No Wind for Northwind

Northwind plant, located at the northern part of Luzon grid in the Philippines has a capacity factor of 16.2% from March to July 2013. And that is six months.

This means the said wind farm has an average dependable capacity of 4 MW out of total of 25.5 MW maximum capacity which is very low compared to the global wind power capacity factor of 28% and to the US wind power capacity factor of 31.8%.

Significantly, this means that  for a Luzon peak load of 6,800 MW we need about 42,000 MW of wind power capacity to supply Luzon grid on wind power alone, and that's a lot!

Capacity factor and daily output of Northwind power plant from March to July 2013.

Electric Vehicle Charging Station Location using Fuzzy Optimization

Electric vehicle charging station location is a basic problem in integrating electric vehicles in electric power systems. An electric vehicle plugged into the electric distribution system may absorb or produce active and/or reactive power [1-4] depending on the need of the electric power system, Table 1 below.

Electric vehicle charger operating modes [4].

When finding the location of EV charging stations in order to support the electric distribution systems, the cost of EV charging, the impact on distribution system losses and voltage profile of the system are parameters needed to be considered. These variables are to be looked into when plugged in EV is either acting as a generator or a load given a system demand level.

Recent studies have solved this EV charging station location problem. In [5], a mixed integer programming solution was developed with site accessibility, local jobs and population densities and trip attributes as main constraints. A genetic programming approach is utilized in [6] for simulation of electric vehicles on a real map of a European city where the optimal solution of the charging infrastructure is derived based on mean trip times of electric vehicles. A two step procedure is proposed in [7] where the authors included environmental factors and service radius of EV charging stations in the screening first step and built a modified primal-dual interior point algorithm (MPDIPA) for optimal sizing of EV charging stations with the minimization of total cost associated with EV charging stations to be planned as the objective function with losses and voltage profile included in the problem. Reference [8] introduces an optimization process for sizing and siting of EV charging stations, modeling the charging demand and the structure of road network to where the solution approach was graph theory. Level 1 and level 2 charging stations are discussed in [9] and how to allocate them for residential EV users using simulation-optimization strategy.

Recent studies do not consider uncertainties and imprecision which can be captured using fuzzy optimization. Fuzzy set theory can provide a simpler yet powerful solution for allocating EV charging stations in electric distribution systems. The Civanlar test system [11] will be utilized for the study and assuming that capital investment of the EV charging station is the same for all distribution system candidate nodes while considering time of use (TOU) electricity tariff, distribution system losses and voltage profiles.

References

[1] Chenye Wu, Hamed Mohsenian-Rad, and Jianwei Huang, “PEV-based Reactive Power Compensation for Wind DG Units: A Stackelberg Game Approach”, in Proc. of the IEEE Conference on Smart Grid Communications (SmartGridComm’12), Tainan City, Taiwan, October 2012.

[2]   Chenye Wu, Hamed Mohsenian-Rad, Jianwei Huang, Juri Jatskevich, “PEV-Based Combined Frequency and Voltage Regulation for Smart Grid”, the 3rd IEEE Innovative Smart Grid Technologies Conference, Washington DC, Jan 2012.

[3]    M. Kisacikoglu, B. Ozpineci, L. M. Tolbert, "V2G Reactive Power Compensation Using a PHEV Bidirectional Charger Interface Rated at Level 1, 2, and 3 Charging Standards," IEEE Energy Conversion Congress and Exposition, Atlanta, Georgia, Sept. 12-16, 2010.

[4]     M. Kisacikoglu, B. Ozpineci, L. M. Tolbert, "Examination of a PHEV Bidirectional Charger System for V2G Reactive Power Compensation," IEEE Applied Power Electronics Conference, Palm Springs, California, Feb. 21-25, 2010, pp. 458-465.

