Improvement of Frequency Stability in an Isolated Island System by Usi - PDF document

Improvement of Frequency Stability in an
Improvement of Frequency Stability in an Isolated Island System by Using Demand Response Yuan-Kang Wu and Guan-Ting Ye Department of Electrical Engineering, National Chung-Cheng University, Chiayi, Taiwan Email: allenwu@ccu.edu.tw Abstract²Balance between supply and demand is an important basis of the power system, unlike traditional operating and dispatching, the technology called demand response (DR) is widely used in different countries. Supply and demand unbalance would lead to unstable frequency, in particular in isolated island systems, and system accidents Manuscript received June 3, 2015; revised August 18, 2015. J. A. et al. [1] showedInternational Journal of Electrical Energy, Vol. 3, No. 3, September 2015©2015 International Journal of Electrical Energy151doi: 10.18178/ijoee.3.3.151-156in the isolated power system, especially the system that have been installed large-scale wind turbine on King Island in Australia. The study [9] showed that a huge implementation of intermittent sources may weaken the reliability of the electricity system in Reunion Island, but the problem can be solved by combining renewable sources and Demand Response solutions. D. Nikolic et al. [10] reported on the implementation of a simple and fast demand response technology to enable high wind penetration in an isolated power system. This solution is based on centralized two-way communication and control of residential and commercial loads. Typically, demand response can be dispatched and confirmed within 1s. The technology has been installed and successfully tested in an isolated power system on an island in Australia. Miguel Asensio and Javier Contreras [11] indicated the importance of adding short-term demand response to time-varying prices in systems with increasing stochastic generation penetration scenarios, and aQH[DPSOHEDVHGRQGDWDIURP6mR0LJXHO,VODQGLQ$]RUHV3RUWXJDOshows the applicability of the study proposed. This paper is divided into four sections: Section I describes the importance of demand response and some demand response cases in different countries, Section II describes demand response strategy in the Penghu Island power system, Section III presents simulation results and Section IV gives discussions and conclusions. II. DEMAND RESPONSE STRATEGY IN PENGHU POWER SYSTEM A. Penghu Isolated Island System The power system in Penghu area is a typical islanding system with the highest voltage rating at 69kV. It can be divided into Jiangshan thermal Power Plant, Zhonetun and Husi wind farms, Huxi and Magong substations. Jiangshan thermal Power Plant has Phase-I and Phase-II diesel generator units, including 4 diesel generator units made by BRUSH for Phase-I with an installed capacity of 12,285KVA for each unit and 8 diesel generator units made by SIEMENS for Phase-II with an installed capacity of 12,980KVA for each unit. Therefore, the total installed capacity of thermal Power Plants is 152.98MVA. These 12 diesel generator units are grid connected through the 13.2kV/69kV step-up transformers. Each generator unit has two control modes: droop and isochronous controls. According to the operation experience in the Jiangshan Thermal Power Plant, the Phase-I units are generally operated by droop control and the Phase-II units are operated by isochronous control. Therefore, this work applies the actual operation experience on the generator control. For the eight Type-D wind power generator units (Enercon E40) in Zhonetun wind farm, each unit has a rated output of 600kW. After the step-up transformer to convert the voltage to 11.95KV, each set of four units is connected to the bus of Huxi substation through the dedicated underground cables. For the six Type-D wind power generator units (Enercon E44) in Huxi wind farm, each unit has a rated output of 900kW. The single line diagram of the whole Penghu system is shown in Fig. 1. 69kV busJianshan Diesel Generator power station12kV busLoadLoadLoadZhonetun wind farmphase IZhonetun wind farmphase

