![]() The proposed model has a significant effect on reducing the total operation cost.Īs traditional fossil energy sources such as coal cause serious environmental pollution, it is a major trend to promote the construction of a ‘clean’ power system with new energy sources as the mainstay. According to the results obtained, PHESS has the most effect on minimization of wind spillage and total system operation cost, and when all flexibility options are evaluated, the total cost is significantly reduced, and no-load shedding occurs. Besides, various case studies carry out to demonstrate the effectiveness of the proposed framework in the IEEE 6-bus and IEEE 24-bus test system. With the proposed structure, an effective decision-making approach is presented that can meet all the requirements of power system operation, both technically and economically. ![]() In this respect, this study deals with the stochastic optimum operating problem in a power system with wind power plants (WPPs), where dynamic line rating (DLR), pumped hydro energy storage (PHESS), common energy storage (CES), demand response (DR) and electric vehicle (EV) aggregator (EVAGG) is considered as flexibility options. In this respect, considering the increasing number of RESs thanks to the incentives of more environmentally friendly sources, and new generation loads, it is vital to use flexibility options in order to ensure reliability in the power systems. The carbon emissions emitted from conventional energy sources and the possibility of extinction of these sources in the near future push the states to seek new energy alternatives, namely renewable energy sources (RESs). The performance of the method is tested on a real ADN. Then, in real-time operation, relying on a linear optimization problem, the second stage adjusts the power flexibility injection of a utility-scale battery energy storage system (ESS) to mitigate the imbalance at the PCC inherent in the above-mentioned uncertainties. The inter-temporal constraints and losses of the grid are accounted for by exploiting a linearized dynamic optimal power flow model, whereby the first stage is implemented as a linear scenario-based optimization problem. ![]() The first stage updates the power set-points of DERs considering their offer curves as well as the uncertainties stem from the short-term forecast errors of demand and renewable generation profiles. In this context, this paper presents a two-stage ADN management method to deliver, at the PCC, the power flexibility that the upper-layer grid operator would request minutes-ahead real-time operation. The power flexibility is defined as additional bi-directional active/reactive powers a resource can provide to the grid by adjusting its operating point. Relying on the power flexibility of distributed energy resources (DERs) located in an active distribution network (ADN), this ADN will be able to provide power flexibility to the upper-layer grid at their point of common coupling (PCC). Simulation of the New England system has validated that the proposed multi-time scale coordinated scheduling model could fully explore the distinguished power regulation speed and capacities of thermal power units, hydro pumped storages and batteries to effectively track WPL variations and achieve system economic operation simultaneously. 3) In the 15-minute ahead scheduling, based on day-ahead optimal power outputs of thermal units and the 1-hour ahead optimal outputs of pumped storage, the battery optimal power generation is obtained from an AC optimal power flow model solved by MATPOWER. 2) In the 1-hour ahead scheduling, based on power output of thermal units optimized in the day-ahead scheduling and the hourly forecasted WPL, the hydro pumped unit power outputs are optimally dispatched to minimize their operation cost. 1) in the day-ahead scheduling, based on the 24-hour ahead forecast data of Wind-Photovoltaic power and Load demand (WPL), the optimal power outputs of thermal power units are solved from a mix integer linear programming (MILP) model to achieve the minimal operation cost of thermal units. The scheduling model is composed of three time scales: the day-ahead scheduling, the 1-hour ahead scheduling and 15-minute ahead scheduling. In order to solve this problem, this paper proposed a multi-time scale coordinated scheduling model for the combined system of Wind power-Photovoltaic-Thermal generator-Hydro pumped storage-Battery (WPTHB) by taking advantages of their complementary operation characteristics. Grid connection of intermittent renewable energy such as wind power and photovoltaic results in challenges of keeping power balance for power system operation.
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