[5]    Chen, T. D., et al, “The Electric Vehicle Charging Station Location Problem: A Parking-Based Assignment Method for Seattle”, on-line: http://www.caee.utexas.edu/prof/kockelman/public_html/TRB13EVparking.pdf

[6]    Hess, A. Et al, “Optimal Deployment of Charging Stations for Electric Vehicular Networks”, on-line:http://conferences.sigcomm.org/co-next/2012/eproceedings/urbane/p1.pdf

[7]    Liu, Zhipeng, Wen, F. and  Ledwich, G. F. , “Optimal Planning of Electric-Vehicle Charging Stations in Distribution Systems”, IEEE Transactions on Power Delivery, Jan. 2013, Vol. 28 , Issue 1.

[8]    Jia, L., Hu, Z., Song, Y., Luo, Z., “Optimal siting and sizing of electric vehicle charging stations”, 2012 IEEE International Electric Vehicle Conference (IEVC), 4-8 March 2012

[9]    Xi, X., et al, “Simulation-Optimization Model for Location of a Public Electric Vehicle Charging Infrastructure”, on-line:http://www.ise.osu.edu/ISEFaculty/sioshansi/papers/charge_infra.pdf

[10]“Siting Electric Vehicle Charging Stations”, on-line: http://www.sustainabletransportationstrategies.com/wp-content/uploads/2012/05/Siting-EV-Charging-Stations-Version-1.0.pdf

[11]On-line: http://ee.sharif.ir/~e_hajipour/index_files/Test_Cases_Data.pdf

Benefits from Electric Vehicles for the Philippine Power Grid

The last blogs I posted on electric vehicles (EV) may seem to have created the wrong impression in what I’m trying to do. I analyzed the loading impacts of E-Jeepneys and E-Trike to local electric distribution power system, specifically loading up a pole mounted distribution transformer. In practice, these scenarios are very real and can be prevented by planning and coordinating new loads which are the EVs under the government’s program.

The overloading of electrical equipment, at least locally, is just one tiny bit on one side of the fence. EVs when largely manufactured and utilized can be a resource of power grid reliability and security support, just like any other ancillary services.

References [1-4] provide simulations and analysis on the following:

• Frequency regulation – NGCP procures frequency regulation from on-line generators which are called spinning reserves. A big bulk of load can be aggregated and adjust accordingly to maintain system frequency, like a spinning generating reserve. I posted that the vision of DOE to have 100,000 E-Trikes by 2017 will have a MW load greater than the Quezon Power plant which is 480 MW. EV charging is via power electronic converters/inverters which are controllable. The charging of E-Trikes if coordinated accordingly to serve a load serving as a spinning reserve is a promising capability for E-Trikes or any large scale electric vehicle when aggregated.

• Reactive power compensation – Again, NGCP installs and may procure voltage support services from generation or invest on its own reactive power devices. In [3], the authors described an EV charging system which can be a source of reactive power compensation. This system is allowed to inject or consume reactive power whichever is needed by the power system in real time. In [4], the authors provided a pricing methodology for wind farm reactive compensation provided by an EV charging park.

• Contribution to system security – NGCP procures contingency reserves per Philippine Grid Code.  These are generators which are on-line ready to respond (increase or decrease their output) in times of a system disturbance. Authors in reference [2] indicate that EV chargers have response time faster than generators. In this case, going back to the 100,000 E-Trike, you may have a large “generator” providing that contingency reserve to mitigate any undesirable system condition due to a disturbance.

For large scale E-Trike or E-Jeepney charging, which is envisioned in the Philippines, these features would become income generating resources for EV operators or aggregators. Also, the NGCP will have another source of ancillary services which can be counted upon to support grid reliability and security.

References:
[1]    Chenye Wu, Hamed Mohsenian-Rad, Jianwei Huang, Juri Jatskevich, “PEV-Based Combined Frequency and Voltage Regulation for Smart Grid”, in Proc. of the IEEE PES Innovative Smart Grid Technologies Conference (ISGT’2012), Washington, DC, January 2012.
[2]    Sakis Meliopoulos, Jerome Meisel, George Cokkinides and Thomas Overbye, "Power System Level Impacts of Plug-In Hybrid Vehicles." PSERC Document 09-12, PSERC Final Report. October 2009.
[3]    M. Kisacikoglu, B. Ozpineci, L. M. Tolbert, "Examination of a PHEV Bidirectional Charger System for V2G Reactive Power Compensation," IEEE Applied Power Electronics Conference, Palm Springs, California, Feb. 21-25, 2010, pp. 458-465.
[4]    Chenye Wu, Hamed Mohsenian-Rad, and Jianwei Huang, “PEV-based Reactive Power Compensation for Wind DG Units: A Stackelberg Game Approach”, accepted for publication in Proc. of the IEEE Conference on Smart Grid Communications (SmartGridComm’12), Tainan City, Taiwan, October 2012.

