首页期刊导航|IEEE transactions on power systems: Institute of Electrical and Electronics Engineers transactions on power systems
期刊信息/Journal information
IEEE transactions on power systems: Institute of Electrical and Electronics Engineers transactions on power systems
Institute of Electrical and Electronics Engineers
Institute of Electrical and Electronics Engineers
季刊
0885-8950
IEEE transactions on power systems: Institute of Electrical and Electronics Engineers transactions on power systems/Journal IEEE transactions on power systems: Institute of Electrical and Electronics Engineers transactions on power systemsEI
查看更多>>摘要：The self-scheduling energy-intensive enterprise (EIE) has great potential to participate in demand response (DR) regulations. However, the multi-period self-scheduling model with the DR will bring computational burdens, since there are lots of binary decision variables. To address this challenge, this paper proposes a convex hull model for the self-scheduling model with the DR. Specifically, it presents the self-scheduling model of EIE as an integer programming (IP) model, then transforms this IP model into a dynamic programming (DP) model, and finally reformulates this DP model into a linear programming (LP) model. Furthermore, the proposed LP model is theoretically proved to be the convex hull of the self-scheduling EIE with the DR. Moreover, the benefits of the convex hull model are discussed, and extensive numerical experiments are carried out to demonstrate the excellent performance and efficiency of the convex hull model.
查看更多>>摘要：The uncertainties from distributed generators (DGs) and load behaviors pose more challenges to traditional dynamic equivalent modeling of the active distribution networks (ADNs). Parameter identification of ADN equivalent models is affected by various dynamic components with time-varying characteristics. Moreover, multi-solution issue, parameter mutation, and continuous outliers further complicate the problem. Therefore, a robust dynamic equivalent modeling approach for ADN with time-varying parameters is proposed in the paper. To effectively avoid the multi-solution issue, a parameter sensitivity and decoupling based dominant parameter discrimination scheme have been designed. Then, a time-varying parameter identification algorithm with the directional forgetting technique (DFT) is developed to continuously update model parameters, especially when only some parameters change. Furthermore, a continuous outlier detection and suppression approach is proposed to eliminate the impacts of low-quality measurements. Case studies and simulations on the actual and modified ADNs verified the effectiveness of the proposed approach.
查看更多>>摘要：Maintaining an accurate system model is one of the significant challenges in applications for distribution system monitoring and control. While keeping track of topology changes is important, keeping accurate model of the circuit elements is equally important, and it has not been emphasized in practice at distribution level. The current approach is to use constant parameters for line models. However, line impedances vary with the weather conditions and ampere loading of the line. This paper investigates the impact of line impedance variations and its impact on distribution system state estimation (DSSE). Test results show that the effect of the parameter changes is considerable on distribution system state estimation accuracy. The paper proposes a method to tune line models periodically in order to address this issue.
查看更多>>摘要：This paper proposes an analytic neural network Gaussian process (NNGP)-based chance-constrained real-time voltage regulation method for active distribution systems with photovoltaics (PVs), batteries, and electric vehicles (EVs). NNGP can utilize historical measurement data to achieve real-time probabilistic node voltage estimation through Bayesian inference. Then, NNGP is fully analytically embedded into the optimal power flow model to perform voltage regulation and adapt to various topological changes. The uncertainties of voltage estimations are easily considered via the chance constraint, and it has been shown that the adoption of this chance constraint can significantly improve the reliability of voltage regulation under various scenarios. The comparison results with other methods, carried out on a real 759-node distribution system located in western Colorado, U.S., show that the proposed method can achieve accurate voltage estimation across different topologies and reliably perform voltage regulation considering PVs, batteries, and EVs.
Francesco GeriniElena VagnoniRachid CherkaouiMario Paolone...
2050-2060页
查看更多>>摘要：This paper proposes a methodology to optimize the dispatch and reserve between multiple units in a Hydroelectric Power Plant (HPP) that makes use of the Hydraulic Short Circuit (HSC) operating mode. HSC allows for the simultaneous generation and pumping from different units of the same plant. The objective of optimal dispatching is to maximize efficiency and reduce the number of start and stop of the machines. We first introduce the original Mixed Integer Programming (MIP) problem and discuss its computational complexity. Then, we propose an optimal dispatching algorithm obtained by efficiently solving a set of convex optimization sub-problems, as opposed to the original MIP. The methodology is applied and validated in two different cases, including one real study case in France. The study cases demonstrate the ability to include HSC in short-term dispatch, consider future set-points for optimizing power trajectory, and find the optimal solution to the HPP dispatching problem while guaranteeing a computationally tractable approach.
查看更多>>摘要：This paper proposes a frequency security-constrained optimal restoration scheduling framework for active distribution networks (FRSDN). The approach leverages distributed energy resources (DERs), particularly the inverter-interfaced renewable energy generators (IIREGs). First, incorporating the equivalent aggregated frequency response from both the governors of synchronous thermal generators (TGs) and the virtual synchronous control manner of IIREGs, linearized and conservative constraints for dynamic frequency metrics are derived, in particular for load-pickup process in renewable-based distribution system restoration (DSR). Next, a sequential dynamic boundary identification model (SDIDM) is developed to identify the dynamic boundaries and the involved generator types of networked microgrids (MGs), which facilitates the precise imposition of frequency security constraints by conserving the serial numbers of dynamically clustered networked MGs. Finally, the frequency-constrained DSR method is formulated as a three-layer robust mixed-integer linear programming (MILP) problem and solved by the column-and-constraint generation (C&CG) algorithm. Numerical results on a modified IEEE 123-node system are leveraged to demonstrate the effectiveness and superiorities of the proposed method. It is manifested that the frequency responses of all boundary-aware MGs could be confined to secure conditions by implementing the proposed FRSDN.
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