Influence of Solar and Wind Power Generation Sources on Power Supply Availability in Telecom Infrastructure Domagoj Talapko
Prof. Sejid Tesnjak, Ph.D.
Emerson Network Power Selska 93, Zagreb, Croatia
Faculty of Electrical Engineering and Computing Unska 3, Zagreb, Croatia
[email protected]
[email protected]
Abstract - This paper addresses reliability and availability of power infrastructure in telecom core and data centers. Special attention is given to modelling of solar and wind power sources in terms of availability as well as their implementation into critical infrastructure. Influence on overall electrical reliability and availability of infrastructure is shown in different topologies. Architecture of the topologies is based on both alternating current (AC) and direct current (DC) 400V distributions. Results of reliability and availability calculations derive from models based on dynamic Fault Tree Analysis (FTA). Keywords-Solar, Wind, Telecom, Reliability, Availability, FTA
I. INTRODUCTION Energy efficiency can be seen as an imperative of sustainable development what is also confirmed by European Commission DG INFSO in their study from 2008 [1]. The goal of reducing electrical power consumption by 20% from power plants and therefore reduce carbon footprint by 20% by implementing alternative power sources increasing their share by 20% by the year 2020 will certainly require nonconventional approach to powering of many facilities among which facilities belonging to telecom industry have a fair share. Telecom industry axiom calls for high reliability and availability level allocated to electrical infrastructure in telecom facilities. When using traditional energy sources such as AC commercial grid in conjunction with diesel generators and battery back-up these levels are always met, but due to the global usage increase of alternative power supplies it is a question how implementation of these sources in critical infrastructure such as data center reflects on overall infrastructure availability. In order to understand the impact on total availability by use of alternative energy supplies in telecom facilities in this paper reliability and availability models will be proposed. Presented models will consist of models of solar, wind and diesel power generation systems implemented into different electrical topologies, what will enable good result differentiation resolution.
II. CRITICAL FACILITY MODELS For the purpose of this paper electrical models are proposed to reflect a powering of 200kW nominal data center load composed primarily of servers. Powering of cooling equipment and other mechanical loads is not considered. Telecom loads can be considered as constant loads and their power consumption does not very significantly during the day or year. Proposed models and architectures are based on European voltage levels and frequency. A.
Electrical Architecture in Telecomunication Facility Total system availability is not determined simply by the reliability of individual components or sub-systems, but also by system topology and how sub-systems interact together. Typically, mission critical facilities are powered from more than one AC power source. This can include separate feeds from independent utilities or substations often in conjunction with local diesel generator(s) on site. Distribution of energy is done via discrete wiring or bus-duct systems connected to distribution cabinets, from which the critical load is fed. Depending on proposed system topology, transfer switch gear like automatic transfer switch (ATS) is often used to enable transition between two sources.
Fig. 1. Implementation of solar power in AC architecture
Fig. 2. Implementation of solar power in DC architecture
Fig. 3. Implementation of wind power in AC architecture
Fig. 4. Implementation of wind power in DC architecture
B.
Electrical Equipment in Telecomunication Facility State of the art UPS systems can be deployed in several different modes of operation. Modular construction not only provides for scalability but also by placing a static switch in
every module eliminates a single point of failure. In both cases the operation modes can be on-line, line interactive or in “eco mode” (power supplied to the load via static switch bypass directly from the utility). Line interactive and “eco mode” operation depends heavily on switching between line and UPS and high reliability of static switch is crucial. Modern modular and scalable DC based power systems used in telecom applications can be easily expanded and designed with redundancy / availability built into the system based on the ease of use of modular approach. In the applied models all systems under study have two strings of batteries sized to supply the full load during period of 15 minutes enabling the succesful start of diesel generator. Batteries used in AC UPS have different configuration (number of cells) than those used in DC UPS due to different voltage requirements. The AC UPS uses a battery string with 40 blocks (240 cells) with 120Ah capacity while the battery string for DC UPS consist 28 blocks (156 cells) with 170Ah capacity. Ultimately, the number of cells impacts availability of