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Modern power grids combine conventional generators with distributed energy resource (DER) generators in response to concerns over climate change and long-term energy security. Due to the intermittent nature of DERs, different types of energy storage devices (ESDs) must be installed to minimize unit commitment problems and accommodate spinning reserve power. ESDs have operational and resource constraints, such as charge and discharge rates or maximum and minimum state of charge (SoC). This paper proposes a linear programming (LP) optimization framework to maximize the unit-committed power for a specific optimum spinning reserve power for a particular power grid. Using this optimization framework, we also determine the total dispatchable power, non-dispatchable power, spinning reserve power, and arbitrage power using DER and ESD resource constraints. To describe the ESD and DER constraints, this paper evaluates several factors: availability, dispatchability, non-dispatchability, spinning reserve, and arbitrage factor. These factors are used as constraints in this LP optimization to determine the total optimal reserve power from the existing DERs. The proposed optimization framework maximizes the ratio of dispatchable to non-dispatchable power to minimize unit commitment problems within a specific range of spinning reserve power set to each DER. This optimization framework is implemented in the modified IEEE 34-bus distribution system, adding ten DERs in ten different buses to verify its efficacy.

This paper provides a strategy to identify layers and sub-layers of cyber-physical power systems (CPPS) and characterize their inter- and intra-actions. The physical layer usually consists of the power grid and protection devices whereas the cyber layer consists of communication, and computation and control components. Combining components of the cyber layer in one layer complicates the process of modeling intra-actions because each component has different failure modes. On the other hand, dividing the cyber layers into a large number of sub-layers may unnecessarily increase the number of system states and increase the computational burden. In this paper, we classify system layers based on their common, coupled, and shared functions. Also, interactions between the classified layers are identified, characterized, and clustered based on their impact on the system. Furthermore, based on the overall function of each layer and types of its components, intra-actions within layers are characterized. The strategies developed in this paper for comprehensive classification of system layers and characterization of their inter- and intra-actions contribute toward the goal of accurate and detailed modeling of state transition and failure and attack propagation in CPPS, which can be used for various reliability assessment studies., Comment: Accepted in Texas Power and Energy Conference (TPEC) 2023

Game theory-based approaches have recently gained traction in a wide range of applications, importantly in power and energy systems. With the onset of cooperation as a new perspective for solving power system problems, as well as the nature of power system problems, it is now necessary to seek appropriate game theory-based tools that permit the investigation and analysis of the behavior and relationships of various players in power system problems. In this context, this paper performs a literature review on coalitional game theory's most recent advancements and applications in power and energy systems. First, we provide a brief overview of the coalitional game theory's fundamental ideas, current theoretical advancements, and various solution concepts. Second, we examine the recent applications in power and energy systems. Finally, we explore the challenges, limitations, and future research possibilities with applications in power and energy systems in the hopes of furthering the literature by strengthening the applications of coalitional game theory in power and energy systems., Comment: Presented in Texas Power and Energy Conference (TPEC) 2023

This paper proposes an approach based on graph theory and combinatorial enumeration for sizing of movable energy resources (MERs) to improve the resilience of the electric power supply. The proposed approach determines the size and number of MERs to be deployed in a distribution system to ensure the quickest possible recovery of the distribution system following an extreme event. The proposed approach starts by generating multiple line outage scenarios based on fragility curves of distribution lines. The generated scenarios are reduced using the k-means method. The distribution network is modeled as a graph where distribution network reconfiguration is performed for each reduced line outage scenario. The combinatorial enumeration technique is used to compute all combinations of total MER by size and number. The expected load curtailment (ELC) corresponding to each locational combination of MERs is determined. The minimum ELCs of all combinations of total MER are used to construct a minimum ELC matrix, which is later utilized to determine optimal size and number of MERs. The proposed approach is validated through a case study performed on a 33-node distribution test system., Comment: 11 pages, 6 figures, presented in 2022 CIGRE Grid of the Future Symposium

This paper revisits the generation hosting capacity (HC) calculation approach to account for grid operational flexibility--the ability to reconfigure the system safely. In essence, the generation hosting capacity is determined against the set of limiting factors--voltage, thermal (conductor loading), reverse flow (at the feeder head, station transformer, or substation), and change in the voltage (due to sudden change in generation output)). Not that long ago, California Investor-Owned Utilities (IOUs) added a new criterion that does not allow reverse flow at the supervisory control and data acquisition (SCADA) points that can change the system configuration, aiming to prevent the potential transfer of reverse flow to an adjacent feeder. This new criterion intended to capture operational constraints as part of hosting capacity-known as hosting capacity with operational flexibility (OpFlex). This paper explores the shortfalls of such an approach and proposes performing actual transfer analysis when determining hosting capacity rather than implementing the OpFlex approach. Furthermore, we discuss the need for transition to determining hosting capacity profile (all intervals) rather than a flat line (one, worst performing interval) hosting capacity. A hosting capacity profile would inform the developers of interval-by-interval limits and opportunities, creating new opportunities to reach higher penetration of DERs at a lower cost. With technological and computational advancements, such an approach is neither out of implementation reach nor that computationally expensive. In return, far more DER can be interconnected once programmed not to violate certain generation profiles as part of the interconnection requirement, and utilities would be better informed of their actual operational flexibility, benefiting society overall.

This paper proposes a cooperative game theory-based under-frequency load shedding (UFLS) approach for frequency stability and control in power systems. UFLS is a crucial factor for frequency stability and control especially in power grids with high penetration of renewable energy sources and restructured power systems. Conventional UFLS methods, most of which are off-line, usually shed fixed amounts of predetermined loads based on a predetermined schedule which can lead to over or under curtailment of load. This paper presents a co-operative game theory-based two-stage strategy to effectively and precisely determine locations and amounts of loads to be shed for UFLS control. In the first stage, the total amount of loads to be shed, also referred to as deficit in generation or the disturbance power, is computed using the initial rate of change of frequency (ROCOF) referred to the equivalent inertial center. In the second stage, the Shapley value, one of the solution concepts of cooperative game theory, is used to determine load shedding amounts and locations. The proposed method is implemented on the reduced 9-bus 3-machine Western Electricity Coordinating Council (WECC) system and simulated on Real-time Digital Simulators (RTDS). The results show that the proposed UFLS approach can effectively return the system to normal state after disturbances.