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An, Xuena; Zhang, Shaohua; Li, Xue
doi: 10.1177/0142331213492788pmid: N/A
High wind power penetration presents many challenges to the flexibility and reliability of power system operation. In this environment, various demand response (DR) programs have received much attention. As an effective measure of DR programs, interruptible load (IL) programs have been widely used around the world. This paper addresses the concern of how the IL program impacts the equilibrium outcomes of electricity markets with wind power. First, a market demand model is developed to take consideration of the IL program. Next, a Cournot equilibrium model for electricity markets with an IL program and wind power is presented. The introduction of the IL program leads to a non-smooth equilibrium problem. To solve this equilibrium problem, a novel solution method is proposed. Finally, considering that wind power penetration will increase the risks faced by the conventional generators, the conditional value at risk is employed to measure the risk, so that the impact of the IL program on the generators’ risk can also be examined. Numerical examples are presented to verify the effectiveness of the method. It is shown that the IL program can lower market price and its volatility significantly. In addition, the IL program can help generators reduce their risks in the market, especially when the uncertainty in wind power output is relatively large.
doi: 10.1177/0142331213494100pmid: N/A
Moving from combustion engine to electric vehicle (EV)-based transport is recognized as having a major role to play in reducing pollution, combating climate change and improving energy security. However, the introduction of EVs poses major challenges for power system operation. With increasing penetration of EVs, uncontrolled coincident charging may overload the grid and substantially increase peak power requirements. Developing smart grid technologies and appropriate charging strategies to support the role out of EVs is therefore a high priority. In this paper, we investigate the effectiveness of distributed additive increase and multiplicative decrease (AIMD) charging algorithms, as proposed by Stüdli et al. in 2012, at mitigating the impact of domestic charging of EVs on low-voltage distribution networks. In particular, a number of enhancements to the basic AIMD implementation are introduced to enable local power system infrastructure and voltage level constraints to be taken into account and to reduce peak power requirements. The enhanced AIMD EV charging strategies are evaluated using power system simulations for a typical low-voltage residential feeder network in Ireland. Results show that by using the proposed AIMD-based smart charging algorithms, 50% EV penetration can be accommodated, compared with only 10% with uncontrolled charging, without exceeding network infrastructure constraints.
Wang, Jianwei; Zhang, Qingzhen; Hu, Xiaoguang; Wang, Yi
doi: 10.1177/0142331213510432pmid: N/A
In order to make the dynamic voltage restorer (DVR) concurrently compensate for low-order harmonics and voltage sag, and eliminate the influence of digital control on system performance, we propose a novel double closed-loop digital control strategy, consisting of the fundamental proportional resonant (PR) control in a voltage loop and selective harmonic PR control in an inductance current loop. Then, we mainly analyse the discretization effects of the virtual LC method and the step response method, and further present a straightforward digital design method. Next, with this method, we design the parameters of the fundamental and selective harmonic PR controllers in the discrete domain, which inhibit the influence of sampling, calculation delay etc. on the steady-state error and the dynamic response performance. Finally, an 11-kVA DVR prototype is developed and tested. The experimental results indicate that the proposed control strategy satisfies the requirement of voltage quality for sensitive loads and achieves a good dynamic response performance.
Qi, Liang; Bao, Sheng; Shi, Hongbo
doi: 10.1177/0142331213495886pmid: N/A
In this paper, a novel second-order integral sliding mode control (SOSMC) algorithm is proposed to accomplish velocity control of the permanent-magnet synchronous motor (PMSM) so that the performance can be improved. An integral manifold is utilized to reduce the static error during the sliding mode movement phase to improve the control precision, and a new SOSMC law is achieved by a Lyapunov function approach so the system convergence is guaranteed. The presented method can not only eliminate the system chattering problem successfully but also improve the performance of the PMSM control system. Meanwhile, in order to solve the problem of the windup phenomenon of the PMSM control system, an anti-windup control method is proposed in the PMSM control system. The simulation experimental results are given to indicate that the proposed method is effective and can improve the performance of the PMSM control system such as fast response, high robustness and speed tracking precision, etc.
doi: 10.1177/0142331213510549pmid: N/A
This paper presents an adaptive neural-fuzzy control scheme for a dual-level-structure flexible manipulator with variable dynamic payload. The dynamic moving model of the flexible manipulator is derived and the state-space equation is formulated first. A control scheme that consists of a neural-fuzzy controller in the feedback channel and an image-guided identification network (IGIN) in the forward configuration is then proposed. The IGIN is employed to locate the object (e.g. bimetal) to achieve the tracking function, while the dynamic neural network is used to learn the weighting factor of the fuzzy controller. Finally, simulations are run for various modes to describe the dynamic tracking system, and simulated results show a good performance of the control tracking system.
Li, Jiwei; Li, Dewei; Xi, Yugeng; Lu, Jianbo
doi: 10.1177/0142331213494219pmid: N/A
This paper is concerned with model predictive control for polytopic systems subject to exogenous disturbance and H2/H∞ performance constraints. It is shown that a better characterization of H2/H∞ performance can be provided by introducing additional free parameters. Meanwhile, input constraints are ensured by using a dilated linear matrix inequality technique, so the utilization of actuator capability is improved. These two aspects bring extra degrees of freedom in optimizing control performance. Recursive feasibility and stability of the controller are proved. Numerical examples verify these properties.
Cen, Lihui; Xi, Yugeng; Li, Dewei; Cen, Yigang
doi: 10.1177/0142331213512365pmid: N/A
This paper proposes a boundary feedback control design for open canal networks using the linearization of boundary conditions. For open canal networks with any types of cross-sections, which can be modelled by the Saint-Venant equations, the characteristic form in terms of Riemann invariants has been established. Under this established characteristic form, the stabilizing boundary control law has been developed by linearizing the boundary conditions for both a single reach and the open-channel network composed by multi-reaches in a cascade. The design of the boundary feedback control laws for both a single canal and the cascaded networks is illustrated in a unified framework, which extends the results in the literature.
doi: 10.1177/0142331214536200pmid: N/A
Risk management and inventory cost control are key issues in supply chain management. Based on an (r, Q) strategy, this paper formulates a multi-layer multi-period stochastic inventory problem as a robust multi-objective model. The novelty lies in the consideration of both perturbed variables and stochastic demand in the model. The goal is to minimize the expected cost and the risk measured by conditional value at risk (CVaR). To solve this model, we propose a hybrid Non-Dominated Genetic Algorithm-II (NSGA-II) where a polynomial time algorithm is designed to obtain the optimal CVaR for a given (r, Q). Moreover, a local search method is tailored for the NSGA-II to improve solutions. This hybrid algorithm can significantly increase the number of optimal solutions and decrease the inventory cost. Numerical results validate the effectiveness of our robust multi-objective model and the hybrid algorithm.
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