Why the Philippines is Lacking in Power Supply Always and is Expensive Compared to its Asian Neighbors

September 24th, 2014 Posted in cost of power generation

Why the Philippines is Lacking in Power Supply Always and is Expensive Compared to its Asian Neighbors

Following is the outline of my power point presentation on “Why the Philippines is Lacking in Power Supply Always” and  why the Philippines has one of the highest power rate in Asia and the World.

If you need the pdf version, please email me so I could respond to your request.

 “Why the Philippines is Lacking in Power Supply Always”

By: Marcial T. Ocampo

        Energy Technology Selection and Optimization Consultant at

        OMT Energy Enterprises

Good afternoon and evening, Ladies & Gentlemen. I would like to thank the organizers and officers of UP ARISE for holding this important symposium to allow a healthy discussion on why electricity is among the most expensive in Asia and the world, aside from electric power lacking in supply always.  

I am Marcial Ocampo, a Chemical Engineering undergraduate and graduate student of the UP College of Engineering many decades ago when the hallways were free of iron grills and lecture rooms and amphitheaters were left unlocked most of the time without fear of losing valuable equipment and personal articles. Well, we had  no smart phones, iPads and laptops then, but only had our pencils, ball pens, notebooks and slide rules.
Executive Summary
I would like to provide you with my analysis as to the root cause of inadequate Philippine power supply and its high cost of power:

• Our least cost expansion planning fixes (“=“ constraint) the old power plants, rather than opening their capacity dispatch to economic and technical challenge (use “>=“ constraint rather than using “=“ constraint) by the proposed power plants in a multi-period least cost capacity expansion linear programming (LP) modeling exercise (“Best New Entrant”).
• By not doing so, the old and soon-to-be-retired power plants are still in the generation mix with very low reliability, thus when they conk out or when any of the newer plants undergo maintenance and periodic overhauls, the remaining supply is ALWAYS inadequate to meet future demand, aside from being expensive due to tight supply, and the economic consequence is very costly to the Philippine economy.
The country can never attain inclusive growth if power is scarce and expensive, since access to electricity is the greatest enabler of the poorer citizens of this country.
There is a need to use optimal (least cost) load dispatch to meet daily base load, mid-merit and peak load instead of the WESM paying all power producers the same cost of the last marginal plant dispatched wherein some plants with zero or negative bids is dispatched but paid at the bid of the last marginal plant. Optimal dispatch means getting paid based on your bid, so plants will strive always to be transparent, competitive and efficient.

Also, maintaining a capacity expansion plan with an average 50-60% capacity factor does not help assure that future plants come on time. This means some plants have 30-40% capacity factor because they are old and conks out frequently or not dispatched because they are expensive. On the other hand, the newer plants have 70-80% capacity factor with very little expansion allowance to 80-90% upper limit.
Since it takes between 3-5 years to plan, procure, install, test and commission a new power plant, maintaining an average 50-60% capacity factor result in recurring power shortages. A better plan is to maintain a 40-50% capacity factor to allow sufficient time to put into service new plants. (The more advanced economies strive for 30-40% average capacity factor thus giving them sufficient lead time to put in place additional capacity.)
Table of Contents (1)


•Revenues & Expenditures

•Energy & Power Taxes

•Total Revenues of Gov’t

•Total Expenditures of Gov’t

•Cash Budget vs. GDP & GNP

•Historical Capacity Utilization

•Forecast Capacity Utilization

•How to Reduce Energy & Power Costs

•How to Optimize Load Dispatch (“Least Cost” dispatch”)

•Least Cost Expansion Planning (“Best New Entrant” expansion)

•Distributed Generation (DG)

•Smart Grid

•Low Carbon Economy

•Feed-in-Tariff (FIT, FIT ALL)

•Fossil Fuel Price (oil, coal, natural gas)

•Conventional & Fossil Power

•Renewable Energy Sources

•Energy Storage Technologies

•Levelized Cost of Energy (US NREL)

•RP Formula by MTO

My presentation will attempt to present the magnitude of the energy and power industry in the Philippine economy, and its contribution to government revenues and taxes in order to provide funds to cover expenditures of the government for social services, security, infrastructure and development. I will present both historical and forecast data (outlook) to support my thesis that the lack of scientific and continues planning and innovation, wrong information and inadequate analysis, leading to wrong recommendations and solutions – is the root cause of the country’s lack of competitive, efficient, cost-effective energy & power infrastructure – resulting in lack of job opportunities and non-inclusive growth, especially the poor.

Table of Contents (2)

•Low Carbon Economy

•New Energy Plan Considerations

•Base Case A – Business As Usual

•Case B – Renewable Energy with FIT

•Case C – Nuclear Option

•Case D – RE FIT and Nuclear Option

•Power Generation Technologies (cheapest to most expensive)

•Project Finance Models (Biomass, Mini-hydro, Wind, Solar, Ocean Thermal)

•Comparative LCOE of Conventional, Fossil, Nuclear and RE Technologies

•How the must-run and cheaper RE with FIT can displace expensive diesel/bunker power

•Power Demand Profile (best, worst, realistic / most likely)

•Power Supply Demand Outlook

•Power Demand Growth Rates

•Power Demand Forecast (L, V, M)  – Electricity Sales, Gross Generation and Peak Demand from System Loses and Load Factor

I will present the strategic goal of the energy and power sector, identify the objectives, analyze the scenarios and alternative paths, prepare forecasts on each scenario, and analyze the results to see if that path leads to sustainable and environmentally benign development that will promote inclusive growth for all.

Table of Contents (3)

•Power Reserves & Contingencies – LFFR, Spinning, Backup)

•Power Development Plan Updates – 2012 to 2030

•Modeling Scenarios

•GDP & Power Demand Growth Rate Assumptions by Grid by Year (revised growth rates)

•Impact of Extreme Weather on Dependable Capacity of the Power Generation Technologies  (coal, diesel genset, oil thermal, gas turbine, CCGT, Geothermal, Hydro, Mini-hydro, RE (biomass, wind, solar)

•DOE Outlook – No Retirement (Luzon, Visayas, Mindanao)

•MTO Outlook – with Retirement Luzon, Visayas, Mindanao)

•Note: Visayas has revised both higher growth rate and historical growth rate assumption

I will present the short term and long term planning steps being conducted by the DOE to provide an optimal energy and power mix thru its least cost capacity expansion modeling runs.

