In this paper, a mixedinteger Nonlinearprogramming (MINLP) for the short-term hydropower optimization problem considering operational constraints such as demand and startup costs, is presented. Since solving the MIN...
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The unit commitment (UC) problem has been extensively researched in the literature, which is typically formulated as a mixedintegerprogramming (MIP) problem. However, current studies lack effective methods to identi...
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With the large-scale new energy connected to the grid, its volatility and randomness bring challenges to the power system increasingly prominent. It is urgent to study how to reduce or avoid the wind and light cutting...
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Multi-objective optimization plays a significant role in optimizing the sizing and operation of Renewable Energy Communities (RECs), facilitating informed decision-making through precise Pareto curves. In this study, ...
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This study introduces a novel approach for redundancy allocation in series-parallel systems, incorporating component dependency via copula functions. By modeling these dependencies, we enhance the accuracy of system r...
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In this paper, a formulation for the Dial-a-Ride Problem with Meeting Points (DARPmp) is introduced. The problem consists of defining routes that satisfy trip requests between pick-up and drop-off points while complyi...
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This work addresses the problem of coordinating multiple autonomous vehicles. In particular, an optimal planner based on Model Predictive Control (MPC) is designed for each vehicle, using the linear parameter-varying ...
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This paper adopts a min-max-min two-layer robust optimization method to deal with the inherent uncertainty of renewable energy power generation units in integrated energy systems. First, the principles of wind power a...
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A new and efficient distributed algorithm based on multi-parameter quadratic programming (MPQP) is proposed in this paper to realize distributed voltage optimization of coupled HVDNs and MVDNs. With the boundary varia...
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Design, operation, and planning of Microgrids (MGs) have been enriched by advances in machine learning (ML) techniques and availability of real data. These advancements have significantly improved the accuracy of pred...
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