E-Trike: Impact on Distribution Transformer Loading

The partnership of DOE and ADB envisions having 100,000 E-Trikes between now and 2017 [1]. Each E-Trike will have about 3 kW to 5 kW electric power usage and will be charging for about 45 minutes to 1 hour.

A study by DOE in collaboration with United Nations [2] indicated that one E-Trike will consume 1.8 MWh in one year. So to check the values here: 1.8 MWh divided by 365 days, an E-Trike will take 4.93 kWh. Below is a table for the kW loading of E-Trike(s). Note that 100,000 E-Trikes is even above the capacity of Quezon Power plant which has 480 MW capacity.

In this post, several scenarios of charging time and number of E-Trikes are presented using 4.93 kW charging power.

Figure 1 presents the connection of 1 E-Trike during three separate hours in the evening versus a 25 kVA distribution transformer. In here, the assumption is the E-Trike driver uses the vehicle from 8am to 5pm, then comes home to his family and charges his vehicle on those random hours. If 1 E-Trike is being connected with the base residential load curve, the 25 kVA distribution transformer will have no overloading.

Figure 1

Figure 2

Figure 2 shows the plots of several number of E-Trike being charged on separate hours of the day. For this case, the assumption is the E-Trike operator/businessman who has several vehicles takes advantage his vehicle charging according to the Time of Use (TOU) rates of the distribution utility. He may utilize a timer-switch to program when the charging begins and ends.  A 25 kVA distribution transformer will overload for the assumed hours for both during evening and during morning except for 3 E-Trikes during morning. A distribution utility coordination with this E-Trike operator will identify that an upgrade from 25 kVA to 37.5 kVA transformer will provide mitigation of the overload unless other households in the service area will shut down all their appliances ( voluntary load shedding).

References:

[1] Consultants sought for $500-M e-Trike project. Available: 

http://business.inquirer.net/74917/consultants-sought-for-500-m-e-trike-project [2] Philippine Electric Vehicle Project. Available: http://cdm.unfccc.int/filestorage/3/K/Y/3KY4J2IW70AZPTX9MS6VGU1QORNE8F/Etrike%20CPA-DD%20ver1.pdf?t=MGF8bWVremlifDCLzXH3EtuSp9elyiR5MR_6

Revision on Loading Impacts of PHUV – E-Jeepney

Ms. Diana Limjoco, manufacturer of E-vehicles in the Philippines responded to my query and corrected my post on charging time of one E-Jeepney which I assumed to be 8 hours. According to her, an E-Jeepney can be charged fully at about 4-5 hours if done right.

Below, I updated the graphs for the loading impact of E-Jeepney(s) charging from 8 hours to 5 hours. No matter what the charging time is, a 25 kVA distribution transformer will suffer overloading for 1 PHUV scenario when charged during the evening and will be heavily loaded in other scenarios. If 2 PHUVs are charged at the same time, the 25 kVA distribution transformer will have severe overloads. And even if the transformer is rated 37.5 kVA, 2 PHUV charging at the same time will overload the transformer when combined with the base residential load.

In this case, the distribution utility has to be proactive in their operations planning in upgrading their distribution transformers or coordinate with consumers who have E-Jeepneys so as to prevent overloading of electrical equipment especially distribution transformers.

Dynamic Models and Simulations for Reduced and Approximate Philippine Major Island Power Grids

Since developing the power flow models of Luzon, Visayas and Mindanao, one step forward in these projects is to provide dynamic modeling of the generators, exciters, governors, etc.