  • The author (energy technology selection expert) has a blog at
  • One such article dealt on the topic: “Why the Philippines is Lacking in Power Supply Always”
  • Impact of power supply to GDP growth, Public Finance, and providing inclusive growth to the poor sectors of economy
  • Suggested solutions and the optimization of the renewable energy sources in the Philippines.

One of your officers, Nathalie Gabrielle Tatualla, has came across my blog on “Why the Philippines is Lacking in Power Supply Always”. She emailed me to ask if I could present my technical blog during their Renewable Energy program at the UP College of Engineering.

Revenues, Expenditures & Deficit

 A budgetary surplus of P56.7 Billion was registered in 2008.  Thru prudent and targeted expenditure and efficient tax collection, a budget surplus will prevent the country from following the “Greek Financial Meltdown”.  

I have been part of 3 gov’t task force and study groups on the first “The Emergency Task Force on the Impact of 100 US$/BBL Crude Oil Price in 2008”, the second “Independent Oil Price Review Committee of 2012”, and now the “Power Price Reduction Task Force of 2014”. In 2008, total revenues stood at P1,296 Billion of which P1,057 Billion (81.6%) came from taxes and P239 Billion (18.4%) from non-taxes. Total expenditures stood at P1,239 Billion for a budgetary surplus of around P56 billion.
Energy  & Power Taxes – P138.7 Billion (estimate)
Of the P1,057 Billion of tax revenues, the energy & power industry contributed P138 Billion. The 12% VAT and royalties from indigenous geothermal and natural gas provided the two major sources of predictable cash flow for the government. Without this contribution, the government would have suffered huge budgetary deficit that has to be covered by expensive borrowings from abroad leading to an unthinkable exchange rate regime of P100 per US$.
Since our government has just emerged from the long-term effect of martial law dictatorship that resulted in poor economic performance, only the financial re-engineering of public finance thru the “Oil Deregulation Law” of price and supply and “Electric Power Industry Reform Act or EPIRA” has brought stability and predictability of oil and power pricing as it closely mirrors the international price oil movements, and electric power generation has been removed NAPOCOR whose subsidies constituted almost 50% of the gov’t deficit.
By transferring the unsustainable NAPOCOR debt (financed by gov’t deficit borrowings) to PSALM and liquidated this debt via a universal charge that is paid by all consumers (foreigners and locals alike) of electricity, not just the local taxpayers, the economic burden of re-structuring the Philippine power industry was shared equally by all power users. In essence, the prevented the “Greek Financial Meltdown” of the Philippine gov’t.
However, with the newfound economic strength of the Philippines propelled by the almost $2.0 Billion per month remittance from our OFWs, our country can now invest to improve our deteriorating infrastructure such as roads, bridges, airports, seaports, and the energy and power industry – so that the country can regain its lost competitiveness, generate more local manufacturing jobs for both domestic and export markets, making the Philippine business model the best in the world: OFW remittance, BPO income, local manufacturing for domestic and export market, agricultural production, cultural and arts renaissance, and robust domestic consumption.
Total Revenues of Philippine Government
The gradual imposition of consumption taxes such as the VAT has resulted in improved gov’t tax revenues to replace the soon-to-be-gone customs duties and excise taxes with the onset of the Asian Free Trade Zone by 2015.

Since 2001 to 2008, the government’s fiscal position has improved from a nagging deficit to a budgetary surplus of P56 Billion by 2008. Infrastructure spending has increased tremendously, but unfortunately, it is believed that more than 50% of this infrastructure were of the wrong kind, resulting in massive losses to corrupt NGOs that financed the immoral and dirty lifestyle of the rich and famous politicians and their business friends.
I do believe that removing the “pork barrel” system in our socio-political and economic life will propel the Philippines further. Just imagine, with over 50% losses to corruption, the country managed to grow consistently 6-7% p.a., how much more would it have grown and improved our infrastructure and utilities (water, power, fuels) leading to tremendous leaps in our overall efficiency and competitiveness, and with the best Filipino spirit, no one can beat the Philippines if only we had honest, dedicated, properly educated, capable of scientific planning political, economic and social leaders.
Cash Budget vs. GDP and GNP
1) Total revenue and Expenditure as % of GDP and GNP is around 17%

2) Tax revenue as % of GDP and GNP is around 14%
3) Deficit (2001-2007) provided by borrowings (foreign, domestic) and grants
4) Surplus in 2008 needs to be sustained by strengthening VAT and energy taxes (oil, coal, geothermal, natural gas,  electricity) such as customs duty, specific tax, excise tax and royalties that are steady and predictable
The country’s tax revenue constitute 14% of its GDP, which is eaten up by expenditures at 17% of GDP. The country needs to increase further its tax collection efficiency and I believe we must support the fragile efforts of our BIR Commissioner in this regard. Pay your taxes first before you complain how it is badly spent and lost to corruption. You can’t complain if you yourselves are cheating on your patriotic duty of paying the right taxes in a timely manner.

Historical Phil. Capacity Utilization

Historically, the overall capacity utilization of our power plants stood at a healthy 37-40%. However, it started to grow rapidly to 48% by 2011, of which oil based peaking plants was 13.5% utilized, hydro 30.9%, geothermal 63.6%, coal 58.8%, natural gas 82.2% and new RE 20.0%. Since these are annual averages, there is a range or swing  of around +/-20%; thus, some plants are underutilized at 20-40% as in the case of peaking plants or plants that regularly breaks down, while some plants are stretched to the limit at around 60-80%. In most advanced countries, they maintain a safe reserve with their annual capacity utilization being set at 30%-40%, so that they can grow their economy with new manufacturing activity to provide jobs for inclusive growth, while awaiting the 5-year lead time for new power plants to be completed to bring down the utilization level of 50% to the desired level of 30-40%.
Forecast Luzon Capacity Utilization

The DOE has prepared the PEP 2012-2030 and provided for baseload, midrange and peaking power generation using the least cost expansion planning tools such as WASP provided by the IEA, and now replaced with the newer MESSENGER. By 2020, the Luzon grid will be 50.08% utilized. By 2030, this would rise to 52.92%.

Forecast Visayas Capacity Utilization

On the other hand, the Visayas grid will be utilized at a higher rate of 58.01% by 2020.  By 2030, this would rise to 67.45%.

Forecast Mindanao Capacity Utilization

Likewise, the Mindanao grid will be utilized at 50.15% by 2020. By 2030, this would rise to 52.22%.

