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Showing posts with label POWER SYSTEMS. Show all posts
Showing posts with label POWER SYSTEMS. Show all posts

Saturday, August 3, 2013

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.

Thursday, December 13, 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.

Thursday, December 6, 2012

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.

Wednesday, December 5, 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

Monday, November 26, 2012

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

Wednesday, November 21, 2012

New Citations


Citing my work on “Utilizing Fuzzy Optimization for Distributed Generation Allocation,” IEEE TENCON 2007:

Citing my work on ““Static Voltage Stability Analysis for Electric Subtransmission System”, http://ebcano.files.wordpress.com/2008/07/microsoft-word-ebcano_vs_0908.pdf, 2008:


Tuesday, November 20, 2012

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.

Sunday, November 11, 2012

Integrating Computer Simulations in Electrical Engineering Courses


Abstract— At the deregulation of electric power industry, technical and value-based studies for planning and operations of power systems as outlined in electricity regulatory codes should be integrated in electrical engineering programs and promote the present scenario by undertaking power systems applications and incorporate computer simulations to stimulate students' interest and increase their insights with the on-going deregulation of the industry.  This paper provides experience of incorporating computer applications and simulations in undergraduate and graduate programs considering present curriculum and subject offerings. 

Index Terms— electrical engineering education, computer simulations, power systems

Download the full paper here.

Friday, November 2, 2012

New England 39 Bus Test System

The New England 39 bus test system is a power system test system usually utilized for dynamic simulations test and research. It is believed that this is an actual equivalent system of the New England grid in 1960s [1].


The data I utilized here comes from [2], where the power flow and dynamics data were given in PSS/E v29 format which were loaded into PowerWorld. The data has 1 kV base voltage in all buses which I changed to 345 kV to reflect the New England system voltages. In the PowerWorld's transient stability data validation (this is very cool!), I accepted the corrections identified in the dynamic data, mostly are time constant depending on the time step being studied.

Normally in stability simulations, it is imperative to run a no fault simulation or what they call flat run to verify that dynamic models are behaving in a manner without disturbance thus expecting flat plots of parameters.

Generator angles for no fault simulation.

A stub fault is another practical test if the response of the dynamic models is correct for a simple and fast fault disturbance. Here are example plots from a stub fault at bus 1 at 1.0 seconds and cleared after 0.1 seconds without tripping any line.

Generator angles for stub fault simulation.

Generator speed for stub fault simulation.

Bus frequency for stub fault simulation.

Bus voltages for stub fault simulation.

If you want the New England 39 bus test system, email me at ebcano@gmail.com.

References:
[1] Power Systems Test Case Archive. Available on-line: http://www.ee.washington.edu/research/pstca/dyn30/pg_tcadyn30.htm
[2] Pablo Ledesma, New England Test System, IEEE 39 Bus System, 10 generators, in PSS/E format (version 29). Departamento de Ingeniería Eléctrica Universidad Carlos III de Madrid. Available on-line: http://electrica.uc3m.es/pablole/new_england.html



Thursday, October 18, 2012

Cost Allocation of SPS Service Using Cooperative Game Theory


Power systems planning and operations are usually defined by N-1 criterion. This means that in an event of a single contingency, no remaining connected transmission elements will be thermally overloaded, no bus voltage will be outside of acceptable limits, no system interface limit is violated, and system stability is maintained.

Special Protection Systems or SPS are widely utilized for increasing power transfer in transmission systems at the same time respecting security constraints [1]. SPS applications usually are generation rejection schemes (GRS), line/transformer transfer tripping and load shedding. GRS are designed to mitigate overloading of a transmission line or lines after an N-1 contingency near the vicinity of a generating plant or are employed to arrest increasing dynamic oscillation which may lead to unstable system conditions. Without the GRS, generation output is curtailed to satisfy the N-1 security criterion. With the GRS, the output of the generation is increased thereby increasing power transfer. Further, GRS also mitigates or delays the possibility of transmission expansion or investment due to transmission capacity constraints.