battery. Estimated time between failures for battery system used in AC system is 12500h [2] and for the battery in DC system, 19231h. Proposed MTBF for battery strings in AC systems is derived from reference [2] while the figure for DC systems is derived from interpolation of data provided in [2] and is valid only during first two years of batteries exploitation. Availability of AC commercial grid is set to 99,9%. The European distribution model was used for calculations – using transformerless power distribution units (PDU) from UPS to the load. In the USA, PDUs would typically be equipped with a step down transformer what would ultimately decrease the availability of an AC distribution model. The modular AC UPS consists of eight (8) 30kVA modules placed in two cabinets (four modules per cabinet) for a total system rating of 240kW. Since modules can operate with cos φ ≈ 1, seven modules are sufficient to provide power to the load (210kW) and one module is redundant. This is assuming perfectly balanced load. Typically 3 phase systems are derated by the safety factor of 0.8 to accommodate for potential unbalance. This is not the case for DC as there is only a single circuit. Each module has additional capacity built-in for recharging of the batteries. All key components (rectifier, inverter and static switch) are present in each module. In the case of failure of any element of the module (controller board included), the whole module is pronounced as faulty. Modular UPS also supports “eco mode” or in “on-line mode” operating regimes, achieved on module level. In the case of more than one module failure, the system will run out of the power capacity and the load will be transferred on direct feed from AC mains by means of static by-pass switch. DC Power System model incorporates 16 modules connected in parallel, where each module is rated 15kW, enabling 240kW of installed power. Modules are placed in two cabinets so that in each cabinet 8 modules are placed. The system is dimensioned according to telecom application logic (N+1), what is achieved by 14 modules to power the load (210kW) with two additional modules of 15kW for
battery recharging and redundancy. Output of the system is achieved via circuit breakers rated for 100% of load. The system controller is not subjected to analysis since its failure will not influence overall performance of the system. When AC mains is available the DC System is able to supply the load without any interruptions even if two out of the twenty modules fail as that will simply mean that there is no more redundancy and no capacity to charge the battery. However, there will still be enough capacity to supply the load. In case if more rectifier modules go down, battery reserve will backup for lack of energy that should come from rectifiers. The battery discharge, considering low power drain would last for hours, so the maintenance time is very long and considering short MTTR the system’s capacity can be easily restored without impact on critical bus. This is a fundamental difference between AC modular and DC modular – battery in DC is on–line while in AC is coupled through inverter, so technically in DC modular 2 rectifiers can fail if there are spares on site. In order to increase the efficiency level of the solar system, maximum power point tracking (MPPT) modules are used [3] based on DC/DC architecture. Each module is 15kW and modeled system consists of 15 modules in placed in two cabinets where 14 modules are used to enhance the efficiency of the power flow from solar panels and one more module is used to achieve N+1 architecture specific for telecom sites. It is considered that all loads (servers) are based on dual cord power supply and that it is possible to set the server to take the energy primeraly from one input and use other as a back-up line and in that way server will intake the energy from “B” branch by default and use the “A” branch as an auxiliary. C.
Models of Power Sources Diesel Generators are most well-known standby power source of energy not only in telecom infrastructure but also in nuclear facilities, hospitals, airports and may other types of critical infrastructures. Diesel generators are capable to take the full load in about 10 seconds after they go online and can operate typically 30000 hours without major failures [4]. In size, usually they can be up to 7MW. They are easy to parallel and in that way form more flexible, scalable and reliable power supply systems. According to [5] two out of top ten data centers outages worldwide in year 2012 are associated to diesel generator failure. Since the diesel generators operate mainly as back-up systems, their failure to start can be potentially huge problem. For that reason, regular maintenance schedules must be followed. One of the weakest elements in the whole diesel system is actually an internal starter battery; therefore regular maintenance checks must also include that element. In this paper, model is based on single diesel system of 250kWe. Reliability model incorporate failure to start of diesel generator since it is modeled in a cold standby mode and not under maintenance in moment when it needs to operate.
