With the continuing growth of renewable penetration in power systems, it becomes increasingly challenging to manage the operational uncertainty at near-real-time stage via deterministic scheduling approaches. This paper explores the necessity, benefits and implementability of applying stochastic programming to security constrained economic dispatch (SCED). We formulate a stochastic look-ahead economic dispatch (LAED-S) model for near-real-time power system operation. A concept of uncertainty responses is introduced to assess the power system economic risk with respect to net load uncertainties. This concept offers the system operator a simple yet effective gauge to decide whether a stochastic approach is more desirable than a deterministic one. For an efficient stochastic dispatch algorithm, an innovative hybrid computing architecture is proposed. It leverages the progressive hedging algorithm and the L-shaped method. Numerical experiments are conducted on a practical 5889-bus system to illustrate the effectiveness of the proposed approach.
Yingzhong Gu, Le Xie
IEEE Transactions on Power Systems, Volume: 29 , Issue: 1 , Jan. 2014.,
2017
Although the installed wind generation capacity has grown remarkably over the past decades, percentage of wind energy in electricity supply portfolio is still relatively low. Due to the technical limitations of power system operations, considerable wind generation cannot integrate into the grid but gets curtailed. Among various factors, transmission congestion accounts for a significant portion of wind curtailment. Derived from DC power network, an analytical approach is proposed to efficiently assess the congestion induced wind curtailment sensitivity without iterative simulation. Compared to empirical simulation-based wind curtailment studies, the proposed approach offers the following advantages: 1) computational efficiency, 2) low input information requirement, and 3) robustness against uncertainties. This approach could benefit system operators, wind farm owners as well as wind power investors to better understand the interactions between wind curtailment and power system operations and can further help for curtailment alleviation. Numerical experiments of a modified IEEE 24-bus Reliability Test System (RTS) as well as a practical 5889-bus system are conducted to verify the effectiveness and robustness of the proposed approach.
Yingzhong Gu, Le Xie
IEEE Transactions on Power Systems, Volume: 29 , Issue: 1 , Jan. 2014.,
2014
We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models.
Le Xie, Yingzhong Gu, Xinxin Zhu, Marc G. Genton
IEEE Transactions on Smart Grid, Volume: 5 , Issue: 1 , Jan. 2014.,
2014
To support large-scale integration of wind power into electric energy systems, state-of-the-art wind speed forecasting methods should be able to provide accurate and adequate information to enable efficient, reliable, and cost-effective scheduling of wind power. Here, we incorporate space-time wind forecasts into electric power system scheduling. First, we propose a modified regime-switching, space-time wind speed forecasting model that allows the forecast regimes to vary with the dominant wind direction and with the seasons, hence avoiding a subjective choice of regimes. Then, results from the wind forecasts are incorporated into a power system economic dispatch model, the cost of which is used as a loss measure of the quality of the forecast models. This, in turn, leads to cost-effective scheduling of system-wide wind generation. Potential economic benefits arise from the system-wide generation of cost savings and from the ancillary service cost savings. We illustrate the economic benefits using a test system in the northwest region of the United States. Compared with persistence and autoregressive models, our model suggests that cost savings from integration of wind power could be on the scale of tens of millions of dollars annually in regions with high wind penetration, such as Texas and the Pacific northwest.
Xinxin Zhu, Marc G Genton, Yingzhong Gu, Le Xie
TEST, March 2014, Volume 23, Issue 1, pp 1–25.,
2014
This paper presents a novel algorithm for the early detection and optimal corrective measures of power system insecurity in an enhanced look-ahead dispatch framework. By introducing short-term dispatchable capacity (STDC) into the proposed look-ahead security management (LSM) scheme, the algorithm is capable of predicting and identifying future infeasibilities that pose security risks to the system under both normal conditions and assumed contingency conditions. An optimal recovery plan can be computed to prevent system insecurity at a minimal cost. Early awareness of such information is of vital importance to system operators for taking timely actions with more flexible and cost-effective measures. This, in addition to the economic benefits studied in the literature, demonstrates the advantage of security improvement of the look-ahead dispatch framework. The performance of the proposed algorithms is illustrated in a revised 24-bus IEEE Reliability Test System as well as in a practical 5889-bus system.
Yingzhong Gu, Le Xie
IEEE Transactions on Power Systems, vol. 28, no. 2, pp. 1297-1307, May 2013.,
2013
This paper presents a progressive hedging (PH) based decomposition algorithm to improve the computational efficiency of stochastic day-ahead reliability unit commitment (RUC). Stochastic programming is introduced into RUC to facilitate a better decision making for market operation efficiency and energy supply reliability. However, the computational burden of stochastic RUC using today’s computing power is still significant. We propose to apply progressive hedging (PH) algorithm to decompose the stochastic RUC problem. It is shown that a PH-based algorithm allows parallel computation of stochastic RUC, which can be much faster than conventional stochastic programming methods. A practical power system is used to verify the effectiveness of the proposed computation framework.