In a locational marginal pricing based electricity market, curtailment of generation (without GRS), specifically of a cheap generation due to the security N-1 criterion can be considered as transmission congestion. Transmission capacity limitations impede the generation output thereby decreasing the profit opportunity of the generation company (GenCo).  If a GRS is installed for this GenCo, the output of the GenCo is increased and thus there is a clear benefit for the GenCo in terms of profit. When transfer capability is limited, without GRS, the profit of a transmission owner (TO) is decreased due to less power wheeling charges. With the GRS, wheeling charges increase as a consequence of the added power transfer. This premise is the same with the electricity system and market administrator, called independent system operator (ISO), since the ISO charges for cost-based services including scheduling, system control and dispatch.  For the demand side, when generation output is curtailed due to congestion, without GRS, the resulting nodal prices at the demand’s location maybe higher than when a GRS is in place to increase generation output from a cheap generation.

GRS installations have embedded cost and actual service cost [3]. Since electricity market participants have various benefits in having a GRS installation, the cost of the SPS/GRS service must be allocated among the participants. Cooperative game theory [4-5] can be utilized in allocating fair cost on the beneficiaries of the SPS service.

The PJM 5 bus test system [6], shown Figure 1, is to be utilized as an example for the application of cooperative game theory in sharing the SPS service cost among power system organizations.

Figure 1. PJM 5 bus test system.

References:
[1]     W. Fu, S. Zhao, J. D. McCalley, V. Vittal, N. Abi-Samra, “Risk Assessment for Special Protection Systems,” IEEE Transactions on Power Systems, vol. 17, no. 1, pp. 63-72. February 2002. Available: home.eng.iastate.edu/~JDM/WebJournalPapers/RiskAssessentSPS.pdf
[3]     J. K. Earle, “Functional unbundling of special protection systems as a required interconnected operating service in a deregulated environment,” MSEE Thesis, University of New Brunswick, 1997. Available: dspace.hil.unb.ca:8080/handle/1882/42522
[4]     H. Singh, “Introduction to Game Theory and Its Application in Electric Power Markets,” IEEE Computer Applications in Power, IEEE Computer Application in Power, vol.12, no.2, pp. 18-20, 22, Oct.1999.
[5]     J. Mepokee, D. Enke, B. Chowdhury, “Cost allocation for transmission investment using agent-based game theory,” International Conference on Probabilistic Methods Applied to Power Systems, Iowa State University, Ames, Iowa, September 12-16, 2004.
[6]     L. Fangxing, B. Rui, "Small Test Systems for Power System Economic Studies," Proceedings of the 2010 IEEE PES General Meeting, Minneapolis, MN, July 25-29, 2010.

Tuesday, September 25, 2012

Mindanao Approximate Grid Model

Here is your Mindanao Approximate Grid Model.


Mindanao Approximate Grid Model in PowerWorld



In coming up with the Mindanao model, I still followed the procedure I have developed in this post, with the following diversions:

  •  The transformers’ rating in this model are assumed, I can’t find any public information on the grid transformer ratings.
  •  The transmission lines’ ratings were assumed to be 100 MVA for the 69 kV lines, 215 MVA for the 138 kV lines (consistent with the Visayas modeling) and 300 MVA for the 230 kV lines.
  •  There is no publicly available for demand allocation for the Mindanao model. For this approximate model, the load distribution was based on the population of each region (group of provinces) from this Wikipedia page (http://en.wikipedia.org/wiki/Mindanao). I started with having 1200 MW of load and partitioned it per percentage population where the load substations are located.
  •  The network configuration was derived using the following data rich public sources:



Again, this is an approximate model and does not attempt to replicate what NGCP or WESM is using and the model is developed for educational and research purposes. There is no publicly available Mindanao grid model to benchmark this approximate model.

Again, a big gigantic thanks to PowerWorld for the very user-friendly and very visually attractive tool.

You can download the Mindanao approximate network model here, if you bump into a dead link, please drop me an email.