Forecast Phil. Capacity Utilization
By 2020, the overall capacity utilization of the Philippines would be 51.15%. By 2030, this would rise to 54.85%.
How to Reduce Energy & Power Costs
•Optimal load dispatch (least cost)
•Least cost capacity expansion planning – “Best New Entrant” technology
•Distributed Generation (DG) – minimize transmission & distribution costs
•Apply “Smart Grid”
•“De-carbonize” the energy economy – from fossil carbon economy to low carbon economy to hydrogen economy and ultimately breeder reactor economy
•Encourage renewable energy use thru feed-in-tariff (FIT) – to bump off expensive diesel/bunker fuel generation
•Lower government taxes on capital equipment & fuels
•Use nuclear energy (BNPP with pumped hydro storage)
•Prepare a comprehensive energy development plan that addresses high GDP growth with sufficient and optimal power supply and efficient transmission & distribution system with smart control and distributed generation and appropriate taxation to be competitive with our Asian neighbors to promote sustainable and environmentally benign inclusive growth
Reducing power costs requires in the short-term optimizing load dispatch, long-term least cost capacity expansion planning, application of new technologies such as Distributed Generation and application of Smart Grid, promoting renewable energy to de-carbonize the energy economy as well as to bump-off expensive peaking diesel/bunker fuel generation, lowering gov’t taxes on capital equipment and fuels and generated electricity, adoption of cheaper nuclear energy and most of all preparing a comprehensive energy development plan that addresses high GDP growth with sufficient and optimal power supply that is delivered by efficient transmission and distribution system with smart control and distributed generation and applying appropriate taxation levels that balances fiscal needs with providing competitive energy and power rates to promote sustainable and inclusive growth in an environmentally benign fashion.


How to Optimize Load Dispatch

  • Obtain power plant information on rated (dependable) plant capacity, minimum stable load, capacity factor, plant heat rate or efficiency, fuel cost, variable O&M and fixed O&M, regulatory and other costs, take-or-pay contractual obligations
  • Obtain market demand (peak load, average load), define renewable energy mix (% RE in demand to be supplied by hydro, geothermal, biomass, wind, solar, ocean thermal)
  • Define objective = minimize LRMC costs (capital, fuel, O&M, other costs)
  • Define constraints:
  • 1) energy balance (gross generation, own use, net sales)
  • 2) meet maximum demand (average, peak)
  • 3) meet minimum renewable energy mix
  • 4) meet maximum dependable capacity dispatch of each plant
  • 5) meet minimum take-or-pay contractual obligations of each plant
  • 6) meet minimum dependable capacity dispatch of each plant
  • 7) transmission line constraints (congestion in grid)
  • 8) other constraints such as ramp-up rate (respond to load changes)

In the short term, we optimize load dispatch on an hourly, daily, weekly, monthly, and annual basis to minimize the total capital, fuel and operating costs (LRMC) or only fuel and operating costs (SRMC). An LP model of the power system is prepared is expressed in LP format (objective function, constraints and variables).

Why Optimize Load Dispatch?
  • Meet load (demand) at any given hour using the most economic combination of power generating plants
  • Optimal dispatch means generation mix has lowest incremental generation cost (capital, fuel, variable O&M, other costs)
  • Lowest incremental generation cost leads to least price offer to the spot market (WESM) and direct consumers
  • Optimal dispatch also indirectly minimizes outflow of foreign exchange for imported generating equipment and fossil fuels, leading further to lower GHG emissions
  • Optimal dispatch leads to lowest supply cost to distribution utilities (DUs) which in turn leads to lowest selling price to end consumers (usually captive accounts)
  • Optimal dispatch is used during actual plant operation; however, “best new entrant” approach is applied during the planning phase of the Philippine Energy Plan wherein new capacity is vetted to the least cost alternative (best entrant).

Optimal dispatch means lowest incremental generation costs leading to minimum foreign exchange outflow for imported fuel and equipment, leading also to lower GHG emissions to mitigate global warming and climate change. For long-term capacity expansion planning, the “best new entrant” technology, capacity and fuel combination is also determined using Linear Programming (LP) techniques.

“Best New Entrant” levelized first year tariff of  Thermal Technologies

Using project finance modeling of a power plant with latest $/kW cost and fuel prices, a sorted list of “best new entrant “levelized tariff (selling price) shows that nuclear power is cheapest relative to other fossil-fired thermal technologies.  Actual estimate by NPC experts place nuclear levelized cost at P2.50-3.50 per kWh depending on the nuclear fuel cycle used. (note: selling price = generation cost + profit, where cost = fuels + O&M + other costs)

Using a unified set of data, the cheapest or “best new entrant” is nuclear PHWR once thru power plant at 3.41 P/kWh, followed by CCGT 5.60, IGCC 6.13, PC 6.29, CFB 6.46, simple cycle GT 6.96, etc.Distributed Generation (DG) – from Wikipedia
  • Distributed generation, also called on-site generation, dispersed generation, embedded generation, decentralized generation, decentralized energy or distributed energy, generates electricity from many small energy sources.
  • Currently, industrial countries generate most of their electricity in large centralized facilities, such as fossil fuel (coal, gas powered) nuclear or hydropower plants. These plants have excellent economies of scale, but usually transmit electricity long distances and can affect the environment.
  • Most plants are built this way due to a number of economic, health & safety, logistical, environmental, geographical and geological factors. For example, coal power plants are built away from cities to prevent their heavy air pollution from affecting the populace. In addition, such plants are often built near collieries to minimize the cost of transporting coal. Hydroelectric plants are by their nature limited to operating at sites with sufficient water flow. Most power plants are often considered to be too far away for their waste heat to be used for heating buildings.

Distributed Generation (DG) is on-site generation, dispersed, embedded or decentralized generation. Power is generated on-site where the fuel is available and transmitted to nearby end-users to minimize distribution & transmission line losses.

Distributed Generation (DG) – from Wikipedia
  • Low pollution is a crucial advantage of combined cycle plants that burn natural gas. The low pollution permits the plants to be near enough to a city to be used for district heating and cooling.
  • Distributed generation is another approach. It reduces the amount of energy lost in transmitting electricity because the electricity is generated very near where it is used, perhaps even in the same building. This also reduces the size and number of power lines that must be constructed.
  • Typical distributed power sources in a Feed-in Tariff (FIT) scheme have low maintenance, low pollution and high efficiencies. In the past, these traits required dedicated operating engineers and large complex plants to reduce pollution. However, modern embedded systems can provide these traits with automated operation and renewables, such as sunlight, wind and geothermal. This reduces the size of power plant that can show a profit.

