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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. Data-driven Estimation of Probabilistic Constraints for Network-safe Distributed Energy Resource Control

   https://doi.org/10.1109/Allerton49937.2022.9929351  

   Jang, Sunho ; Ozay, Necmiye ; Mathieu, Johanna L. ( January 2022 , 58th Annual Allerton Conference on Communication, Control, and Computing)

   Distribution network safety should not be compromised when distributed energy resources (DERs) provide balancing services to the grid. Often DER coordination is achieved through an aggregator. Thus, it is necessary to develop network-safe coordination schemes between the distribution network operator (i.e., the utility) and the aggregator. In this work, we introduce a framework in which the utility computes and sends a constraint set on the aggregators’ control commands to the DERs. We propose a policy to adjust the charging/discharging power of distributed batteries, which allows them to be incorporated into the framework. Also, we propose a data-driven approach for the utility to construct a constraint set with probabilistic guarantees on network safety. The proposed approach allows the DERs to provide network- safe services without heavy communication requirements or invasion of privacy. Numerical simulations with distributed batteries and thermostatically controlled loads show that the proposed approach achieves the desired level of network safety and outperforms two benchmark algorithms. 

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5. Coordinating Distribution System Resources for Co-optimized Participation in Energy and Ancillary Service Transmission System Markets

   https://doi.org/10.23919/ACC.2019.8815242  

   Ji, Chengda ; Hajiesmaili, Mohammad ; Gayme, Dennice F. ; Mallada, Enrique ( July 2019 , American Control Conference)

   his work investigates the potential of using aggregate controllable loads and energy storage systems from multiple heterogeneous feeders to jointly optimize a utility's energy procurement cost from the real-time market and their revenue from ancillary service markets. Toward this, we formulate an optimization problem that co-optimizes real-time and energy reserve markets based on real-time and ancillary service market prices, along with available solar power, storage and demand data from each of the feeders within a single distribution network. The optimization, which includes all network system constraints, provides real/reactive power and energy storage set-points for each feeder as well as a schedule for the aggregate system's participation in the two types of markets. We evaluate the performance of our algorithm using several trace-driven simulations based on a real-world circuit of a New Jersey utility. The results demonstrate that active participation through controllable loads and storage significantly reduces the utility's net costs, i.e., real-time energy procurement costs minus ancillary market revenues. 

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