I followed the references [1-3] for assuming models for each generation considering fuel types. Also, combined with these good sources, PowerWorld provides default data for the dynamic models including the generic wind generation dynamic models (for NorthWind generation, north of Luzon) and loads (motors and discharge lighting, etc).

For generation using diesel as fuel, I initially modeled the machine as GENSAL but WECC has indicated to use GENTPJ instead for reasons cited in reference [4].

As I'm using PowerWorld, I made advantage of the auto correction of dynamic data and proceeded with the validation of models.

As mentioned in other posts, I simulated flat runs and had the models respond as expected. The following plots are simulated three-phase faults where fault clearing time is in accordance with the Philippine Grid Code and assuming a single-line contingency.

Bus Voltages Plots for Fault on Balintawak 230 kV, tripping Balintawak-Araneta 230 kV Line (Luzon)

Rotor Angles Plots for Fault on Balintawak 230 kV bus, tripping Balintawak-Araneta 230 kV Line (Luzon)

Bus Frequency Plots for Fault on Lugait 138 kV bus, tripping Lugait - Tagaloan 138 kV Line (Mindanao)

Generator Speed Plots for Fault on Lugait 138 kV bus, tripping Lugait - Tagaloan 138 kV Line (Mindanao)

Various Plots for Fault at Quiot 138 kV bus, tripping Quiot-Banilad 138 kV Line (Visayas)

I'm planning to write a full paper on this work and if you are interested in the models or collaborate with me, drop me a message at ebcano@gmail.com.

References:
[1]    IEEE Recommended Practice for Excitation System Models for Power System Stability Studies, IEEE Std 421.5-1992
[2]    IEEE PES Working Group, Hydraulic Turbine and Turbine Control Models for System Dynamic, IEEE Transaction on Power System 7 (1992) 167-174.
[3]    Dynamic Models Package Standard 1. Available: http://www.energy.siemens.com/hq/pool/hq/services/power-transmission-distribution/power-technologies-international/software-solutions/Dynamic_Models_Package_Standard-1.pdf
[4]    Additional Information on GENTPJ Model. Available: http://www.wecc.biz/library/WECC%20Documents/Documents%20for%20Generators/Generator%20Testing%20Program/gentpj%20and%20gensal%20morel.pdf

Modeling FACTS Devices

There are two categories in modeling Flexible AC Transmission System (FACTS) devices in power systems: steady –state modeling and dynamic modeling.

Steady-state

For Unified Power flow Controller (UPFC), you can model this device by inserting a phase shifting transformer (PAR) between two buses connected with a transmission line(s). Since a PAR controls the power transfer by adjusting its tap, this can mimic UPFC response in a given condition. Other implementation [1] includes a bus with a generator and a bus with a load, which are not connected, inserted in a transmission line where the power flow is supposedly controlled.

For a Static Var Compensator (SVC), model a generator without MW output but with MVar (Qmax and Qmin) limits. The model is basically a synchronous condenser but enough to simulate the SVC response. Normally, the output of the SVC is dependent on the bus voltage where it is connected (maintaining a certain magnitude).

For a Thyristor Controlled Static Reactor/Capacitor (TCSR/TCSC), model a series reactor/capacitor along a given transmission line in the power flow case. Note that this is basically a series compensation model and in power flow, the compensation is seen as constant in all throughout the simulation.

In any case, you must assure that no pre-contingency impact violation is produced when you add a FACTS device in the power flow model before running contingency analysis, OPF or locational marginal pricing (LMP) studies.

Dynamics

For SVC, most power system application programs (PSS/E, PSLF, and PowerWorld) apply a Static Var Compensator dynamic model (CSVGN), for example in PowerWorld [2].

For UPFC and TCSR/TCSC, for the above software packages there is no known modeling for dynamic simulations, unless a user model is developed. Most research on dynamic modeling of these devices are implemented in MATLAB or PSCAD/EMTDC.