Apply “Smart Grid” – from Wikipedia

  • A smart grid delivers electricity from suppliers to consumers using two-way digital technology to control appliances at consumers’ homes to save energy, reduce cost and increase reliability and transparency. It overlays the electricity distribution grid with an information and net metering system.
  • Such a modernized electricity network is being promoted by many governments as a way of addressing energy independence, global warming and emergency resilience issues. Smart meters may be part of a smart grid, but alone do not constitute a smart grid.
  • A smart grid includes an intelligent monitoring system that keeps track of all electricity flowing in the system. It also incorporates the use of superconductive transmission lines for less power loss, as well as the capability of integrating renewable electricity such as solar and wind. When power is least expensive the user can allow the smart grid to turn on selected home appliances such as washing machines or factory processes that can run at arbitrary hours. At peak times it could turn off selected appliances to reduce demand.

“De-Carbonizing” the Economy

The above formula shows the procedure for calculating the kg CO2 per kWh (or MT CO2 per MWh) of gross generation. To reduce the CO2 emission of a particular technology, the plant heat rate must be lower (higher thermal efficiency) and the fuel has a lower carbon content (C) and has more hydrogen (H2).

What is “De-Carbonization” of power industry about?
  • The electric power industry can achieve deep reductions in greenhouse gas emissions by 2050 by building new nuclear plants, sequestering coal-plant emissions, boosting wind energy and improving efficiency, the industry’s top research group said yesterday.
  • The Electric Power Research Institute‘s report on de-carbonizing electricity generation said an “aggressive” push on new technologies could lower 2005-level carbon dioxide emissions from power plants by 41 percent in 2030.
  • EPRI’s conclusions about energy technology gains were fed into a second computer model to assess the costs of stripping 80 percent of 1990-level carbon emissions out of the electricity sector by 2050, approximating the goal of the House-passed climate bill.
  • With what EPRI calls a “full” portfolio of technology options, including new nuclear, expanded wind power and carbon capture, the price of electricity in current dollars would climb by 80 percent in 2050. With a “limited” range of generation options, excluding carbon capture and new nuclear, the price soars 210 percent higher than now, EPRI reported.

The power industry can be de-carbonized by building new nuclear power plants, sequestering  coal-plant CO2  emissions (CCS), boosting wind energy and improving efficiency. This may entail additional costs, however, as reported by EPRI.

 De-carbonizing the power industry also requires the capture and sequestration of carbon emissions from coal plants and utilization of nuclear power and biomass power technologies.

What is “De-Carbonization” of power industry about?
  • “Our analysis clearly shows the imperative for the electricity sector to move aggressively to deploy a full portfolio of technologies that will lead to low-carbon energy future while limiting costs to the nation’s economy,” EPRI president Steve Specker said in presenting the findings yesterday to a meeting of industry executives and regulators in Westlake Village, Calif.
  • Based on its research, EPRI concludes that capture and sequestration of carbon emissions from coal plants would be technically feasible by 2020, and it assumes that new regulations would be in place to support that strategy. It also assumes that 45 new nuclear power plants could be built by 2030, using existing reactor sites, adding 64 gigawatts of new capacity.
  • “Each of these assumptions is based on the question, can we do that, from a science and engineering standpoint?” said the report’s co-author, Revis James, director of EPRI’s Energy Technology Assessment Center. “It might be expensive. It might be fraught with policy challenges, but is it feasible to do it technically? The spirit of this, to be candid, is to suspend reality for a moment with respect to the policy challenge and the financial challenge and first just assess the technical potential. Then you can overlay the financial and policy concerns on top of that.”

Feed-in-Tariff (FIT and FIT ALL)

The DOE would allocate the installation targets for hydro, wind, solar and biomass power on a first-to-build basis. The approved  installation targets: 250 megawatts for hydro, 250 MW for biomass, 200 MW for wind, 50 MW for solar and 10 MW for ocean technology.

If a developer becomes eligible for the installation target, it can avail of the feed-in tariff rates as follows:

• Hydro     = 250 mw = 5.90 PhP/kWh
•Biomass = 250 mw = 6.63 PhP/kWh
•Wind       = 200 mw = 8.53 PhP/kWh
•Solar       = 50 mw   = 9.68 PhP/kWh
•Ocean     = 10 mw   = none yet
The FIT ALL of around 0.04 PhP/kWh will be added to the electricity bill to be collected by NGCP/TRANSCO and then paid to the RE developers at the FIT rate.
Since intermittent renewable energy (RE) sources are more expensive than the average grid rate (from oil, coal, gas, geothermal, hydro, nuclear), the use of RE would require some form of subsidy in the form of feed-in-tariff for each technology. An installation target or MW cap is also provided to limit the generation of power from RE in order to put a cap on the level of subsidy (around 0.04 P/kWh of FIT ALL). The FIT ALL is like a universal charge collected by TRANSCO/NGCP from all ECs, DUs, and end-consumers. It is estimated by ERC at the beginning of the year by summing up the product of RE capacity x CF x FIT for all technologies, and dividing by the expected annual generation. It is adjusted on the next year if the NGCP collections does not match the NGCP payments to the RE developers.Oil Price Formula – absolute pump price



VAT1 = SUB1 x 12%

DPLC, $/bbl = SUB1 + VAT1

DPLC, P/L = (DPLC, $/bbl) x (48 P/$) / (158.9868 L/bbl)


VAT2 = SUB2 x 12%



 NOTE: Exchange rate = 48.00 P/$

                42 gallons/bbl x 3.7854 liters/gallon = 158.9868

The above simplified oil price formula calculates the absolute pump price given the source (FOB) cost and adding ocean freight & insurance, local logistical costs such as wharfage, BOE fee, ocean loss allowance, doc stamps, actual demurrage charges, customs duty and specific tax (excise tax). A 12% VAT is applied on all this fuel importing activities. Then the duty paid landed cost (DPLC) is calculated using the exchange rate (e.g. 48 P/$) and conversion factor (around 159 L/bbl). The local value adding activities such as oil company gross margin (OCGM), biofuels (10% ethanol, 2% CME biodiesel), depot operation, dealer’s margin, haulers fee, transshipment (barge, tanker, tank trucks) is added and another 12% VAT is applied on the local value adding activities to arrive at the local costs. The final (absolute) pump price is then the sum of the DPLC and local costs.

