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|Title:||Plug-in electric vehicle charging control for wind power integration enhancement|
|Advisors:||Chan, Kevin K. W. (EE)|
Electric vehicles -- Power supply.
|Publisher:||The Hong Kong Polytechnic University|
|Abstract:||Global environmental crises, such as the global climate change and awful air pollution in major cities over the world, are causing profound changes to both the power system and the transportation sector. On one hand, power systems worldwide are evolving towards a greener version by integrating increasing amount of renewable energy sources, especially wind power (WP). On the other hand, as an effective way to reduce greenhouse gas emission, plug-in electric vehicles (PEVs) are currently incentivized in many countries and more and more types of PEV are being rolled out by various automakers. With the adoption of PEV surging, a rapid increase of PEV charging load can be expected in the coming years. The uncertainty and variability of WP generation will weaken the controllability on the supply side of the power system and require more fast-reacting reserve, while bulk uncontrolled PEV charging may severely stress the network at all voltage levels, threatening the system reliability, lowering its efficiency, and jeopardizing the system economy. Controlled PEV charging, however, could be a valuable source for large-scale demand response (DR). The DR is identified as a very effective tool to facilitate smooth WP integration, and clean electricity from WP to propel PEVs can significantly decarbonize the transportation sector. Thus, a lot of synergies can be explored between the PEV charging load and the WP generation. As an effort to safely accommodate the PEV charging load at the initial stage of PEV adoption before the upgrade of the network infrastructure, this thesis firstly proposes a real-time scheduling scheme for PEV charging in low-voltage residential distribution network. This scheme schedules PEV charging to either minimize system losses or prevent over-low voltage, depending on the PEV penetration level. Since most often voltage drop would become a binding constraint when a low-voltage distribution feeder is subject to high PEV penetration level, a scheduling method is first developed to enlarge the voltage safety margin. Then, a novel factor is derived to allow the scheduling scheme to be flexibly adjusted from being voltage-safety-oriented to loss-minimization-oriented, or vice versa. Simulation results verify that the proposed scheduling scheme is fast and effective with circuit losses close to optimal at low PEV penetration level and voltage drops maintained within the tolerable limit at high PEV penetration level.|
To facilitate the PEV demand response, a decentralized charging control scheme is devised in this thesis. In the proposed control scheme, individual PEV would autonomously adjust its power in response to two system-level directional signals. Since the power adjustment would also take into account the PEV's urgency level of charging (ULC), the charging/discharging power among PEVs will be distributed automatically according to their heterogeneous charging requirements. The mechanism that can trigger divergent PEV power adjustment is analyzed to obtain the stability condition for the proposed control scheme. For the control inaccuracy caused by interrupted individual PEV power adjustments, a remedy is proposed and proved. As an application, the power of a PEV fleet is controlled by the proposed decentralized charging control scheme to compensate undesired fluctuations in a wind farm's power output. Simulation results verify that the controlled PEV power can respond to undesired WP fluctuations timely and accurately, and the power distribution among PEVs is consistent with the heterogeneous PEV charging requirements. Increasing amount of WP in the power system will force conventional generators to go through more frequent cycling operations which have damaging effects on generator components. In this context, a 3-level hierarchical scheme is proposed to utilize the PEV power to hedge against the unit ramp cycling (URC) operations. A general URC operation model is proposed for the first time. Net load variation range (NLVR) is used to capture the WP forecast uncertainty. The top-level scheduling model reshapes the NLVR by coordinating PEV charging load to minimize the URC operations that can be caused by the possible net load realizations in the NLVR. Based on updated WP forecasts, the middle-level dispatch model exempts the over-scheduled anti-URC regulation onus on PEVs to promote PEV charging. Nevertheless, the actual dispatch of net load is confined within the reshaped NLVR from the top-level scheduling to avoid overly restoring the PEV power. At the bottom-level is the proposed decentralized charging control scheme to implement the PEV power dispatch instruction. Simulation results show that with the proposed hierarchical scheme, the PEV-aided URC operation mitigation is effective and most of the desired charging energy is preserved to satisfy the charging requirements for the majority of PEVs. The effectiveness of the proposed scheme is shown to be robust to WP forecast errors. The associated cost to accommodate the WP uncertainty and variability (WPUnV) in a power system is referred as the wind power uncertainty cost (WPUC) which would increase rapidly with WP penetration level. This thesis investigates to what extent the controlled PEV power would help reduce this WPUC. A comprehensive WPUC model is proposed in which generator cycling costs are included. Also, the proposed decentralized charging control scheme is used to obtain a realistic response of the PEV load to the system dispatch instruction. With the WPUnV decomposed into two components, namely hourly WP forecast errors and sub-hourly WP fluctuations, the WPUC raised by each of the components will be evaluated. Simulation results show that generator cycling costs are non-negligible parts of the WPUC and controlled PEV power has a favorable effect on reducing the overall WPUC. The controlled PEV power, however, may not be as helpful as expected to mitigate the WPUC induced by the WP forecast errors on hourly scale. Yet, the WPUC raised by sub-hourly WP fluctuations can be largely reduced with the controlled PEV power.
|Description:||PolyU Library Call No.: [THS] LG51 .H577P EE 2016 Luo|
xvi, 167 pages :color illustrations
|Rights:||All rights reserved.|
|Appears in Collections:||Thesis|
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Checked on Sep 17, 2017
Checked on Sep 17, 2017
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