Sunday, September 23, 2012

Kundur Two-Area Test System


Kundur's two-area test system, from Prabha Kundur's book "Power System Stability and Control", is a power system utilized mostly for testing dynamics of solving stability issues.  Most researchers and engineers worked on this system to analyzed HVDC and FACTS impact on the transient stability. Other works were focused on small signal stability effect of such devices and/or Power System Stabilizers (PSS).

Single-line diagram of the Kundur two-area system.

The left part of the system is Area 1 and right part is Area 2. The ties (lines between buses 7, 8 and 9) are 110 km long thus the interconnection is rather not strong.

The system has dynamic data for the four machines and their exciters and stabilizers, aside from the power flow data. I took the power flow and dynamics data from "Implementation of an Adaptive Controller for Controlled Series Compensators in PSS/E". I adjusted the tie lines' data since the paper indicates that the lines were 150 km.

I will probably post power system dynamics tests using this system in the upcoming months (impact of PSS, critical clearing times, etc.).

You can download the test system built on PowerWorld v16 using this link.

Friday, September 7, 2012

Visayas Grid Approximate Model


I have developed the Visayas Grid approximate model using available public data following the procedure given in my approximate Luzon network model. For the Visayas model, I used the line parameters given in the book “Probabilistic Transmission Planning” as shown below.


The single-line diagram was posted previously at wesm.ph but not currently. Still, publicly, Nick Nichol’s website has it – link.

Again, this is approximate and does not attempt to replicate what NGCP or WESM is using. Nevertheless, this model can be utilized by electrical engineering instructors in teaching power systems, analysis and issues in the electric power industry. It can be useful for computer based laboratory exercises in power systems, transmission and distribution. It is useful for research for technical reports or thesis during senior year. If there are Filipino electrical engineering instructors open to discussing how to use this model, I am very willing to cooperate and we can do this via skype or google+.

Some notes on developing the Visayas grid model:
  • The Visayas submarine cables are an important components together with the shunt reactors. Precise modeling of these components is not attempted.
  • The nature of Visayas grid is that it is not a meshed power system but is a radial power system: from Leyte-Samar to Bohol and Cebu to Negros to Panay Island. This means power flow solution algorithm being used can be tricky unlike in meshed power systems like that of Luzon.
  • Validating this model can be cumbersome, apply generation MW/cost bid parameters from wesm.ph and see if the locational marginal prices of this model and that of posted at wesm.ph matches up. If you would like to cooperate on this, I am open to doing it in PowerWorld. 

I’m not connected to PowerWorld, nor I’m endorsing it. It’s just that I am using it and because PowerWorld has practical power system applications like power flow, contingency analysis, shift factor calculations, optimal power flow, security constrained optimal power flow, short circuit analysis, and transient stability just to name a few. 

If you have questions or want the model, drop me an email at ebcano@gmail.com. Or download the model here.



Friday, May 11, 2012

Averting The Predicted 2013 Power Crisis

Google this "Rowaldo Del Mundo".

Instantly, you read lines and lines of the upcoming power crisis in the Philippines. At least my title says "predicted". Just like the forecasted electric demand, the power crisis supposedly happening in 2013 is forecasted, too. It is uncertain. Though the numbers tell us the generation capacity is short by that time compared to the demand, not only investments in generation capacity will surely help.

WESM has been employing demand response control in Visayas which prove to be effective in peak shaving. Large customers who own their generation in their facility help out in alleviating the need to put up power plants, which take some time to build, when they voluntarily interrupt their grid connection and depend on their in-house energy sources. In this case, WESM may design a demand response program which can provide peak shaving for normal and emergency grid operations. This may delay the shortage generation from short to medium term. This will also lessen transmission congestion since local generation will supply local loads.

Second, it's time for WESM to design a installed generation capacity market. The spot market in energy brings competition in the short term which is good but it's short term and just pay for the variable cost of power plants. The variable cost covers fuel and operating expenses of putting out MW to the grid. In a capacity market, the market operator will provide signal for investors and reward payment for that fixed costs in building power plants.