Oil Price Formula – incremental price adjustment between period 2 and period 1

ADJ = Change in DPLC + Change in LOCAL COSTS

ADJ = { [ FOB(2) x FOREX(2) – FOB(1) x FOREX(1) + (FOREX(2) – FOREX(1)) x FRT ] x (1 + 0.05%) x (1+ 0.10% + 0.50% + 0.15% + 3.00%) + ((FOREX(2) – FOREX(1)) x WHARFAGE } 1.12 / 158.9868 x (1 + % OIL COMPANY MARGIN x 1.12)

If the purpose is just to estimate the incremental price adjustments, then it is just the change in DPLC and LOCAL costs, adjusted for the % oil company gross margin and the 12% VAT.

How to Calculate Oil Pump Price

The table shown is a step-by-step application of the many formulas to arrive at the final pump price.

Imported Coal & Local Coal Parity Pricing

Local coal is priced using a coal parity pricing formula that recognizes the heating value of the two coal supplies and providing a 2% discount on a heating value basis on local coal to provide an economic incentive to use local coal to compensate for the difficulties in utilizing local coal compared to imported coal.

For instance, imported coal from Indonesia is delivered to the Philippines at a cost that includes provisions for ocean freight & insurance, then converted to Peso dutiable value, then applying customs duty, bank charges, brokerage fee, arrastre charges/stevedoring, wharfage, doc stamps, import processing fee, excise tax, and VAT.

Import parity price computation is applied to value local coal production using last 3 quarters importation of coal by NPC. This means that local coal prices tracks the imported price of coal based on heating value and providing a 2% discount as incentive to utilize local coal.

Natural Gas Price Determinants

Domestic natural gas price is linked or indexed to imported crude oil, fuel oil and gas oil (diesel). The pricing formula for the Sta. Rita and Ilijan power plants are shown in the next 2 slides.

Sta Rita & San Lorenzo Price Adjustment Formula
Pn =  [ Po   x   [ a (US CPIn / US CPIo) + b (FOn / FOo) + c (GOn / GOo) + d (DCOn / DCOo) + e (OCOn / OCOo)         

           + 0.17 ]] x (NCVn/GCVn) x (GCVo/NCVo)

This is the Sta. Rita San Lorenzo Price Adjustment Formula. Basically, this formula indicates that the Prevailing price (Pn) of natural gas is computed by multiplying the base price of natural gas (Po) with the different indicators like the US CPI, price of Dubai crude oil (DCO), price of Oman Crude Oil (OCO) etc.

NPC-Ilijan Price Adjustment Formula (Ilijan Power Plant)

The NPC Ilijan Price adjustment formula is similar with that of Sta. Rita & San Lorenzo with only a slight difference. NPC’s formula does not have the GCV/NCV ratio component and they also differ in the assignment of weights to the different escalators.

Malampaya Gas Price Schedule

This matrix tabulates the price formula components like the base price, the different indicators and escalators with their corresponding weights. The computation of the prevailing price (Pn) was done using excel. (By clicking the underlined words Price Schedule,  the excel worksheet can be accessed.)


This provides us with information on the contracted volumes of natural gas by the different buyers.

Conventional & Fossil Power
  • Nuclear energy (uranium, plutonium) – e.g. PHWR
  • Large Hydro, pumped storage (Caliraya with BNPP)
  • Geothermal (dual flash, binary fluid)
  • Spark Ignition Engine (Gasoline)
  • Compression Ignition Engine (Diesel, Fuel Oil/Bunker)
  • Oil Thermal (Fuel Oil/Bunker)
  • Gas Thermal (Natural gas, syngas from gasification)
  • Coal Thermal (PC, CFB)
  • Simple Cycle  Gas Turbine (gas oil/diesel, kerosene)
  • Combined Cycle Gas Turbine (natgas, gas oil/diesel)
  • Integrated Gasification Combined Cycle (IGCC)
  • Fuel Cells (power and water)

The above list shows the nuclear, conventional and fossil power generation technologies.

Renewable Energy Sources
  • Biomass direct combustion (furnace, boiler, turbine, electric generator) – condensing turbine
  • Biomass cogeneration (electricity & process heat; and with space cooling or refrigeration – trigeneration) – back pressure turbine
  • Biomass gasification (pyrolysis) – SI engine (duel fueling with gasoline), CI engine (dual fueling with diesel), or boiler to produce steam and power
  • Biomass integrated gasification combined cycle (BIGCC)
  • Biomass waste-to-energy (WTE) – MSW, LFG, biogas
  • Mini-Hydro (small-hydro, micro-hydro) run-of-river
  • Solar (thermal – CSP, photovoltaic – solar PV panels)
  • Wind turbine generator, micro-turbine
  • Ocean thermal energy conversion (OTEC)
  • Ocean wave, tidal power

Renewable Energy (RE) sources includes biomass, mini-hydro or run-of-river, solar thermal and photovoltaic, wind, ocean thermal, ocean wave and tidal power technologies.

Energy Storage Technologies


       •Compressed air storage

       •Flywheel storage

       •USB – lead acid storage

       •USB – advanced storage

       •SMES storage

       •Ultracapacitors storage

Energy storage technologies store cheap or excess energy and power generated during off-peak hours and releasing them during peak hours or when needed. This will reduce the need for too much peaking power plant capacity. The Caliraya pumped-hydro storage is an example of an optimized system designed in tandem with the BNPP.

Levelized Cost of Energy (US NREL)

LCOE = ICC * CRF / AEPnet + (LLC + O&M + LRC + MOE) – PTC,  $/kWh                   


LCOE = Levelized Cost of Energy, $/kWh

ICC = Initial Capital Cost (total debt), $                                                          

CRF = capital recovery factor, 1/yr = int / (1 – (1 + int)^-Life)                                                 

AEPnet, kWh/yr = (kW capacity) * (capacity factor) * (hours/year)                                                     

LLC = Land Lease Cost, $/kWh                                                         

O&M = Levelized Operating & Maintenance Expense, $/kWh                         

LRC = Levelized Replacement/Overhaul Cost, $/kWh                                                 

MOE = Miscellaneous Operating Expense, $/kWh                                                       

PTC = US Production Tax Credit, $/kWh                                                       

Levelized cost of energy (LCOE) calculates the net present value of all capital and operating expenditures and dividing it by the net present value of the quantity of generated electricity. This allows comparison of various power generation technologies of unequal life-times. 

