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A multi-area power system requires coordination to enhance reliability and reduce operating costs. Economic dispatch in such systems is crucial because of the uncertainties associated with variable loads and the increasing penetration of renewable energy sources. This paper presents a hierarchical consensus algorithm designed to determine the economic dispatch in a multi-area power system, accounting for the uncertainties in load and renewable generation. The proposed algorithm, which utilizes distributed agents, operates across three levels. Level 1 coordinates all areas, while levels 2 and 3 form a leader–follower consensus algorithm for overall economic dispatch. Breadth-first search is employed to identify the leader agent within each area. To address the uncertainties in loads and renewable generation, Monte Carlo simulations are performed. The efficacy of the proposed method is validated using the IEEE 39-bus and 118-bus systems, as well as a realistic 1968-bus power system in Taiwan. The traditional equal lambda method is employed to verify that the proposed approach is suitable for multi-area power systems using distributed computation. [ABSTRACT FROM AUTHOR]

A new energy ship is being developed to address energy shortages and greenhouse gas emissions. New energy ships feature low operational costs and zero emissions. This study discusses the characteristics and development of solar-powered ships, wind-powered ships, fuel cell-powered ships, and new energy hybrid ships. Three important technologies are used for the power system of the new energy ship: new-energy spatio-temporal prediction, ship power scheduling, and Digital Twin (DT). Research shows that new energy spatio-temporal prediction reduces the uncertainty for a ship power system. Ship power scheduling technology guarantees safety and low-carbon operation for the ship. DT simulates the navigational environment for the new energy ship to characterize the boundary of the shipboard's new energy power generation. The future technical direction for new energy ship power systems is also being discussed. [ABSTRACT FROM AUTHOR]

Microgrid operation is challenging because the amount of electricity that is produced from renewables is uncertain and the inertia of distributed generation resources is very small. Energy storage systems can regulate energy, improve the reliability of the power systemand enhance the transient stability. This paper determines the optimal capacities of energy storage systems in an islanded microgrid that is composed of wind-turbine generators, photovoltaic arrays, and micro-turbine generators. The energy storage system can enhance the reliability of the microgrid and eliminate the unnecessary load shedding when a severe transient (such as a generator outage) occurs in the islanded microgrid. The studied problem is expressed as a multi-objective programming formulation, which is solved using an immunity-based algorithm. Four objective functions are optimized: minimum of energy storage capacity, minimum of load shedding, maximum of the lowest swing frequency, and minimum of the Customer Average Interruption Duration Index (CAIDI). These four objective functions are subject to both steady-state constraints and the transient-state equality constraint. The steady-state constraints include the total shed load limit, the feasible range of energy storage capacities while the transient-state equality constraint is expressed by the dynamic equation. The Pareto optimums are explored and optimality of the problem is investigated. The simulation results based on an islanded 15-bus microgrid show the applicability of the proposed method. [ABSTRACT FROM AUTHOR]

The unit commitment problem (UCP) is one of the key and fundamental concerns in the operation, monitoring, and control of power systems. Uncertainty management in a UCP has been of great interest to both operators and researchers. The uncertainties that are considered in a UCP can be classified as technical (outages, forecast errors, and plugin electric vehicle (PEV) penetration), economic (electricity prices), and "epidemics, pandemics, and disasters" (techno-socio-economic). Various methods have been developed to model the uncertainties of these parameters, such as stochastic programming, probabilistic methods, chance-constrained programming (CCP), robust optimization, risk-based optimization, the hierarchical scheduling strategy, and information gap decision theory. This paper reviews methods of uncertainty management, parameter modeling, simulation tools, and test systems. [ABSTRACT FROM AUTHOR]