Third, DOE must reward large customers who practice energy efficiency programs. Energy efficiency may not be significant in impacting the level of electricity demand, however, better than no action. Measure their consumption during peak hours and see if they are contributing to alleviate the generation shortage.

I hope to come back on this interesting topic by 2013 and see what happened and what did not happen. By that time, I will still use Google.

Saturday, March 26, 2011

Philippines' Earth Hour 2011 - A Success!

I woke up reading tweets from VECO on the load being dropped regarding the Earth Hour 2011 on March 26, between 8:30 pm to 9:30 pm. VECO reports:

"EARTH HOUR RESULTS: The highest load drop In the VECO franchise area was 18 MW. Thank you to all those who participated!"

"EARTH HOUR RESULTS: As of 9:30 demand for VECO franchise area dropped to 248.89 MW."

"EARTH HOUR RESULTS: As of 9:15 p.m. demand dropped further to 249.76 MW in the VECO franchise area."

"In the VECO franchise area , As of 8:45 p.m. demand dropped to 257.1 MW. As of 9:00 p.m. it dropped further to 254.68 MW."

"AS of 8:45 p.m. VECO load dropped from 266.646 MW to 257.503 MW. Thank you for your support to Earth Hour!"

So from, VECO reports, about 9MW dropped after 15 minutes of the start of the energy conservation. Less than a MW dropped at 9:00 pm. At 9:15 pm, another chunk of about 7MW was dropped. Fifteen minutes after that, less than a MW was turned off. So at the end of the Earth Hour, VECO tweets that about 18MW was conserved.

Conserving that amount of energy,18MWh, is a big pull. It is a big accomplishment. What more if we look at the overall picture in the Philippines as a whole.

Figure 1

Figure 2
Figures 1-3 illustrates the load trend from the past Saturdays of March 2011. If we want to know the impact of the hour, we look at the load reduction in March 26 compared to March 19, March 12 and March 5. In this way, we are assuming that the load cycle exercised by the residential, industrial and commercial consumers are all alike. The insets in the figures shows that the hour of 8 pm to 10 pm in March 26 is at the lowest level compared with the other Saturdays except for the Luzon between the March 5th and the 26th at around 10:00 pm. 

Figure 3
A simple quantification of the load reduction is conducted by subtracting the average MW difference with the March 26th to other Saturdays in March 2011. The table below shows the numbers. All negative MW difference are good indicators. The positive number is as discussed above.

Table 1
Last year's Earth Hour seems to have failed. This year, the Earth Hour in the Philippines is a resounding success!


Thursday, March 24, 2011

PHL Power Plants in Google Map

'There is no known exhaustive locational map of Philippine power plants on-line. So, from this need, I took my free time to work.

From Nick Nichols post on "Philippine Power Plants – Carbon Emissions", I got the link to Carbon Monitoring for Action (CARMA). CARMA has a massive database for power plants' carbon emission which also contains locations of the plants using latitude and longitude. Their database on the generating plants in the Philippines are around 512 power plants. The list includes generation connected to the transmission grid, embedded generation and some generation used by industrial and commercial facilities. Though they have that number of plants, only about 250 plants have specific location.

I utilized an online tool to generate the KML file for Google Map which is free from Earth Point. The tool requires a spreadsheet format of the dataset which was prepared in OpenOffice Calc, a free software. The KML file generated is also compatible with Google Earth.

Here are the figures of the mapping of the power plants.

PHL Luzon Power Plants

View PHL Luzon Power Plants in a larger map

PHL Visayas-Mindanao Power Plants

View PHL Vis-Min Power Plants in a larger map

There are ways to improve this work. Classify the power plants using color code by fuel type, grid or distribution or industrial connected, or by classifying them by capacity level or by classifying the plants' cost of power.

The keyword here is FREE. Free time. Free data. Free tools. Good project!

Update: I categorized the power plants by region -- Luzon and Vis-Min. The map displays are having error on this blog because of the limitation of number of rows read by Earth Point. 03-25-2011

Tuesday, March 22, 2011

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.