RP Formula by MTO (grossed up)

LCOE = Total Cost / ((1 – g) * (1 – t)), in US $/kWh or US cents/kWh                                               


Total Cost = ( ICC * CRF + (FixO&M + VarO&M + DOE + Fuel) * (1 – t) – t * DEPN ) / AEPnet                              

ICC = (Capacity, kW) * (Overnight Cost, $/kW)                                

CRF = capital recovery factor, 1/yr = int / (1 – (1 + int)^-Life)                         

AEPnet = kWh/yr = (kW capacity) * (capacity factor) * (hours/year)                           

FixO&M = (Fixed O&M, $/kW/yr) * (Capacity, kW)                         

VarO&M = (Variable O&M, $/kWh) * AEPnet                                  

DOE = (PhP 0.10 / kWh) / (Exchange Rate, PhP / US $) * AEPnet                             

Fuel = (net Heat Rate, LHV) * AEPnet * (Price of fuel, LHV)

        = (3600 / Efficiency, kJ/kWh net) * AEPnet * (Price, $/kJ net)                            

DEPN = Depreciation, $ / yr = ICC / Life                                

g = Franchise Tax + Business Tax = 2.5% + 0.005% = 2.005%                                  

t = Income Tax = 32%                        

int = Interest Rate, % p.a.                                

Life = Economic Life or Project Life, yrs                                  

The Philippine (RP) power price formula developed by MTO (Marcial T. Ocampo) is a grossed-up version of the US NREL cost formula to consider the impact of depreciation and taxation. It is the price that allows the RE developer to recover the cost of capital, fuel, fixed and variable O&M costs, taxes and profit.

Low Carbon Economy
  • Extensive use of Renewable Energy (RE)
  • Include or expand nuclear power generation
  • Adoption of CO2 capture or sequestration technologies
  • End result is lower CO2 emissions
  • Secure energy and power supplies
  • But energy and power costs may rise
  • Citizenry willing to pay for higher costs in exchange for an environment that mitigates global warming and avoids severe climatic changes
  • Impact can only be predicted by sophisticated mathematical models available only from the advanced countries
  • A technical working group (TWG) of energy and environmental experts may be needed to produce a similar but simplified model for the country

From the current high-carbon economy (BAU), the world’s migration to a low carbon economy has began – extensive use of RE, a revisit of the nuclear option is happening word-wide, CO2 capture and sequestration technologies are being developed for coal-fired generation and the impact is now being predicted by sophisticated mathematical models.

Carbon Capture Sequestration (CCS)

The table from US EIA estimates the 2018 cost of advanced carbon capture sequestration (CCS) applied to coal-fired power generation. The total levelized cost of CCS technologies are compared with conventional CCGT, advanced coal, simple cycle GT, advanced nuclear, geothermal, biomass, wind, solar PV, solar thermal and hydro.

New Energy Plan Considerations
  • Smart Grid
  • Distributed Generation
  • De-Carbonizing the economy
  • Renewable Energy Feed-in Tariff (FIT)
  • Scenario Building – determine impact of energy plan on supply risk, price and GHG emission potential

       Case A – Business as Usual

       Case B – Aggressive RE with FIT

       Case C – Nuclear Energy Option

       Case D – RE with FIT plus Nuclear

  • Low Carbon Economy (leading to a Hydrogen Economy in the future, ultimately the “nuclear breeder” economy)

The “New Energy Plan” for the Philippines must include – Smart Grid, Distributed Generation, promote a low carbon economy, promote RE with FIT and FIT ALL, analyze 4 cases or 4 development paths: business as usual, aggressive RE with FIT, nuclear energy option and RE with FIT plus nuclear.

2008 CO2 Emission without Nuclear (Base Case A – Business As Usual)

The Business as Usual case will result in a power sector contribution of 0.392 kg CO2 per kWh for the 62,608 GWh gross generation in 2008.

Total GHG emission for the Philippine power generation sector would be 24.5 million mt CO2.

The Case A scenario (business as usual will result in a power sector contribution of 0.392 kg CO2 per kWh for a total of 24.5 million MT of CO2 for the 62,608 GWh of gross generation in 2008.

2008 Cost without Nuclear (Base Case A – Business As Usual)

Using the 2008 generation mix, the business as usual case would have a weighted average levelized selling price (using the US NREL and RP MTO formula) of 0.0720 $/kWh or 3.4119 PhP/kWh.

This would result in a weighted average levelized selling price of 0.072 $/kWh or 3.41 P/kWh.

2008 CO2 Emission with RE (Case B – Renewable Energy with FIT)

An aggressive RE development program (to be verified with NREB) enjoying feed-in tariff (FIT) support will provide additional 2,344 GWh generation, up 3.84% share from base case share of 0.10%. A 5.01% reduction in emission intensity to 0.373 mt CO2/MWh is expected with a higher FIT average of 10.54 PhP/kWh.

RE with FIT scenario B will lower by 5.01% the CO2 emission intensity to 0.373 MT CO2 per MWh. Given the capacity cap of 445.75 MW for RE and assumed capacity factor, the average FIT for all technologies would be 10.54 P/kWh only compared to the expensive diesel/bunker fuel generation of over 19-23 P/kWh.


2008 Cost with RE (Case B – Renewable Energy with FIT)

While the aggressive RE development will result in favorable reduction in GHG emission, it would unfortunately result in higher electricity tariff thru the feed-in tariff (FIT) estimated at 10.54 PhP/kWh based on the hypothetical RE development plan (actual plant being prepared by NREB and DOE with the FIT to be approved by ERC).  The price impact is a 3.44% increase in generation cost. (note: generation cost has to be grossed up with depreciation and income tax to arrive at levelized selling price which the customer sees in his electricity bill.)

Thus with FIT, the RE generation if the full cap is utilized will result in a 3.44% increase in generation cost.

2008 CO2 Emission with Nuclear (Case C – Nuclear Option)

Had the 620mw BNPP been operated, it would have replaced expensive diesel and other sources proportionately, leading to a lower GHG intensity of 0.363 mt CO2 per kWh gross generation for a 7.55% reduction from business as usual case of 0.392 mt CO2 per MWh. Total GHG emissions would have been reduced to 22.7 million mt CO2 from base case of 24.5 million mt CO2.

With the nuclear option on the table, a 7.55% reduction in CO2 emission intensity is expected to be lowered to 0.363 MT CO2 per MWh for a total of 22.7 million MT CO2 from the base case of 24.5 million MT CO2.

2008 Cost with Nuclear (Case C – Nuclear Option)

Had the 620mw BNPP been operated, the weighted average levelized generation cost would have been 8.38% cheaper today at 0.0660 $/kWh or 3.1261 PhP/kWh.

If the 620 MW BNPP was operated in tandem with the Caliraya pumped-storage hydro, the country’s average levelized generation cost would have been 8.38% cheaper at 3.12 P/kWh from the 3.41 P/kWh base case.