Under-frequency load shedding (UFLS) prevents a power grid from a blackout when a severe contingency occurs. UFLS schemes can be classified into two categories—event-based and response-driven. A response-driven scheme utilizes 81L relays with pre-determined settings while an event-based scheme develops a pre-specified look-up table. In this work, an event-based UFLS scheme is presented for use in an offshore standalone power grid with renewables to avoid cascading outages due to low frequency protection of wind power generators and photovoltaic arrays. Possible "N-1" and "N-2" forced outages for peak and off-peak load scenarios in summer and winter are investigated. For each forced outage event, the total shed load is minimized and the frequency nadir is maximized using particle swarm optimization (PSO). In order to reduce the computation time, initialization and parallel computing are implemented using MATLAB/Simulink because all forced outage events and all particles in PSO are mutually independent. A standalone 38-bus power grid with two wind turbines of 2 × 2 MW and photovoltaics of 7.563 MW was studied. For each event, the proposed method generally obtains a result with a smaller shed load and a smaller overshoot frequency than the utility and existing methods. These simulation results verify that the proposed method is practically applicable in a standalone power system with penetration of renewables. [ABSTRACT FROM AUTHOR]

Energy losses are a fundamental issue in the electricity distribution sector, being an inevitable consequence of transporting energy from supplying sources to consumers' installations and are becoming one of the factors to be considered in planning and operation of electrical distribution networks. So, electrical distribution losses must be continuously monitored so that they are kept within acceptable levels to ensure the business profitability as well as the good power quality of supplied energy. In this context, this work introduces a modified methodology for technical losses calculation with the application of the concept of reduced equivalent networks, via definition of an Equivalent Operational Impedance, taking as a starting point the electrical network modeling in the Open Distribution System Simulator (OpenDSS). The losses calculation also considers customer's energy billing measurement data, measurements of injected energy and power factor at the feeder's coupling bus at the substation, also considering measurement campaigns to characterize the load consumption profiles for working days, Saturdays and Sundays. The proposed methodology disaggregates energy injections in billed energy, technical and non-technical losses parcels, and presents, as the results have demonstrated, a good precision in the proposed calculation procedures. [ABSTRACT FROM AUTHOR]

This paper presents a compensation method for unbalanced voltage through active and reactive power control by utilizing a smart inverter that improves the voltage unbalance index and detects an unbalanced state of voltage magnitude and phase, and thus enhances power quality by minimizing the voltage imbalance. First of all, this paper presents an analysis of a mathematical approach, which demonstrates that the conventional voltage unbalanced factor (VUF) using the symmetrical component cannot correctly detect the imbalanced state from index equations; and by only minimizing the VUF value, it cannot establish a balanced condition for an unbalanced state of the voltage profile. This paper further discusses that intermittent photovoltaic (PV) output power and diversified load demand lead to an unexpected voltage imbalance. Therefore, considering the complexity of unbalanced voltage conditions, a specific load and an PV profile were extracted from big data and applied to the distribution system model. The effectiveness of the proposed scheme was verified by comparing VUF indices and controlling the active and reactive power of a smart inverter through a numerical simulation. [ABSTRACT FROM AUTHOR]

Energy storage systems (ESSs) are essential to ensure continuity of energy supply and maintain the reliability of modern power systems. Intermittency and uncertainty of renewable generations due to fluctuating weather conditions as well as uncertain behavior of load demand make ESSs an integral part of power system flexibility management. Typically, the load demand profile can be categorized into peak and off-peak periods, and adding power from renewable generations makes the load-generation dynamics more complicated. Therefore, the thermal generation (TG) units need to be turned on and off more frequently to meet the system load demand. In view of this, several research efforts have been directed towards analyzing the benefits of ESSs in solving optimal unit commitment (UC) problems, minimizing operating costs, and maximizing profits while ensuring supply reliability. In this paper, some recent research works and relevant UC models incorporating ESSs towards solving the abovementioned power system operational issues are reviewed and summarized to give prospective researchers a clear concept and tip-off on finding efficient solutions for future power system flexibility management. Conclusively, an example problem is simulated for the visualization of the formulation of UC problems with ESSs and solutions. [ABSTRACT FROM AUTHOR]