Unlike power sources that are constantly available and ready for operation, solar and wind power generation systems significantly depend on availability of the prime energy sources. In case of solar power generation that is the availability of Sun radiation and in case of wind power generation amount of wind masses. One more element is crucial in this kind of operations to enable higher availability and that is battery back-up that will accumulate all excessive energy produced from solar / wind power systems and be utilized during hours with low or no availability of the Sun / wind masses. In proposed models, two locations in Europe are selected for implementation of alternative energy supply; dimensioning of data center with solar system is done according to parameters specific to Valencia in Spain and for implementation of wind system Aberdeen district in Scotland. Both locations are selected intentionally since they have very constant amounts of primary energy source: Sun and wind. Solar system consists of 6480 solar cells of 12V each with maximum (peek) power 250W. Cells are assembled in panels with 2x3 configuration enabling voltage level of 72V and 10 of these panels are forming one solar system operating at 720V nominal. Total number of systems needed to cater sufficient energy throughout the year is 108. Battery dimensioning is based on 3000Ah 2V cells as main building blocks. Battery system consists of 1440 battery blocks enabling 45h battery autonomy at full load with average depth of discharge (DoD) at 42%. According to reliability testing of solar panels of different manufacturers presented in [6], failure rates that derive from accelerated testing protocol indicate that failure rates of various solar panels are rather high: 31% in damp heat test, 14% humidity freeze test and 12-13% during static load, termination and 200 thermal cycling tests. However, these results need to be taken with caution when building a model, since these testing methods are developed for purpose of product qualification on the market. According to [7]-[9], in real life solar panels failures should be seen in terms of degradation of the individual cell depending on climate conditions such as rise of temperature and moisture. For the purpose of modeling, MTBF value of 600 years with lifetime of 30 years for individual 12V solar cell was considered. In general, wind power systems cannot be considered as a stabile option for constant powering primarily due to unpredictability of wind and all parameters associated with it (speed, direction, moisture) especially when considering climate changes and that historical data is less and less reliable. Before considering wind turbine implementation on specific location a detailed measurement needs to be carried out on micro-location level. In presented model capacity of wind masses is assumed and average wind speed is considered as 9 m/s. Electrical power generated by wind turbine is exponentially dependent on wind speed and for that reason in the model proposed is a situation where 3 wind turbines each rated at 250kW nominally will be enough to cover the daily load and daily battery charging during entire
year. Excessive generated energy can be sent into the commercial grid and sold, but this model will not be discussed in this paper, since the impact of this power link will be negligible to the whole facility in terms of reliability. According to [10] typical availability values for wind turbine systems are 98% of manufacturer’s availability and 97% of operators availability. Difference of 1% between these two levels is caused by logistics issues on operator’s side. Also according to [10] 1 failure for 250kW wind turbine during one year is very common and number of failures per year increases with increase of turbine electrical size (1,7 failures for 300kW and 2,5 failures for 500kW during one year). Battery system modeled with the wind system is the same as with solar system, enabling 45h full autonomy with DoD at 42%, meaning that in critical situations battery could provide power during at least three and half days but that would cause deep discharge what could ultimately lead to reduction in batteries lifetime. In all models potential impacts on reliability of equipment associated with power quality issues, such as harmonics, are omitted.
Fig. 5. FTA of AC architecture side A
III. RELIABILITY AND AVAILABILITY CALCULATIONS Reliability of the system is defined as probability that system operates within normal parameters under certain conditions during a given period of time and should be used as a measurement of system complexity, as per Equation (1). Availability is a statistical probability that the system will perform in random time t in the future [11], as per Equations (2) and (3). In all of the calculations an assumption is taken that all components have exponential probability density of failure. R(t) = exp(-t/MTBF)
(1)
A = Uptime / (Uptime + Downtime)
(2)
U = Downtime / (Uptime + Downtime)
(3)
Fig. 6. FTA of DC architecture side A
Downtime incorporates mean times when component is under corrective maintenance or under preventive maintenance that requires its shutdown. TABLE I SYSTEM AVAILABILITY WITH CORRESPONDING DOWNTIME Number of Nines 99,0 99,9 99,99 99,999 99,9999 99,99999
Downtime per Year 90h 9h 0,9h 5min 0,5min 3sec Fig. 7. FTA of AC architecture side B with solar system
Fig. 8. FTA of DC architecture side B with solar system Fig. 10. FTA of DC architecture side B with wind system
The models discussed in this paper do not incorporate influences that are subjected to dynamic events, such as recovery actions during the certain failures of redundant system elements. Actions of preventive maintenance are also not considered. In the models with solar and wind power, assumption is made that all accumulated energy with solar panels can be presented as is solar panels are operating at 100% of their capacity during 20% of time during one day and wind turbines 30% respectively. In addition to already mentioned references and reliability indicators mentioned, some of the MTBF and MTTR figures (diesel generator, circuit breakers, etc.) used in this paper derive from [13]. IV. RESULTS All results in this study derive from reliability assessment software Windchill Quality Solution 10.0. Results of reliability assessment are presented in Table II and Figure 11. Results of availability assessment are presented in Tables III and IV and also in Figures 12 and 13. TABLE II
Fig. 9. FTA of AC architecture side B with wind system
RELATIVE RELIABILITY AFTER TWO YEARS
Results derive from Fault Tree Analysis method that is based on intuitive and graphical methods of failure analysis. FTA is a top-down deductive approach to failure analysis that starts by definition of undesired event and proclaiming it to be the Top event [12]. Connections of top and lower events are created by the gates based on Boolean algebra.
AC architecture DC architecture
Side A 16%
Side B Solar 38%
Side B Wind 0%
97%
90%
52%
As indicated in Table II, power branch with lowest reliability after two years of operation is the wind based in AC architecture while DC based architecture supplied through AC commercial grid with back-up generator is 97% more reliable.
