To Corrupt Or Not To Corrupt

To Corrupt or Not to Corrupt by Ed Opdfamily

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

Voltage Stability Impact of Electric Vehicles

Reactive power consumption or injection is a promising feature out of electric vehicle charging. In [1] and [2], the authors present the analysis of the  reactive power control capability of an electric vehicle charging system to support the power system. Reactive power support and economics from the electric vehicles were discussed in references [3] and [4].

The electric vehicle charger follows the modes of operation [1]:

Electric vehicle charger operating modes [1].

Given these modes, analyzing power system voltage stability with electric vehicle charging would be needed. PV and QV curves will be helpful to assess the impact of the different charger operating modes as well as transient voltage stability simulations. This would be a welcome addition to the increasing literature of vehicle to grid (V2G) especially when the grid operator coordinates a large fleet of electric vehicle with the power network.

Does the electric vehicle charging mode provide increased power transfer in terms of static voltage stability? Does the operating mode of an electric vehicle charger gives a better voltage recovery during transient periods?

These research questions can be analyzed by modeling electric vehicle charging operating modes integrated in a power system test case.

References:

1. 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.
2. 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.
3. 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.
4. 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.

E-Trikes and WESM

Using the 12-12-12 data from WESM, I plotted here the Luzon demand and Luzon LWAP with the inclusion of E-Trike. The peak load for this day was 7,191.7 MW (2 pm) and the lowest LWAP was P1,690.43 per MWh (4 am). For this day, the highest LWAP (P13,145.7/MWh at 6 pm) does not coincide with the peak load.

E-Trikes and WESM.

In the chosen scenario, the 100,000 E-Trikes will be aggregated and charged as one bulk load, but on the other hand, will take advantage of the LWAP at its lowest and be coordinated when the system demand is also at its lowest (off-peak) both from 3 am to 5 am.

Though the 100,000 E-Trikes are envisioned to hit the streets by 2017, it is necessary to study a "what-if" condition on whether the present generation capacity, at least in Luzon, will be able to accommodate the new 493 MW load of E-Trikes. From the NGCP website, the system capacity is 8,091 MW with peak load of 7,318 MW so that's why we have a generation reserve of 773 MW. If the charging of E-Trike is not done during the low load and low LWAP hours, the 493 MW of E-Trike will be added to the current peak load which will bring down the generation reserve to about 280 MW. If the largest contingency is more than 280 MW, the system will be operated at “Alert State”. This shows how important the timing of the E-Trikes’ charging when aggregated as one bulk load. Though when added as a load in the system, the E-Trikes as a load may impact the system price not as depicted in the graph.

The strategy of handling E-Trikes as an additional aggregated load in the power grid would be:

• Charge when the LWAP is at its lowest – from economic standpoint, it makes sense. The E-Trike aggregator will enjoy economic benefits rather than utilizing uncoordinated charging related with LWAP which is to charge at random during a given day.
• Charge when the demand is lowest – from generation capacity and system reliability viewpoints, this will provide support to the power system. Coordination of the E-Trike load with the demand curve may delay the need for additional generation capacity or investments.

In reality, some E-Trikes will be on the streets throughout the day/night. There are transportation needs to be met at night and any time during the day especially in urban locations so it is unlikely there will be 100,000 E-Trikes charging at the same time.

What is discussed here is a worst-case-what-if scenario which may allow us to think if the present generation capacity may be able to accommodate such 493 MW of E-Trike load. So as long as the bulk load does not plug into the grid during peak hours, economic and technical benefits are achievable.

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