Friday, February 4, 2011

Citations

Here is a list of citations I got from Google search on my technical work:

  1. Utilizing Fuzzy Optimization for Distributed Generation Allocation, TENCON 2007 - 2007 IEEE Region 10 Conference, Oct. 30, 2007-Nov. 2, 2007, Taipei, Taiwan – on-line: http://www.ieeexplore.ieee.org/xpl/freeabs_all.jsp?isnumber=4428770&arnumber=4428814&count=405&index=43 in ”Incorporating Distributed Generation into Distribution Network Planning: The Challenges and Opportunities for Distribution Network Operators”, David Tse-Chi Wang, Doctor of Philosophy (PhD) Thesis, The University of Edinburgh, 2010– on-line: http://www.era.lib.ed.ac.uk/bitstream/1842/4621/2/Wang2010.pdf
  2. Utilizing Fuzzy Optimization for Distributed Generation Allocation, TENCON 2007 - 2007 IEEE Region 10 Conference, Oct. 30, 2007-Nov. 2, 2007, Taipei, Taiwan – on-line: http://www.ieeexplore.ieee.org/xpl/freeabs_all.jsp?isnumber=4428770&arnumber=4428814&count=405&index=43 in ”Optimum Distribution Generator Placement in Power Distribution System Using Ant Colony Algorithm” by Ghazanfar Shahgholiyan, MohamadAmin Heidari, Mehdi Mahdavi, Majlesi Journal of Electrical Engineering, Volum 3, Number 1, March 2009 – on-line: http://ee.majlesi.info/index/index.php/ee/article/view/184
  3. Solving Non-Technical Losses Problem by Technical Methods, Elektrisidad Pilipinas, September 2008, - on -line: http://elektrisidadpilipinas.blogspot.com/2008/09/solving-non-technical-losses-problem-by.html in “Analysis of Non-Technical Losses and its Economic Consequences on Power System” , Master of Engineering Thesis by Tejinder Singh, Thapar University, Patiala, India, June 2009 – on-line: http://dspace.thapar.edu:8080/dspace/bitstream/10266/911/1/Tejinder_PSED.pdf
  4. Analysis of Voltage Unbalance Regulation, October 27, 2006, Annual National Convention of Institute of Integrated Electrical Engineers (IIEE), PICC, Manila, Philippines in “On the Assessment of Voltage Unbalance”, Seiphetlho,T.E.;Rens,A.P.J.; Sch. for Electr., Electron. & Comput. Eng., North West Univ., Potchefstroom, South Africa, 2010 14th International Conference on Harmonics and Quality of Power – on-line: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5625366
  5. Luzon Approximate Network Model, Elektrisidad Pilipinas, July 2010, - on -line: http://elektrisidadpilipinas.blogspot.com/2010/07/luzon-approximate-network-model.htmlThe High Cost of Electricity”, The Philippine On Line Chronicles, July 2010 – on-line: http://thepoc.net/commentaries/8970-the-high-cost-of-electricity.html in “
Note that numbers 3 and 5 are post entries in this blog. Number 4 is a technical paper presented in an Institute of Integrated Electrical Engineers (IIEE). 

Why I posted this? Simple. Any good idea when put out for the public can be a resource for others. 

Tuesday, October 26, 2010

Application of N-1 Contingency Analysis

The Philippine Grid Code (PGC) regulates that transmission systems must be N-1 compliant. Any single component in outage must not result to any thermal overloading of lines, which means above 100% of MVA rating, and no voltage limits will be violated whether overvoltage or undervoltage. Voltage limits are 0.95 per-unit voltage and 1.05 per unit voltage.

In this post, we demonstrate how to apply this application to the Luzon Approximate Network model though we will focus only on the thermal loading of lines. I am assuming any voltage violations can be eliminated by transformer tap change or capacitor switching at the substations of power plant switchyards.

In Powerworld, there are two ways, I can think of, to do this. Open the case and manually switch of any branch then solve the case. Or use the automated way to apply contingency analysis.