IIHuxi wind farmLoadLoadLoadLoadLoadHuxi
IIHuxi wind farmLoadLoadLoadLoadLoadHuxi transformersubstationMagong transformersubstation12kV bus12kV bus69kV bus Figure 1. Single line diagram of the Penghu system. Penghu has aEXQGDQWZLQGUHVRXUFH3HQJKX¶VWRWDOoff-peak load is approximately 30MW in winter, which implies that the highest penetration of wind power can be reached 34%. Therefore, in the case of the winter off-peak period, such high penetration of wind power may impact the stable operation and transient characteristics of 3HQJKX¶VSRZHUV\VWHPThe stability of the frequency in an offshore island system is an important index of dynamic safety. The ratio of power output from each online diesel engine in an island system is normally very high. Therefore, once the diesel engines trip, the system frequency falls rapidly, affecting the frequency stability. Currently, the load shedding scheme is the only defense strategy in Penghu: the shedding operation is divided into three stages: The first stage is set at 57.4Hz; the second stage is set at 57.2Hz, and the third stage is set at 57Hz to shed 4 feeders respectively. The operating time of each relay and circuit breaker is 5 cycles and 45ms respectively. However, this kind of fixed-frequency low-frequency load shedding could not provide the optimal load shedding amount, and it sometimes yields an excessive load shedding amount. Several researches have addressed the issue about the high wind power penetration in Penghu Island and proposed several methods to reduce the system impact [12]-[15]. However, most works were focused on the generation side, not at the demand side. This work improves the frequency stability in the Penghu system by developing a demand response strategy. B. Demand Response Strategey The use of system frequency as an input signal to a load-controller was patented in 1979 in the U.S., which is called a Frequency Adaptive Power-Energy Re-scheduler (FAPER) [16]. The concept of FAPER can be applied to any electrical consumer [17]. In power systems and some International Journal of Electrical Energy, Vol. 3, No. 3, September 2015©2015 International Journal of Electrical Energy152customer electric equipment, such as refrigerator and air conditioning, the mechanism of fast demand response and FARER can be installed to achieve a flexible system operation. For example, the load with demand response would be switched off as frequency falls; otherwise, the load would be switched on as frequency rises. Because the refrigerator, air conditioning and other electric devices are controlled based on the temperature, one can switch off these devices temporarily until the temperature increases up to a predetermined limit [2]. In order to avoid the device to be switched off under higher temperature, this study designs a relation to describe a linear characteristic between frequency nadir and temperature, which can help system operators determine whether the controlled device is on or off, as shown in Fig. 2. LowerFrequencyHigherTemperatureHigherFrequencyLowerTemperatureOFFON Figure 2. Operating strategy on refrigerator, air conditioning or other devices. In the demand response mechanism, the power system controller (PSC) can monitor the power output from diesel generators, the power output from wind farms, and FXVWRPHU¶VORDGDVVKRZQLQ)LJ:KHQZLQGVSHHGfalls or rises, or when system has a contingency, unusual frequency will be detected by the slave controller, then PSC would send a message that requests customers implement load shedding or load increasing. The fast demand response can dispatch load within 1s after the control unit sends request message. Through the mechanism of demand response, the frequency stability can be improved. Power system controller(PSC)Diesel generatorsWind farmCustomer loadMeasurement signalControl signal Figure 3. The power system controller and monitoring systems. C. Simulation Situations Different system contingencies, such as the loss