Fig. 13. Overall facility availability when both A and B side are present
V. Fig. 11. Reliability results of every side in both architectures
TABLE III RELATIVE AVAILABILITY FOR EACH BRANCH
AC architecture DC architecture
Side A 0,01673%
Side B Solar 0%
Side B Wind 0,00187%
0,01705%
0,006%
0,00788%
TABLE IV RELATIVE AVAILABILITY ON FACILITY LEVEL
AC architecture DC architecture
Side A 0%
Side B Solar 1E-7%
4E-7%
4,7E-7%
CONCLUSION
Results of reliability assessment indicate that systems based on alternative energy supply (solar and wind) are less reliable compared to conventional solutions in Telecom facilities that are based on power supply from commercial grid with backup diesel generator. Also, systems (power branches) that incorporate alternative energy supplies tend to be less available compared to conventional power supply. Among alternative based systems it appears that wind based systems are less reliable and more available compared to solar systems. Despite lower reliability and availability when alternative energy supplies are paralleled with conventional systems total energy infrastructure of the facility tends to have very high availability and that is especially outlined when topologies based on DC distribution system are used. Final conclusion to this paper is that usage of DC architecture can improve overall facility availability in situations when alternative energy based power systems are used and also indicate that with alterations in architecture DC systems have the potential to increase the availability level even further by opening up the architecture allowing for multiple branches to connect to main bus systems. Further research needs to be carried out by making the models more dynamic and allowing for impact of maintenance actions and wind masses / solar radiation availability distributions on overall facility availability, what can be achieved by application of Monte Carlo method. REFERENCES [1]
[2]
Fig. 12. Availability results of every side in both architectures
[3]
A. Beton, C. Abbayes, S. Iyama, L. Stobbe, S. Gallehr, L. Günter Scheidt, “Impacts of Information and Communication Technologies on Energy Efficiency, Final report – Executive summary”, European Commission DG INFSO, September 2008 UPSonNet NewsLetter, “Impact of Backup Batteries on UPS Reliability”, Newsletter April 2010, http://www.upsonnet.com/Newsletter2010/April.html, 10.07.2012 Shaanxi XinTong Intelligent Technology: MPPT Control System, XinTong Solar 2011, Shaanxi XinTong Intelligent Technology Co.,Ltd, China, 2011.
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
T. Loehlein, “Maintenance is one key to diesel generator set reliability”, published on October 4, 2013 in Latest EPSS News, 2013 http://mgisys.com/maintenance-one-key-diesel-generator-setreliability/ R. Miller, “The Year in Downtime: Top 10 Outages of 2012”, Data Center Knowledge, web published, (2012) http://www.datacenterknowledge.com/archives/2012/12/17/the-yearin-downtime-top-10-outages-of-2012/ G. TamizhMani, “Testing the reliability and safety of photovoltaic modules: failure rates and temperature effects”, TÜV Rheinland PTL & Arizona State University, Tempe, Arizona, USA, http://www. tuv. com/media/usa/aboutus_1/pressreleases/PTL_Magazine_Article. pdf (consultado 18 de Agosto de 2011) 2010. A. Realini, E. Bura´, N. Cereghetti, D. Chianese, S. Rezzonico, “Study of 20-year old PV plant (MTBF Project) ”, 17th EPVSEC, Munich, Germany, 2001. M. Vasquez, I. Rey-Stolle, “Photovoltaic module reliability model based on field degradation studies, Progress in Photovoltaics: Research and Applications”, Volume 16, Issue 5, pages 419–433, John Wiley & Sons, Ltd., August 2008 A. Realini, “MTBF – PVm Mean Time Before Failure of Photovoltaic Modules”, Federal Office for Education and Science BBW, Final report BBW 99.0579, June 2003 P. Tavner, Reliability & Availability of Wind Turbine Electrical & Electronic Components, RELIAWIND Training Course, Helsinki, June 2009 Department of Defence USA, “Reliability, Availability, Maintainability, and Cost Rationale Report Manual”, Office of the Secretary of Defence, Washington, DC, 2009 E.O. Schweitzer III, B. Fleming, T.J. Lee, P.M. Anderson. “Reliability analysis of transmission protection using fault tree methods”, Proceedings of the 24th Annual Western Protective Relay Conference, pp. 1-17, (1997) Headquarters Department of the Army, “Survey of Reliability and Availability Information for Power Distribution, Power Generation, Heating, Ventilating and Air Conditioning (HVAC) Components for Commercial, Industrial and Utility Installations”, Technical Manual, TM 5-698-5, Washington, DC, (2006)
