Guangchao Geng

Dr. Guangchao Geng

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Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 March 2013 in IEEE Transactions on Power Systems
Verified
Journal Article
Closed access
QJQuanyuan Jiang
Quanyuan Jiang
MXMeidong Xue
Meidong Xue
GGGuangchao Geng
Guangchao Geng
There are two operation modes of microgrids: grid-connected mode and stand-alone mode. Normally, a microgrid will be connected to the main grid for the majority of time, i.e., operates in the grid-connected mode. In the stand-alone mode, a microgrid is isolated from the main grid; the highest priority for microgrids is to keep a reliable power supply to customers instead of economic benefits. So, the objectives and energy management strategies are different in two modes. In this paper, a novel double-layer coordinated control approach for microgrid energy management is proposed, which consists of two layers: the schedule layer and the dispatch layer. The schedule layer obtains an economic operation scheme based on forecasting data, while the dispatch layer provides power of controllable units based on real-time data. Errors between the forecasting and real-time data are resolved through coordination control of the two layers by reserving adequate active power in the schedule layer, then allocating that reserve in the dispatch layer to deal with the indeterminacy of uncontrollable units. A typical-structure microgrid is studied as an example, and simulation results are presented to demonstrate the performance of the proposed double-layer coordination control method in both grid-connected mode and stand-alone mode.
28 January 2019 in IEEE Transactions on Power Systems
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Journal Article
Closed access
RYRong Yan
Rong Yan
GGGuangchao Geng
Guangchao Geng
QJQuanyuan Jiang
Quanyuan Jiang
YLYanglin Li
Yanglin Li
Stability assessment is a regular routine in both power system planning and operation. It is computationally demanding using state-of-the-art approaches like time-domain simulation (TDS), as numerous scenarios (e.g., N-1 contingencies) have to be assessed for a large batch of contingencies. The purpose of this work is to determine stability conclusion before the simulator reaches the end of simulating time windows. Therefore, TDS can be terminated early so as to reduce the average simulation time for batch assessment without losses of accuracy. The idea is to develop a data-driven methodology to “learn” from existing TDS results in the batch and “infer” stability conclusions using current available TDS output. To achieve this goal, cascaded convolutional neural networks (CNNs) are designed to capture data from different TDS time intervals, extract features, predict stability probability and determine TDS termination. While accumulating more knowledge in batch processing, early termination criterion is refreshed continuously via feedback learning to terminate TDS increasingly earlier, with the increase of existing TDS results in the batch. Case studies in IEEE 39-bus and Polish 2383-bus system illustrate effectiveness of the proposed method.
30 March 2023 in Energy
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Journal Article
Closed access
XLXining Li
Xining Li
LJLingling Ju
Lingling Ju
GGGuangchao Geng
Guangchao Geng
QJQuanyuan Jiang
Quanyuan Jiang
1 May 2019 in IEEE Transactions on Power Systems
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Journal Article
Closed access
SWSiyuan Wang
Siyuan Wang
GGGuangchao Geng
Guangchao Geng
QJQuanyuan Jiang
Quanyuan Jiang
Energy storage is a potential planning option to relieve transmission congestion caused by increasing penetration of renewable energy. This paper presents a robust formulation for energy storage and transmission line co-planning, considering binary variables that represent energy storage statuses in the recourse problem. In order to solve this model, an improved nested column and constraint generation (nested C&CG) algorithm is used to cope with numerical issues caused by new binary variables, big-M constraints, and the enormous size of the problem. Case studies of a modified Garver's 6-bus system and a practical Chinese 196-bus system were used to assess the effectiveness of the proposed approach. The numerical results indicate that energy storage is more economical for relieving the transmission line congestion when the transmission distance is relatively long.
13 November 2017 in IEEE Transactions on Control of Network Systems
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Journal Article
Closed access
PYPengcheng You
Pengcheng You
SLSteven H. Low
Steven H. Low
Wayes TusharWayes Tushar
Wayes Tushar
GGGuangchao Geng
Guangchao Geng
Chau YuenChau Yuen
Chau Yuen
YSYouxian Sun
Youxian Sun
We formulate an optimal scheduling problem for battery swapping that assigns to each electric vehicle (EV) a best battery station to swap its depleted battery based on its current location and state of charge. The schedule aims to minimize a weighted sum of EVs' travel distance and electricity generation cost over both station assignments and power flow variables, subject to EV range constraints, grid operational constraints and AC power flow equations. To deal with the nonconvexity of power flow equations and the binary nature of station assignments, we propose a solution based on second-order cone programming (SOCP) relaxation of optimal power flow (OPF) and generalized Benders decomposition. When the SOCP relaxation is exact, this approach computes a global optimum. We evaluate the performance of the proposed algorithm through simulations. The algorithm requires global information and is suitable for cases where the distribution grid, battery stations, and EVs are managed centrally by the same operator. In Part II of the paper, we develop distributed solutions for cases where they are operated by different organizations that do not share private information.
16 November 2016 in IEEE Transactions on Power Systems
Verified
Journal Article
Closed access
ZLZhihao Li
Zhihao Li
GYGuoqiang Yao
Guoqiang Yao
GGGuangchao Geng
Guangchao Geng
QJQuanyuan Jiang
Quanyuan Jiang
With the expansion of modern power systems, the stability issues become more and more prominent. Transient stability emergency control is usually designed in open-loop schemes and applies proper actions to avoid system collapse when transient stability cannot be guaranteed in serious contingencies. Taking transient stability and economic efficiency of power system into consideration, the emergency control problem can be modeled as an optimal control problem, which is computational expensive. In this paper, an optimal control method with constraint aggregation is proposed to reduce computational complexity. The yield nonlinear problem is a fairly small-scale optimization problem which can be efficiently solved by predictor-corrector interior point method. The adjoint sensitivity analysis (ASA) is employed to evaluate the first-order derivative while Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is used to obtain the second-order derivative. Besides, very dishonest Newton (VDHN) method and reusage of LU factorization results are explored to accelerate the forward and backward integration phase of ASA, respectively. The proposed approach is tested on four cases with different scales, and shows its potential in computational efficiency.