References:
[1]    A. Kazemi, et al, “A comprehensive load flow model for UPFC and its combination with ESS.” Available: http://www.emo.org.tr/ekler/986405e39c5a796_ek.pdf
[2]   http://www.powerworld.com/files/Block-Diagrams.pdf

Reduced and Approximate Models of Philippine Major Island Power Grids

Abstract—The restructuring of electric power industry brings challenges and opportunities among its stakeholders. Economic and engineering analyses brought forth by these changes are usually tested on power system test models to study different strategies. In a developing country, like the Philippines, where commercial and security concerns may prevent the availability of these test systems, the involvement of research and academic communities’ maybe limited. This paper reports the development of reduced and approximate power system models for major islands in the Philippines using publicly available data which can be utilized for research and academic purposes.

Index Terms—Electric power test systems, interconnected power systems, electric power system modeling.

Download the full paper here.

Wind Power Capacity Value in the Philippines

Prof. Rowaldo Del Mundo, my respected professor in UP-Diliman, came out with the study of quantifying the value of wind power in terms of capacity last year. I believe this is welcome advancement in understanding the contribution of wind energy in the country. As investments in renewable energy sources are coming in, studies like this are sure to support the anticipated technical and economic impacts of integrating wind power into the grid.

However, just as I was taught by the good professor, there are some loopholes in the study I thought needing some discussion thereof.

First, the study considered wind power plants to have an equivalent forced outage rate (EFOR). Forced outage rate (FOR)  is computed using the mean time to failure and the mean time to repair of a component of a generating plant to be in service or not. The Philippine Grid Code defines FOR as:

From this premise, FOR is a component based value not a fuel availability based variable. Wind power is variable. A wind farm stops to produce power when wind stops blowing, not mainly because a component in the wind farm fails.

An accepted approach to overcome the FOR modeling of a wind farm is to model the wind power output as a negative load. Studies here and here by IEEE and NERC uses this practical strategy since load is variable and adding wind power increases the variability is the power system. With this, you don't have to assume an EFOR for electrical or mechanical components inside the wind farm since they don't really fail, its just that the wind is not blowing.

Second, the study's conclusion includes this: The maximum penetration limit is, at the end not a technical issue, it is an economic issue that must  be resolved based on willingness to pay of the consumers.

I remember that when the 1216MW Sual power plant suffered failure and resulted to a Luzon wide blackout. Imagine the peak load of Luzon as about 6500MW, the capacity output of Sual is 25% of that loading condition. Which gives us a scenario that a plant generating 25% of the demand level provides risk in the system operational reliability. If wind power penetration becomes 25% of any demand level, we are merely replicating the possibility of what happened in 2001 since wind is variable. The integration of any energy resource in any grid would always be a technical issue. That is why Prof. Del Mundo was part of the team who they developed the Grid Code and the Distribution Code.

A single study must not generalize such conclusion without looking at all angles and involving all stakeholders.

Third, the study cites that the capacity value of wind in the Luzon grid is nil. Zero. Nada. This is surprising. Any resource adds capacity. Any amount of energy resource penetration level adds value. Below is a figure from this IEEE study.

 

The figure above tells us that there is a certain capacity value relative to a certain amount of wind power penetration in various electric transmission systems. I am wondering what is very unique in the Philippine electric power systems to have wind power assessed as having no capacity value when added to the grid.  

Wind power will play an important role in the energy situation in our country though it is variable in nature. It will add resource and capacity together with conventional plants, much needed as demand grows. We must study its impact carefully.

Solar Application at Princeton University Campus

This is a solar application at the campus of Princeton University near the main street of Nassau. The solar panels are energizing sign post including a map and bus line directions. The sign post can be switch on as depicted in Pictures 3 and 4.

Being a case of academic application of renewable energy, professors and students can draw a lot from this small scale renewable energy project. 

Picture 1

Picture 2

Picture 3

Picture 4

Solar Application at Central Park, Schenectady, NY

This a solar powered electric post at Central Park, Schenectady, NY. I am wondering though how many times does this electric post lights up during winter since normally cloudy days are dominant during snow days. Assuming the bulb has 100 watts, the 64 (2 x 32) solar cells must receive radiance to light the walkway towards the kids' playground.