Before we go further, here are initial evaluations needed to undergo: (1) no existing overloads in the pre-contingency, (2) no existing voltage violations, (3) generating machines are not over dispatched.

In the Philippines, the substation configuration is usually a breaker and a half arrangement. With this assumption, the single branch contingency or N-1 is adaptable. In other power systems abroad, there are design contingencies which will trip several lines, not only one branch, for an N-1 set-up. These contingencies are called design contingencies. Also, any bus (outage of 1 or more lines) or breaker fail (outage of one or more lines) contingency are not considered in the N-1 analysis at least in the Philippines.

Here are the steps for N-1 analysis:

1.    Open the case in Powerworld
2.    At Edit Mode or Run Mode, in Case Information palettes go to Limit Monitoring to check existing pre-contingency thermal overloads. Identify overloads at the column of % of Limit Used. Redispatch generation to correct pre-contingency overloads, if possible. If no pre-contingency overloads are present, proceed to N-1 analysis (Figure 1).

Figure 1.

3.    At Run Mode, go to Tools. Click on Contingency Analysis, a new window will open (Figure 2). In Contingencies, click Auto-Insert to create contingency to be applied to the power network. Another window will open then click Do Insert Contingencies, notice the options of contingency combinations (Figure 3).

Figure 2.
Figure 3.

4.    Program will ask you to confirm 92 contingencies to be created (Figure 4). Click Yes. This will create the contingencies and will input the contingencies in the window (Figure 5). Notice Status as Initialized.

Figure 4.
Figure 5.

5.    Click Start Run to begin N-1 contingency analysis.
6.    When the simulation is finished, at the left bottom of the window, there is a status update for the finished contingency calculations (Figure 6).

Figure 6.
Figure 7.

7.    To view results, click Combined Tables, then to Legacy Tables ' click Contingency Definition-Violation Table' Copy to Clipboard. When finished, paste in notepad or any MS Word type program. You can also view result per contingency when you click at any one of the contingency at the window (Figure 7).

If I am working on this I will analyze the results and even apply the contingency manually and observed the resulting overloads. This means, I don't depend on the software's results but "analyze" the results. Why do the overloads happen? What were the pre-contingency loadings at the overloaded elements? Why is the contingency credible enough to produced those thermal violations? If in operations planning horizon, what are the actions needed to mitigate the thermal overloads?

In doing N-1 analysis, don't let the power system engineer be an "N". Meaning, he must not let himself be taken away by the software and he must not depend fully on the software's results but he is to gain more understanding on the network when examining the results.

Monday, July 19, 2010

Luzon Approximate Network Model

The past days have been a great reminder to my long time personal project which I have not attended to. The newly appointed DOE Secretary raps the NGCP's lack of transparency. This is not a surprise since NGCP now operates as a private company unlike before. Mr. Nick Nichols blogged about the communication of NGCP and Meralco to the public at large. GMA News has done a geographical reporting and analysis of floods in the past, which I think Mr. Nichols is suggesting the same type of reporting for outages.

The difficulty being cited produced fire in me again to re-visit and finish this project. I have been thinking about this project - an approximate Luzon grid model. Of course, data won't be coming from NGCP or the WESM. I believe I can do it by merely using public data. Public data like the following:

1. WESM Market Network Model - has present system configuration and capacities of plants, substations and transmission lines
2. Transco Annual Report - has capacities and distances of several lines
3. Market Simulation of Luzon Grid submitted to the ERC - has a reduced 30 bus model of the Luzon grid, which I think is sufficient for the model I am planning, and provides load allocation for those 30 buses.

Using free Powerworld 40 bus version software to act as my data bank and to simulate the model, I already got an approval from Powerworld Corporation to go ahead with this research, and use Google Earth to measure distances between substations.

This model can be utilize for public discussions and probably have it available for the academic community to have a working power system model.

One weakness, I foresee, in this model is there is no publicly available grid impact study for which I can compare the results of the power flow simulations. Yet, I still believe it's a worthy project.