hierarchical, Grid-Aware, and Economically Optimal Coordination of Distributed Energy Resources in Realistic Distribution Systems

   https://doi.org/10.3390/en13236399  

   Almassalkhi, Mads ; Brahma, Sarnaduti ; Nazir, Nawaf ; Ossareh, Hamid ; Racherla, Pavan ; Kundu, Soumya ; Nandanoori, Sai Pushpak ; Ramachandran, Thiagarajan ; Singhal, Ankit ; Gayme, Dennice ; et al ( December 2020 , Energies)

   null (Ed.)

   Renewable portfolio standards are targeting high levels of variable solar photovoltaics (PV) in electric distribution systems, which makes reliability more challenging to maintain for distribution system operators (DSOs). Distributed energy resources (DERs), including smart, connected appliances and PV inverters, represent responsive grid resources that can provide flexibility to support the DSO in actively managing their networks to facilitate reliability under extreme levels of solar PV. This flexibility can also be used to optimize system operations with respect to economic signals from wholesale energy and ancillary service markets. Here, we present a novel hierarchical scheme that actively controls behind-the-meter DERs to reliably manage each unbalanced distribution feeder and exploits the available flexibility to ensure reliable operation and economically optimizes the entire distribution network. Each layer of the scheme employs advanced optimization methods at different timescales to ensure that the system operates within both grid and device limits. The hierarchy is validated in a large-scale realistic simulation based on data from the industry. Simulation results show that coordination of flexibility improves both system reliability and economics, and enables greater penetration of solar PV. Discussion is also provided on the practical viability of the required communications and controls to implement the presented scheme within a large DSO. 

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5. A Hybrid Optimization and Deep Learning Algorithm for Cyber-resilient DER Control

   https://doi.org/10.1109/ISGT51731.2023.10066345  

   Panahazari, Mohammad ; Koscak, Matthew ; Zhang, Jianhua ; Hou, Daqing ; Wang, Jing ; Gao, David Wenzhong ( January 2023 , 2023 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT))

   With the proliferation of distributed energy resources (DERs) in the distribution grid, it is a challenge to effectively control a large number of DERs resilient to the communication and security disruptions, as well as to provide the online grid services, such as voltage regulation and virtual power plant (VPP) dispatch. To this end, a hybrid feedback-based optimization algorithm along with deep learning forecasting technique is proposed to specifically address the cyber-related issues. The online decentralized feedback-based DER optimization control requires timely, accurate voltage measurement from the grid. However, in practice such information may not be received by the control center or even be corrupted. Therefore, the long short-term memory (LSTM) deep learning algorithm is employed to forecast delayed/missed/attacked messages with high accuracy. The IEEE 37-node feeder with high penetration of PV systems is used to validate the efficiency of the proposed hybrid algorithm. The results show that 1) the LSTM-forecasted lost voltage can effectively improve the performance of the DER control algorithm in the practical cyber-physical architecture; and 2) the LSTM forecasting strategy outperforms other strategies of using previous message and skipping dual parameter update. 

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