New analytical approach revolutionizes reliability evaluation of power systems with renewable energy
Higher Education Press
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s1, s2, …, s2N: contingencies; fLS(s1), fLS(s2), …, fLS(s2N): the load shedding of contingencies s1, s2, …, s2N; fLS(s): the load shedding of the contingency s; CT: the weight of the load at each node; Pd: the load demand; LOLP: the loss of load probability; EDNS: expected demand not supplied.
view moreCredit: Longxun Xu et al.
In a recent study published in Engineering, a team of researchers led by Bo Hu and Changzheng Shao from Chongqing University in China has introduced a novel method for evaluating the real-time dynamic reliability of composite power systems integrated with renewable energy sources (RES). The research addresses the challenges posed by the uncertainties associated with RES, which have been a significant obstacle in ensuring the stable and reliable operation of power grids.
The increasing integration of RES, such as wind and solar power, into the power grid has brought about concerns regarding power imbalance and load shedding due to their inherent uncertainties. The new approach aims to provide a more accurate and timely assessment of the operational reliability of power systems, thereby guiding economic dispatch and reducing risks.
The proposed method consists of two key components: a uniform design (UD)-based contingency screening and a modified stochastic response surface method (mSRSM). The contingency screening technique is designed to identify critical contingencies while considering the uncertainties associated with RES and load variations. By reducing the number of contingencies that need to be analyzed, the computational complexity of the reliability evaluation is significantly decreased.
The mSRSM, on the other hand, is used to construct analytical functions that map the load shedding to the load and RES generation for the selected contingencies. This allows for a more efficient assessment of reliability when the load and RES change, eliminating the need for laborious optimal power flow (OPF) calculations.
The research team validated their approach through case studies on three power systems: the Roy Billinton Test System (RBTS), the Reliability Test System (RTS)-79, and the RST-96. The results demonstrated that the proposed method not only exhibited high accuracy in predicting reliability indices such as the loss of load probability (LOLP) and the expected demand not supplied (EDNS), but also significantly reduced the computational time compared to traditional methods.
This research represents a significant step forward in the field of power system reliability evaluation. By providing a more accurate and efficient means of assessing the reliability of power systems with RES, the new approach could have far-reaching implications for the future development and operation of sustainable power grids. It offers a practical solution for power system operators to better manage the uncertainties associated with renewable energy integration and ensure the reliable supply of electricity to consumers.
The paper “A Fully Analytical Approach for the Real-Time Dynamic Reliability Evaluation of Composite Power Systems with Renewable Energy Sources,” authored by Longxun Xu, Bo Hu, Changzheng Shao, Kaigui Xie, Congcong Pan, Heng-Ming Tai, Wenyuan Li. Full text of the open access paper: https://doi.org/10.1016/j.eng.2024.09.023. For more information about the Engineering, follow us on X (https://twitter.com/EngineeringJrnl) & like us on Facebook (https://www.facebook.com/EngineeringJrnl).
Journal
Engineering
Article Title
A Fully Analytical Approach for the Real-Time Dynamic Reliability Evaluation of Composite Power Systems with Renewable Energy Sources
New advances in optimization scheduling of industrial park energy systems with hybrid energy storage
Higher Education Press
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(a) IPES-HES; (b) reference system. Egrid: electricity of purchase or sales in a IPES-HES; PPV: power generation of PVs; Pbat: power of lithium batteries; PP2C: electricity power of P2Cs; PDPC: electric power for the DPC; PP2H: electricity power of P2Hs; CCWS,ch: charging power of CWSs; CCWS,dis: discharging power of CWSs; CDPC: cooling supply of the DPC; Cuser: cooling load of industrial park users; Euser: electric load of industrial park; Quser: heating load of industrial park users; QDPC: heating supply of the DPC; QTST,dis: discharging thermal power of TSTs; QTST,ch: charging thermal power of TSTs.
view moreCredit: Jiacheng Guo et al.
Industrial parks play a crucial role in China’s pursuit of carbon peak and carbon neutrality goals. However, their current energy systems face issues such as high energy consumption and large carbon emissions. A recent study published in Engineering focuses on optimizing the energy systems of industrial parks with hybrid energy storage to enhance economic performance, reliability, and carbon reduction.
The study points out that while renewable energy is a key to low-carbon operations in industrial parks, its intermittency and the unpredictable load demands pose challenges. Existing energy storage technologies have limitations, and most optimization research on hybrid energy storage has relied on rule-based passive-control principles.
To address these gaps, the research team developed a detailed model for the industrial park energy system with hybrid energy storage (IPES-HES), considering the operational characteristics of various energy devices. They proposed an active operation strategy that uses the hourly power output of energy storage for the next day as decision variables. An optimization configuration model was formulated with the goals of cost reduction and carbon emission lowering, solved using the non-dominated sorting genetic algorithm II (NSGA-II). A day-ahead nonlinear optimization scheduling method was also developed based on configuration optimization.
The findings are significant. On a typical summer day, the system energy bill and peak power of the IPES-HES under the optimization-based operational strategy were reduced by 181.4 USD (5.5%) and 1600.3 kW (43.7%) respectively, compared to an operation strategy based on proportional electricity storage.
The researchers plan to further investigate integrating load flexibility into the IPES-HES to improve renewable energy utilization. This study provides important theoretical support and practical guidance for optimizing the energy systems of industrial parks and is expected to have broad applications in the field.
The paper “Day-Ahead Nonlinear Optimization Scheduling for Industrial Park Energy Systems with Hybrid Energy Storage,” authored by Jiacheng Guo, Yimo Luo, Bin Zou, Jinqing Peng. Full text of the open access paper: https://doi.org/10.1016/j.eng.2024.10.006. For more information about the Engineering, follow us on X (https://twitter.com/EngineeringJrnl) & like us on Facebook (https://www.facebook.com/EngineeringJrnl).
Journal
Engineering
Article Title
Day-Ahead Nonlinear Optimization Scheduling for Industrial Park Energy Systems with Hybrid Energy Storage
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