of diesel generation or the loss of wind
of diesel generation or the loss of wind power owing to generation tripping, have different frequency responses. Particularly, Loss of diesel generation would cause inefficient spinning reserve; therefore, one should consider both contingency situations. In the next section, a system accident that both diesel generation and wind power losses occur simultaneously is assumed, which describes a worst condition. Then, the demand response mechanism is tested to confirm its effectiveness. In The Organization for Economic Cooperation and Development (OECD) countries, cold appliances provision account for 10.3% of total domestic electricity consumption [1]. This study implemented various system operating simulations by using PSS/E software. Several different operating conditions are considered, including 0% demand response, 5% demand response and 10% demand response. Additionally, the loss of diesel generation or the loss of wind power owing to generation tripping is also considered. Table I shows six kinds of operating scenarios in this study. TABLE I. DIFFERENT SIMULATION SCENARIOS System accident 0% DR &#x/MCI; 14;&#x/MCI; 14;5% DR &#x/MCI; 15;&#x/MCI; 15;10% DR Loss of diesel generation &#x/MCI; 18;&#x/MCI; 18;Loss of diesel generation with 0% DR (scenario 1) &#x/MCI; 19;&#x/MCI; 19;Loss of diesel generation with 5% DR (scenario 2) &#x/MCI; 20;&#x/MCI; 20;Loss of diesel generation with 10% DR (scenario 3) Loss of wind power &#x/MCI; 23;&#x/MCI; 23;Loss of wind power with 0% DR (scenario 4) &#x/MCI; 24;&#x/MCI; 24;Loss of wind power with 5% DR (scenario 5) &#x/MCI; 25;&#x/MCI; 25;Loss of wind power with 10% DR (scenario 6) III. SIMULATION RESULTS This study uses actual historical Penghu system operating data as PSS/E batch simulation cases, simulating the instantaneous frequency deviation of system after a diesel generator or a wind farm trips offline (Loss of diesel generation or wind power), so as to discuss the cases of actuating low frequency load shedding in different system operating conditions. The total simulation cases are 4344 and each case presents one-hour historical operating status. According to the simulation results, demand response can improve the transient stability and reduce frequency drop when a system contingency occurs. For example, case 1 indicates a severe accident (loss of wind power reduces power generation by 25%) and its operating status is shown in Table II. In that case, frequency nadir would be reduced below 57.4Hz and activate the first-stage load shedding if the Penghu system does not consider demand response mechanism. The frequency response curve is shown in Fig. 4(a). Case 2 indicates a light accident (loss of wind power reduces power generation by 20%). Although the frequency nadir is higher than the predetermined frequency 57.4Hz in Case 2, the transient frequency would be turned back to a normal status quickly if the Penghu system considers demand response mechanism, as shown in Fig. 4(b). International Journal of Electrical Energy, Vol. 3, No. 3, September 2015©2015 International Journal of Electrical Energy153TABLE II. OPERATING STATUS FOR CASES 1 AND 2. &#x/MCI; 20;&#x/MCI; 20;Jiangshan Power Plant &#x/MCI; 30;&#x/MCI; 30;Phase-I &#x/MCI; 40;&#x/MCI; 40;Jiangshan Power Plant &#x/MCI; 50;&#x/MCI; 50;phase-II &#x/MCI; 60;&#x/MCI; 60;Zhonetun wind farm &#x/MCI; 70;&#x/MCI; 70;Huxi wind farm Unit Number# &#x/MCI; 10;&#x/MCI; 10;1 &#x/MCI; 11;&#x/MCI; 11;2 &#x/MCI; 12;&#x/MCI; 12;3 &#x/MCI; 13;&#x/MCI; 13;4 &#x/MCI; 14;&#x/MCI; 14;1 &#x/MCI; 15;&#x/MCI; 15;2 &#x/MCI; 16;&#x/MCI; 16;3 &#x/MCI; 17;&#x/MCI; 17;4 &#x/MCI; 18;&#x/MCI; 18;5 &#x/MCI; 19;&#x/MCI; 19;6 &#x/MCI; 20;&#x/MCI; 20;7 &#x/MCI; 21;&#x/MCI; 21;8 &#x/MCI; 22;&#x/MCI; 22;1~8 &#x/MCI; 23;&#x/MCI; 23