2008 CO2 Emission with RE & Nuclear (Case D – RE FIT and Nuclear Option)

Combining both aggressive RE development supported with FIT incentives and keeping the Nuclear Option open will lead to a dramatic 15.61% reduction in GHG intensity to 0.331 mt CO2 per kWh gross generation.  This leads to a much lower GHG emission of 20.7 million mt CO2 compared to baseline emission of 24.5 million mt CO2.  The brunt of the reduction is absorbed by the coal-fired power plants which will drop to 24.50% of gross generation from previous level of 28.24%.  Oil fired plants is now marginal and purely for peaking purposes.

CO2 emission intensity would have been reduced by 15.61% from 0.392 to 0.331 MT CO2 per MWh for a total of 20.7 million MT CO2 compared to the baseline emission of 24.5 million MT CO2.
2008 Cost with RE & Nuclear (Case D – RE FIT and Nuclear Option)

Combining the Nuclear case to the aggressive Renewable Energy case supported by feed-in tariff will mitigate the increase in tariff arising from the expensive RE FIT (10.54 PhP/kWh), leading to a small decrease of 0.05%, negating the reduction due to the nuclear option.

Combining the RE with FIT and Nuclear Option would likewise reduce the weighted average levelized cost by 0.05% or simply maintains cost while achieving a lower carbon economy for the Philippines.

Power Generation Technologies

Using published data by Paul Breeze, the table shows the technology information (capacity, overnight cost, capacity factor, fixed and variable O&M, economic life, efficiency and fuel price) and the calculated levelized cost of energy using the US NREL and RP MTO formulas.

Sorted Power Generation Technologies

Sorting from the cheapest to the most expensive, the table shows CHAT 300 MW to be the cheapest at 0.0312 P/kWh and the most expensive to be ultracapacitors storage at 37.28 $/kWh.

Project Finance Models

  • The simplified LCOE formulas (by US NREL or by RP MTO) are approximations.
  • Basically, the LCOE calculates the equivalent annual cost of the capital invested at the cost of capital (WACC as discounting factor) and adds it to the annual fuel & lube costs, fixed and variable O&M, and other costs.
  • To improve accuracy and the impact of other technical, economic and financial parameters (e.g. construction lead time, economic life, installed capacity, efficiency or heat rate, capacity & heat rate degradation, net capacity factor (after own use & loses), fuel & lubes, capital cost ($/kW), fixed and variable O&M, overhaul costs, and other costs – a project finance model at 30% equity and 70% debt is prepared to show electric generation, revenues, expenses, loan interest and principal repayment, cash flow, working capital, balance sheet, levelized cost breakdown of tariff, levelized cost based on asset and cost recovery, and financial ratios such as DSCR.

Project finance modeling allows the calculation of the IRR or the first year tariff for a particular power generation technology and installed capacity. It can also be used to more accurately calculate the LCOE from the streams of cash flows for recovery of capital, fuel, fixed and variable O&M costs. The following tables shows the financial models for biomass, hydro, wind and solar PV power generation.

Comparative LCOE of Conventional, Fossil, Nuclear and RE Technologies

Using the same NREB template from biomass power generation, I constructed an improved version that included land costs, levelized cost breakdown of revenues, generation costs and net profit. The LCOE will be used by the DOE in their WASP/MESSENGER least cost expansion LP runs to identify the peaking, mid-merit and baseload power plant requirements during the planning horizon of 2012-2030.

How the must-run and cheaper RE with FIT can displace expensive diesel/bunker power

Mr. Roger Buendia, formerly with PNOC-RE, has prepared a position paper that recommended the use of 100-200 MW of RE to bump-off expensive peaking diesel/bunker fuel generation. Likewise, the provision of mid-merit natural gas open cycle GT (2 x 100 MW AVION units of First Gen) will address the lack of cheaper mid-merit to peaking units to replace baseload coal when they go off-line. 

Power Demand Profile (best)

Best profile – grid dependable capacity is over the demand curve.

Power Demand Profile (worst)

Worst profile – grid dependable capacity is almost as large as the peak demand.

Power Demand Profile (realistic)

The realistic profile shows the peak demand curve between the best case and worst case scenario profile.

Power Supply Demand Outlook

  • The Philippine Energy Plan (PEP 2012-2030), Power Development Plan (PDP 2012-2030), Distribution Development Plan (DDP 2012-2020), NEA Chronicles (ECs, DUs, PIOUs, and LGUOUs), and the TRANSCO & NGCP Transmission Development Plan (TDP) provides historical and forecast power demand (MW) and energy demand (MWh) under a number of scenarios.
  • Power Demand is related to the GDP level (as intensity) and to GDP growth (as elasticity)
  • intensity = (Power quantity) / (GDP value)
  • elasticity = (Power growth rate) / (GDP growth rate)
  • Forecast Power growth = GDP growth rate x elasticity

The Philippine gov’t agencies such as DOE, ERC, NEA, TRANSCO, NGCP, NPC and PSALM, together with the ECs, DUs, PIOUs and LGUOUs, prepare annual energy, power and transmission development plans for inclusion into the Philippine Energy Plan (PEP).

Luzon Demand Forecast from GDP

The Luzon demand forecast assumes an elasticity ratio of 0.6 applied to the GDP growth rate to arrive at the power growth rate.

Visayas Demand Forecast from GDP

The Visayas demand forecast assumes an elasticity ratio of 0.6 applied to the GDP growth rate to arrive at the power growth rate. (revised later to 1.0)

Mindanao Demand Forecast from GDP

The Mindanao demand forecast assumes an elasticity ratio of 0.7 applied to the GDP growth rate to arrive at the power growth rate. (revised later to 1.0, 1.6 and 1.o)

Luzon Power Demand Growth Rates

Visayas Power Demand Growth Rate

Mindanao Power Demand Growth Rate

Power Development Plan for Luzon

The PDP for Luzon is constructed by applying the following formulas: EGR = GDPGR * elasticity

ES = ES * (1 + EGR)
GG = ES / (1 – SU/TL)
PD = GG / (8760 x LF)
SU/TL = System Use/Transmission Loss = 10.4%
LF = load factor = 73%           
Power Development Plan for Visayas

The PDP for Visayas is constructed by applying the following formulas: EGR = GDPGR * elasticity

ES = ES * (1 + EGR)
GG = ES / (1 – SU/TL)
PD = GG / (8760 x LF)
SU/TL = System Use/Transmission Loss = 7.13%
LF = load factor = 68%