Yingzhong Gu, Xing Wang, Le Xie
2013 IEEE Power & Energy Society General Meeting.,
2013
In this paper, a model predictive control (MPC)-based coordinated scheduling framework for variable wind generation and battery energy storage systems (BESSs) is presented. On the basis of the short-term forecast of available wind generation and price information, a joint look-ahead optimization is performed by the wind farm and storage system to determine their net power injection to the electric power grid. In conjunction with moderate battery capacity, the excess unpredictable wind generation can be used to charge the battery storage and vice versa. The benefits of the proposed scheduling approach are that (1) the combined profit of wind generation and BESS is increased; (2) the net power injection from the wind farm into the power grid is smoothed out; and (3) the look-ahead optimization updates the price prediction in a moving horizon, which leads to more robust profit for wind farm and BESS against price uncertainties. By formulating the MPC-based coordinated scheduling as a quadratic programming problem, several numerically efficient algorithms to compute the optimal control strategy for wind generation and BESS are proposed. The effectiveness of the proposed algorithm in a modified IEEE 24-bus reliability test system with aggregated plug-in hybrid electric vehicles is demonstrated. It is shown that the proposed algorithm can increase the joint profit of wind farm and BESS while smoothing out the net power injection to the electricity grid. The proposed MPC-based scheduling problem can be solved in approximately 400 ms, which makes the framework implementable in realtime electricity market operations.
Le Xie, Yingzhong Gu, Ali Eskandari, Mehrdad Ehsani
Journal of Energy Engineering, Vol. 138, Issue 2, June 2012,
2012
We propose a framework of look-ahead dispatch which considers forecast uncertainty and infeasibility management. Two major advantages of the framework are demonstrated: 1) economic performance improvement under the presence of forecast uncertainty; and, 2)feasibility enhancement of the dispatch problem. In the look-ahead dispatch framework, a weighted predictive scheduling (WPS) technique is proposed to relieve the negative impacts on dispatch due to wind forecast uncertainty in future steps. Look-ahead security management (LSM) is introduced, which is a technique to identify and quantify potential infeasibility of the dispatch in advance. The LSM technique is shown to be capable of working out an optimal recovery plan for future violation of system security. Finally, the proposed techniques are illustrated in a modified 24 Bus Reliability Test System.
Yingzhong Gu, Le Xie
2012 IEEE Power and Energy Society General Meeting.,
2012
During the past decade, there has been tremendous development in wind energy all over the world. However, due to the power system operational constraints, reliability requirement as well as other technical limitations (e.g. wind prediction errors), significant portions of the wind generation resources (WGR) are curtailed in real-time operations. Among various power system operating constraints, transmission congestion plays a significant role. In this paper, we analyze the problem of the wind curtailment due to transmission congestion. Furthermore, we propose a sensitivity index to assess the impact of transmission line limit on wind generation curtailment. An analytical expression of the sensitivity index is derived based on the network theory of power system. The modified IEEE RTS-24 Bus system is used to verify the proposed theory.
Yingzhong Gu, Le Xie, Brett Rollow, Bo Hesselbaek
2011 North American Power Symposium.,
2011
The increasing power in the demand side, the large-scale Electric Vehicles’ (EVs) randomness in charging/discharging modes and uncertainty in demand response are posing a threat to the stable operation and security of power systems. A spatio-temporal bi-layers scheduling model for EVs and Load Aggregators (LAs) considering response reliability is proposed in the paper. In the upper layer, the indices of charging urgency and discharging adequacy are established to describe the controllability of EVs. Further, the EVs are sequenced, and the upper and lower boundaries of controllable power domain are determined. Then, the optimal nodal schedulable load is obtained through an improved optimal power flow model considering the spatial characteristics. In the lower layer, pricing strategies for charging/discharging considering the response reliability of LAs and EVs are developed, and the optimal scheduling strategies are built. Finally, the effectiveness of the proposed model is verified through a modified IEEE 33 system, in addition, impacts of response reliability on the energy allocation and economic benefits are analyzed in the case study.
Le Xie, Yingzhong Gu, Xinxin Zhu, Marc G. Genton
IEEE Energytech, 2011, 1-6.,
2011
In a space spanned by generation parameter, the different properties of loading margin surface and generation limit surface are investigated at first in this paper. Then, the shortage of taking the generation limit surface as limit boundary for generation rescheduling (GR) is elaborated and a developed GR model is presented. Additionally, in order to take the uncertainty of load pattern into consideration, a bilevel programming model with the opposite structure to each other is proposed. In this model, the upper level is used to optimize generation pattern (GP) for maximizing the loading margin while the lower level is used to determine the worst load pattern for checking the adaptability of the GP to the variation of the load pattern. A Step-by-step Approximation based Primal Dual Interior Point method (SAPDIP method) and Successive Linear Programming method (SLP method) are used to solve the two sub-models, respectively. The GP optimized by the proposed model reflects the balance between the “variation” and “adaption”, and is less sensitive to the changes in load pattern. Finally, the proposed method is tested on multiple standard IEEE test systems as well as a real power system in China.
Ning Xiong, Haozhong Cheng, Liangzhong Yao, Yingzhong Gu, Zeliang Ma, Zhonglie Zhu, Jianping Zhang
IEEE Transactions on Power Systems, Volume: 25 , Issue: 3 , Aug. 2010.,
2010
The major subject of this paper is the analysis and simulation of market-based coordination of variable resources with storage systems such as aggregated Plug-in Hybrid Electric Vehicles (PHEVs). Starting from our recent work on modeling and model predictive scheduling of conventional generation, variable generation, and battery storage systems, we further develop in this paper a look-ahead multi-layered simulation platform which (1) takes into account of the transmission congestion; and (2) co-optimizes individual participants’ profits from both energy and regulation services markets. In contrast with today’s operation software, the proposed scheduling framework could improve the overall system efficiency while observing the transmission network constraints. We illustrate the improved operational efficiency in a modified IEEE 14-bus system.
Yingzhong Gu, Le Xie
North American Power Symposium (NAPS), 2010.,
2010