;1~6 Case 1 &#x/MCI; 26;&#x/MCI;
;1~6 Case 1 &#x/MCI; 26;&#x/MCI; 26;5.04 &#x/MCI; 27;&#x/MCI; 27;0 &#x/MCI; 28;&#x/MCI; 28;0 &#x/MCI; 29;&#x/MCI; 29;5.04 &#x/MCI; 30;&#x/MCI; 30;10 &#x/MCI; 31;&#x/MCI; 31;0 &#x/MCI; 32;&#x/MCI; 32;4.4 &#x/MCI; 33;&#x/MCI; 33;0 &#x/MCI; 34;&#x/MCI; 34;4.5 &#x/MCI; 35;&#x/MCI; 35;0 &#x/MCI; 36;&#x/MCI; 36;0 &#x/MCI; 37;&#x/MCI; 37;0 &#x/MCI; 38;&#x/MCI; 38;4.175 &#x/MCI; 39;&#x/MCI; 39;5.581 Case 2 &#x/MCI; 42;&#x/MCI; 42;5.62 &#x/MCI; 43;&#x/MCI; 43;0 &#x/MCI; 44;&#x/MCI; 44;0 &#x/MCI; 45;&#x/MCI; 45;0 &#x/MCI; 46;&#x/MCI; 46;6.4 &#x/MCI; 47;&#x/MCI; 47;6.3 &#x/MCI; 48;&#x/MCI; 48;6.5 &#x/MCI; 49;&#x/MCI; 49;0 &#x/MCI; 50;&#x/MCI; 50;6.5 &#x/MCI; 51;&#x/MCI; 51;2.9 &#x/MCI; 52;&#x/MCI; 52;0 &#x/MCI; 53;&#x/MCI; 53;0 &#x/MCI; 54;&#x/MCI; 54;3.679 &#x/MCI; 55;&#x/MCI; 55;5.386 Figure 4. Frequency response curves owing to the loss of wind power (a) case 1: a severe accident, and (b) case 2: a light accident.A. Loss of Diesel Generation Owing to Diesel Generation Tripping To observe the frequency response under different operating statuses, 4344 simulation cases were carried out in this study, and the simulation results are summarized in Fig. 5, if an online largest diesel generator trips offline. Fig. 5 reveals that most of frequency nadirs are between 57.4Hz and 58.6Hz. However, if the system has no the demand response mechanism, the frequency nadir in several operating cases is still lower than the predetermined frequency 57.4Hz. If the Penghu system adopts the demand response mechanism, then the number of frequency nadirs that are lower than 57.4Hz is reduced significantly, which means the demand response mechanism is very effective in the Penghu Island for improving frequency stability. B. Loss of Wind Power Owing to Wind Generation Tripping The same simulation cases (4344 cases) described in Section III. A were also carried out by considering the loss of wind power, and the simulation results are summarized in Fig. 6. Fig. 6 demonstrates that most of the frequency nadirs are located between 57.2Hz and 60Hz. Similar to the results in Section III. A, the application of demand response could reduce the number of low frequency cases, but have a limited effect on high frequency cases. Figure 5. Distribution of frequency nadirs owing to the loss of diesel generation. International Journal of Electrical Energy, Vol. 3, No. 3, September 2015©2015 International Journal of Electrical Energy154 Figure 6. Distribution of frequency nadirs owing to the loss of wind power generation. TABLE III. DISTRIBUTION OF FREQUENCY NADIR UNDER DIFFERENT SCENARIOS Frequency &#x/MCI; 19;&#x/MCI; 19;(Hz) &#x/MCI; 20;&#x/MCI; 20;Scenario 1 &#x/MCI; 21;&#x/MCI; 21;Scenario 2 Scenario 3 Scenario 4 &#x/MCI; 24;&#x/MCI; 24;Scenario 5 &#x/MCI; 25;&#x/MCI; 25;Scenario 6 57.4 &#x/MCI; 28;&#x/MCI; 28;333 &#x/MCI; 29;&#x/MCI; 29;(7.67%) &#x/MCI; 30;&#x/MCI; 30;196 (4.51%) 164 (3.78%) 734 &#x/MCI; 35;&#x/MCI; 35;(16.9%) &#x/MCI; 36;&#x/MCI; 36;465 &#x/MCI; 37;&#x/MCI; 37;(10.71%) &#x/MCI; 38;&#x/MCI; 38;400 &#x/MCI; 39;&#x/MCI; 39;(9.21%) 57.4~58 &#x/MCI; 42;&#x/MCI; 42;1864 &#x/MCI; 43;&#x/MCI; 43;(42.91%) &#x/MCI; 44;&#x/MCI; 44;1847 &#x/MCI; 45;&#x/MCI; 45;(42.52%) &#x/MCI; 46;&#x/MCI; 46;1855 &#x/MCI; 47;&#x/MCI; 47;(42.7%) &#x/MCI; 48;&#x/MCI; 48;1726 &#x/MCI; 49;&#x/MCI; 49;(39.73%) &#x/MCI; 50;&#x/MCI; 50;1945 &#x/MCI; 51;&#x/MCI; 51;(44.77%) &#x/MCI; 52;&#x/MCI; 52;1988 &#x/MCI; 53;&#x/MCI; 53;(45.76%) 58~59 &#x/MCI; 56;&#x/MCI; 56;2147 &#x/MCI; 57;&#x/MCI; 57;(49.42%) &#x/MCI;&