Power Development Plan for Mindanao

The PDP for Mindanao is constructed by applying the following formulas: EGR = GDPGR * elasticity

ES = ES * (1 + EGR)
GG = ES / (1 – SU/TL)
PD = GG / (8760 x LF)
SU/TL = System Use/Transmission Loss = 9.56%
LF = load factor = 72%

Power Reserves & Contingencies

Luzon Grid:
•LFFR = 4 % of Peak Demand
•Spinning = Largest single unit (647 MW)
•Back-up = Largest single unit (647 MW)
Visayas Grid:
•LFFR = 4 % of Peak Demand
•Spinning = Largest single unit (100 MW)
•Back-up = Largest single unit (100 MW)
Mindanao Grid:
•LFFR = 4 % of Peak Demand
•Spinning = Largest single unit (105 MW)
•Back-up = Largest single unit (105 MW)
With the peak demand, we then add the power reserves and contingencies as shown in the table for Luzon, Visayas and Mindanao. The load following frequency regulation (LFFR) is 40% of peak demand. We then add the reserves which is equivalent to the largest single unit for spinning and backup reserves.
The resulting calculations for Luzon, Visayas and Mindanao are shown in the next 3 slides.

Modeling Scenarios

• DOE Outlook – no retirement, 100% of dependable capacity:
• MTO Outlook – with retirement (estimated from commissioning year + economic life)
• Power Demand Growth Rate = GDP Growth Rate x Elasticity:
•     Luzon = 4.67%, Visayas = 7.79%, Mindanao = 8.76%
• High Case = at 100% dependable capacity
• Low Case = extreme weather (El Nino):
•    Coal 80%, Diesel 70%, Gas Turbine 50%
•    Oil Thermal 50%, Geo 60%
•    Large Hydro = 40%, Mindanao Hydro = 20%
•    Small Hydro = 30%
•    Biomass, Solar, Wind = 40%
•    Medium Case = Average of High & Low = (High + Low)/2

With the above formulas, we can now proceed to the modeling scenarios: DOE outlook – no retirement and MTO outlook – with retirement. The growth rates for each grid is likewise estimated from the GDP growth rates and elasticity: Luzon 4.67%, Visayas 7.79% and Mindanao 8.76%. Then 3 sub-cases (high, low and medium) were developed  to simulate weather conditions: high case, low case (extreme weather – El Nino) and medium case (average of high and low cases).

GDP & Power Demand Growth Rate Assumptions by Grid by Year
(revised growth rates)

The assumptions by grid by year are shown in the Tables.

DOE Outlook – No Retirement
•Future supply is = existing + committed + capacity additions (from least cost expansion LP model runs)
•Capacity additions identify capacity, technology and timing of investment by private sector (indicative projects) – DOE LP runs using WASP / MESSENGER
•Plant beyond economic life (not retired) will pose a problem with respect to reliability, availability, load factor and capacity factor – DOE retains them in the LP runs (fixed constraint to run, not subject to economic challenge by the newer & more efficient power plants)
•It is present in the grid but is not reliable in providing capacity – must be replaced by a newer and more efficiency power plant or technology (must not be fixed when running least cost capacity expansion planning)
•Such old plants are good as backup for the other base load plants rather than using peaking diesel

Luzon Grid – DOE PDP (High, Low, Medium) – new

•High – at 100% of dependable capacity
•Low – 30% – 50% lower due to El Nino or extreme summer condition that lowers load factor or capacity of power plants due to higher temperature sink
•Medium – average of high and low cases
•Growth rate – new 4.67% p.a.

Visayas Grid – DOE PDP (High, Low, Medium) – new

•High – at 100% of dependable capacity
•Low – 30% – 50% lower due to El Nino or extreme summer condition that lowers load factor or capacity of power plants due to higher temperature sink
•Medium – average of high and low cases
•Growth rate – new 7.79% p.a.

Visayas Grid – DOE PDP (High, Low, Medium) – old

•High – at 100% of dependable capacity
•Low – 30% – 50% lower due to El Nino or extreme summer condition that lowers load factor or capacity of power plants due to higher temperature sink
•Medium – average of high and low cases
•Growth rate – previous (old) 4.55% p.a.

Mindanao Grid – DOE PDP (High, Low, Medium) – new

•High – at 100% of dependable capacity
•Low – 30% – 50% lower due to El Nino or extreme summer condition that lowers load factor or capacity of power plants due to higher temperature sink
•Medium – average of high and low cases
•Growth rate – new 8.76% p.a.

MTO Outlook – with Retirement

•Plant beyond economic life is retired so as not to pose a problem with respect to reliability, availability, load factor and capacity factor
•It is present in the grid but is not relied upon to provide base load capacity
•Good as backup only for the other base load plants rather than using expensive peaking diesel units
•During extreme weather (e.g.. El Nino), hydro power output declines significantly, and thermal power plant output and efficiency drops due to higher temperature sink of condensers.

Luzon Grid – with retirement (High, Low, Medium) – new

•High – at 100% of dependable capacity
•Low – 30% – 50% lower due to El Nino or extreme summer condition that lowers load factor or capacity of power plants due to higher temperature sink
•Medium – average of high and low cases
•Growth rate – new 4.67% p.a.

Visayas Grid – with retirement (High, Low, Medium) – new 

•High – at 100% of dependable capacity
•Low – 30% – 50% lower due to El Nino or extreme summer condition that lowers load factor or capacity of power plants due to higher temperature sink
•Medium – average of high and low cases
•Growth rate – new 7.79% p.a.

Visayas Grid – with retirement (High, Low, Medium) – old

•High – at 100% of dependable capacity
•Low – 30% – 50% lower due to El Nino or extreme summer condition that lowers load factor or capacity of power plants due to higher temperature sink
•Medium – average of high and low cases
•Growth rate – previous (old) 4.55% p.a.

Mindanao Grid – with retirement (High, Low, Medium)

•High – at 100% of dependable capacity
•Low – 30% – 50% lower due to El Nino or extreme summer condition that lowers load factor or capacity of power plants due to higher temperature sink
•Medium – average of high and low cases
•Growth rate – new 8.76% p.a.

Thank You

 Prepared by:

 Marcial T. Ocampo

 B.S.Ch.E, M.S.Ch.E. (Univ. of the Philippines)

 M.S. Combustion & Energy (Univ. of Leeds, UK)

 Energy & Business Development Consultant

 Energy & Power  Feasibility Studies

 Energy & Power Supply-Demand Forecasting

 Former Executive Director, PCIERD-DOST



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