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1. Power Loss-Aware Transactive Microgrid Coalitions under Uncertainty

   https://doi.org/10.3390/en13215782  

   Sadeghi, Mohammad; Mollahasani, Shahram; Erol-Kantarci, Melike (November 2020, Energies)

   null (Ed.)

   Peer-to-peer energy trading within microgrid (MG) communities emerges as a key enabler of the future transactive distribution system and the transactive electricity market. Energy trading within MGs refers to the idea that the surplus energy of one MG can be used to satisfy the demand of another MG or a group of MGs that form an MG community. These communities can be dynamically established through time, based on the variations of demand and supply of the interconnected MGs. In many modern MGs, Electric Vehicles (EVs) have been considered as a viable storage option due to their ease of use (plug-and-play) and their growing adoption rates by drivers. On the other hand, the dynamic nature of EVs escalates the uncertainty in the transactive distribution system. In this paper, we study the problem of energy trading among MGs and EVs with the aim of power loss minimization where there is uncertainty. We propose a novel Bayesian Coalition Game (BCG) based algorithm, which allows the MGs and EVs to reduce the overall power loss by allowing them to form coalitions intelligently. The proposed scheme is compared with a conventional coalitional game theory-based approach and a Q-learning based approach. Our results show significant improvement over other compared techniques. 

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2. Frequency Regulation with Heterogeneous Energy Resources: A Realization using Distributed Control

   https://doi.org/10.1109/TSG.2021.3071778  

   Anderson, Tor; Muralidharan, Manasa; Srivastava, Priyank; Haghi, Hamed Valizadeh; Cortes, Jorge; Kleissl, Jan; Martinez, Sonia; Washom, Byron (January 2021, IEEE Transactions on Smart Grid)

   null (Ed.)

   This paper presents one of the first real-life demonstrations of coordinated and distributed resource control for secondary frequency response in a power distribution grid. A series of tests involved up to 69 heterogeneous active distributed energy resources consisting of air handling units, unidirectional and bidirectional electric vehicle charging stations, a battery energy storage system, and 107 passive distributed energy resources consisting of building loads and solar photovoltaic systems. The distributed control setup consists of a set of Raspberry Pi end-points exchanging messages via an ethernet switch. Actuation commands for the distributed energy resources are obtained by solving a power allocation problem at every regulation instant using distributed ratio-consensus, primal-dual, and Newton-like algorithms. The problem formulation minimizes the sum of distributed energy resource costs while tracking the aggregate setpoint provided by the system operator. We demonstrate accurate and fast real-time distributed computation of the optimization solution and effective tracking of the regulation signal over 40 min time horizons. An economic benefit analysis confirms eligibility to participate in an ancillary services market and demonstrates up to $53k of potential annual revenue for the selected population of distributed energy resources. 

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3. Market mechanism to enable grid-aware dispatch of Aggregators in radial distribution networks

   Nazir, Nawaf; Almassalkhi, Mads (July 2022, 11TH BULK POWER SYSTEMS DYNAMICS AND CONTROL SYMPOSIUM)

   This paper presents a market-based optimization framework wherein Aggregators can compete for nodal capacity across a distribution feeder and guarantee that allocated flexible capacity cannot cause overloads or congestion. This mechanism, thus, allows Aggregators with allocated capacity to pursue a number of services at the whole-sale market level to maximize revenue of flexible resources. Based on Aggregator bids of capacity (MW) and network access price ($/MW), the distribution system operator (DSO) formulates an optimization problem that prioritizes capacity to the different Aggregators across the network while implicitly considering AC network constraints. This grid-aware allocation is obtained by incorporating a con- vex inner approximation into the optimization framework that prioritizes hosting capacity to different Aggregators. We adapt concepts from transmission-level capacity market clearing, utility demand charges, and Internet-like bandwidth allocation rules to distribution system operations by incorporating nodal voltage and transformer constraints into the optimization framework. Simulation based results on IEEE distribution networks showcase the effectiveness of the approach. 

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4. Fast and Secure Operation of Voltage Source Inverter based DERs using Model Predictive Droop Control

   https://doi.org/10.1109/ECCE.2018.8558323  

   Alhosaini, Waleed; Mahmud, Mohammad Hazzaz; Zhao, Yue (September 2018, Fast and Secure Operation of VSI based DERs using Model Predictive Droop Control)

   Reliability of the power grid can be improved by the use of microgrids (MGs) concept, which regulates the voltage and frequency at the point of common coupling (PCC) during normal and/or faulty conditions. Droop characteristics based hierarchical control strategies are commonly used in MGs, where power converters can operate in parallel. However, the need of multiple control loops not only adds complexity to the controller design, but also reduces the dynamic response of the system. In the future power system, grid-tied converters with fast dynamic response are desired to handle the uncertainties induced by high penetration of distributed energy resources. Therefore, this paper presents a novel model predictive control to ensure fast dynamic response of high power three-level converters in stand-alone operating mode as well as grid-tied operating mode. The proposed controller is applied to a MG which consists of a solar inverter connected in parallel with an energy storage system to the PCC, where a local load is tied. Both simulation and experimental results are presented to demonstrate robustness and the high dynamic performance of the proposed controller under rapidly changing atmospheric conditions and different grid operating modes. 

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5. Market Designs for Inertia Remuneration in Electricity Systems

   https://doi.org/10.1007/s40518-025-00265-w  

   Pauschert, Lukas; Sioshansi, Ramteen (December 2025, Current Sustainable/Renewable Energy Reports)

   Abstract Purpose of ReviewThe share of asynchronous inverter-based resources is increasing in many electricity systems, displacing synchronous generators. This leads to a decreasing level of system inertia, which threatens electricity-system stability. This dynamic raises the question of how to secure sufficient levels of inertia. One possibility is taking a market-based approach to incentivize the installation of inertia-providing equipment. To this end, this paper reviews market designs to reimburse inertia provision that are discussed in the literature. Recent FindingsWe find five distinct market designs to remunerate inertia that are discussed in the literature—bilateral negotiation, tendering, auctions, bonus systems, and integrating inertia-related constraints into energy-market models. In addition, there are other approaches that are not based on a market mechanism—penalties, regulatory obligations, self-provision by electricity-system operators, and redispatch. We examine current approaches that are employed by Ireland, Great Britain, Australia, and Germany, which demonstrate the real-world use of these theoretical designs. We assess the five market designs based on their advantages and disadvantages. SummaryWe find that there is not a single market design that outperforms the othersvis-à-visall market-performance indicators. Which market design is suited best for a specific use case depends upon the particular circumstances. A solely market-based solution may not be sufficient to secure electricity-system stability and should be enriched with regulatory guidelines to mitigate the risk of market failure. 

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