#xD 58;&#x/MCI; 58;2301 &#x/MCI;&#
#xD 58;&#x/MCI; 58;2301 &#x/MCI; 59;&#x/MCI; 59;(52.97%) &#x/MCI; 60;&#x/MCI; 60;2325 &#x/MCI; 61;&#x/MCI; 61;(53.52%) &#x/MCI; 62;&#x/MCI; 62;817 &#x/MCI; 63;&#x/MCI; 63;(18.81%) &#x/MCI; 64;&#x/MCI; 64;867 &#x/MCI; 65;&#x/MCI; 65;(19.96%) &#x/MCI; 66;&#x/MCI; 66;889 &#x/MCI; 67;&#x/MCI; 67;(20.47%) 59~60 &#x/MCI; 70;&#x/MCI; 70;0 &#x/MCI; 71;&#x/MCI; 71;0 &#x/MCI; 72;&#x/MCI; 72;0 &#x/MCI; 73;&#x/MCI; 73;1067 &#x/MCI; 74;&#x/MCI; 74;(24.56%) &#x/MCI; 75;&#x/MCI; 75;1067 &#x/MCI; 76;&#x/MCI; 76;(24.56%) &#x/MCI; 77;&#x/MCI; 77;1067 &#x/MCI; 78;&#x/MCI; 78;(24.56%) This study simulates the historical 4344 operating cases by considering different scenarios that show in Table I. The results are summarized in Table III. For example, 7.67%, 4.51%, and 3.78% frequency nadir is lower than 57.4Hz in scenarios 1, 2, and 3 respectively, which demonstrates the proposed demand response mechanism is very effective. That is, the system with DR mechanism would maintain a more stable system when considering frequency response, no matter on the loss of diesel generation or wind power. IV. DISCUSSIONS AND CONCLUSIONS Traditional small island systems commonly utilize fewer diesel generators than other large systems, and these have a higher individual capacity, usually resulting in high penetration of each generator during off-peak. In particular, for small islands with light loads, the penetration of a generator may exceed 30% and once a diesel unit tripping event occurs, the transient frequency dip of the system will probably trigger the low-frequency shedding relay or even cause a complete blackout of the island. Additionally, if renewable energy is installed with high penetration on an island, then the number of online diesel generators in operation will be further reduced, potentially leading to an insufficient spinning reserve of the system. In order to increase system reliability and reduce the probability of low frequency events, demand response could be an appropriate technology. This study assumes that the Penghu system, a small isolated island system, is installed the proposed demand response mechanism and tests the feasibility of the demand response. Simulation results show that demand response is a very effective mechanism to improve the issue of frequency stability and reduce the number of events that trigger the low frequency protection relay, thus improving reliability and security of the Penghu system 5. ACKNOWLEDGMENT This work was financially supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant 104-3113-E-194-001-CC2. Project title: Development of Integration Technology for Large-Scale Offshore Wind Farms in Taiwan (2/3). REFERENCES [1] J. A. Short, D. G. Infield, and L. L. Freris, ³6WDELOL]DWLRQRIgrid frequency through dynamic demand control´IEEE Trans. on Power Systems, vol. 22, no. 3, pp. 1284-1293, 2007. [2] ':HVWHUPDQQDQG$-RKQ³'HPDQGmatching wind power generation with wide-area measurement and demand-side management´IEEE Trans. on Energy Conversion, vol. 22, no. 1, pp. 145-149, 2007. International Journal of Electrical Energy, Vol. 3, No. 3, September 2015©2015 International Journal of Electrical Energy155[3] $6.RZOLDQG630H\Q³6XSSRUWLQJwind generation deployment with demand response´SUHVHQWHGDWWKH,(((3RZHUand Energy Society General Meeting, 2011. [4] T. L. Vandoorn, B. Renders, L. Degroote, B. Meersman, and L. 9DQGHYHOGH³$FWLYHload control in islanded microgrids based on the grid voltage´IEEE Trans. on Smart Grid, vol. 2, no. 1, pp. 139-151, 2011. [5] H. Saele and O. S. Grande³'HPDQGresponse from household customers experiences from a pilot study in Norway´IEEE Trans. on Smart Grid, vol. 2,

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