Embed Size (px)
Citation preview
1
RATE ANALYSIS OF THE FIT-ALLOWANCE IMPLEMENTATION
IN THE PHILIPPINES
Sahcel C. Estoperes
12F Meralco, Pasig City, Metro Manila, Philippines
Trixia Anne A. Tañedo
12F Meralco, Pasig City, Metro Manila, Philippines
ABSTRACT
The Renewable Energy (RE) Act of 2008 mandated several mechanisms to promote renewable sources of energy
in the Philippines.
One of the non-fiscal incentives stated in this Act is the Feed-in Tariff (FIT) scheme. The FIT scheme aims to
incentivize RE developers to put up RE plants by giving them a guaranteed fixed revenue rate for every kiloWatt-
hour (kWh) of energy they produce for the next 20 years. The guaranteed FIT rate is a premium rate which is
higher than the prevailing market price. To support the program, a FIT-Allowance (FIT-All), a uniform charge
in peso per kWh (PhP/kWh) is collected from all end-users.
In February 2015, the Distribution Utilities (DUs), as the collection agents for the FIT-All, started collecting FIT-
All from all end-users. At the same time, the RE projects eligible for the availment of the FIT incentives also
started receiving their FIT revenues. Since then, more and more RE developers have applied for FIT eligibility
and were approved by the Philippine Department of Energy (DOE). The DOE also increased installation targets
for wind- and solar PV-based facilities to accommodate the increasing number of FIT applicants.
The objective of this paper is to analyze the impact of policy changeson the FIT-All rate paid by the customers.
Considerations were given on the increase in RE installation targets, consequently inflating the energy volume
that would receive guaranteed revenue under the FIT scheme; and, the merit order effect which allegedly presses
down on the electricity spot market prices.
KEYWORDS: Renewable Energy, Feed-In-Tariff, Feed-In-Tariff Allowance, Rates
Renewable Energy Law
(RA 9513)
Fiscal Incentives
Non-Fiscal Incentives
Net-Metering
FIT Scheme
Renewable Portfolio Std
Green Energy Option
2
Introduction
Power supply mix of the Philippines
Unlike its neighbor countries in Southeast Asia, the Philippines is not endowed of fossil fuel resources. The
Philippine power industry relies heavily on imported coal and oil as fuel for electricity generation. This is one of
the major reasons why the country has one of the highest electricity rates in Asia. To lessen the country’s
dependency on fossil fuels and promote environmental sustainability, the Renewable Energy Act was passed in
2008 that aims to promote renewable sources of energy in the country by providing fiscal and non-fiscal incentives
to the RE developers and consumers.
In 2011, the Department of Energy promulgated the National Renewable Energy Targets drafted by the National
Renewable Energy Board (NREB). The set targets serves as a roadmap in facilitating the penetration of renewable
energy in the power supply mix of the Philippines. In 2015, the Department of Energy issued Department Circular
2015-07-0014 entitled, “Guidelines for the Policy of Maintaining the Share of RE in the Country”, that states that
renewable energy sources should have at least 30% share in the country’s power supply mix. In the 2014
Philippine power statistics, renewable energy sources produced 25.64% of the total electric power generation,
which came from 32.87% of the total installed capacity.1
Electricity rate in the Philippines
Philippine power prices have been considered high when compared to prices in such neighboring countries as
Indonesia, Malaysia, and Thailand. In part, this is because Philippine power prices are “cost-reflective”, while
those in other countries are subsidized, such that retail prices are below the actual cost of providing electric service.
Still, the relatively higher prices in the Philippines has affected the affordability of electricity for households and
the competitiveness of Philippine businesses in the global market.
In a study conducted by International Energy Consultants (IEC) in 2012, the Philippines (as represented by its
largest distribution utility, Manila Electric Co.) had the 2nd highest electricity rates in the region and the 9th
highest out of 44 international markets.2
Some of the conclusions reached on why consumer electricity rates in the Philippines are relatively high for the
region and internationally are the following:
The government doesn't subsidize energy.This policy is highly beneficial in the long-run because it
removes most subsidies (which distort supply and demand dynamics) and sends the consumer important
3
price signals. It also allows sustainable funding for new investment and increases security of supply in the
long term.
The high dependence and cost of imported fuel. Coal and oil are both indexed to world prices and are
not subsidized. Unfortunately, the Philippines is not blessed with an abundance of low-cost natural energy
resources.
The country’s geography. As mentioned in the note in the graph above, the markets with highest
electricity costs are island nations/states. The geography, as well as other non-technical factors contributes
to the high cost of transmission and distribution.
While the reasons for the relatively costly price of electricity is not part of this paper’s scope, the hypothesized
significant upward push on power rates due to the policy changes on the FIT scheme is the motivation of this
study.It is deemed that as the number of capacity under the FIT scheme increases, the amount of payments due
to the qualified RE developers also increases. The current FIT scheme collects the FIT payments from customers
as a PhP/kWh tariff.
The Feed-in Tariff (FIT) scheme under the Renewable Energy (RE) Act
To promote renewable energy (RE), the RE Act mandated several policy mechanisms.One of these is the FIT
scheme to accelerate RE adoption in the country. The FIT scheme guarantees eligible RE developers a fixed
revenue per kWh (FIT rate) for 20 years, instead of having to compete in regular spot and contract markets against
other generation sources (such as conventional power plants and even RE projects that were already considered
commercially viable, e.g., geothermal and large hydro plants). The payment of the FIT rate to RE developers is
fully funded by all end-users, through the collection of generation charges and FIT-All rate in their electricity
bills.
The FIT-All became a separate uniform charge that is calculated annually. The main components of FIT-All are
shown in the formula below:
𝐹𝐼𝑇 − 𝐴𝑙𝑙 =𝐹𝐷 + 𝑊𝐶𝐴 + 𝐴𝐴 + 𝐷𝐴
𝐹𝑁𝑆
Where:
FIT-All is the Feed In Tariff Allowance to be implemented in Year t+1 in PhP/kWh,
FD is the estimated Total FIT Differential required for Year t+1 in PhP,
WCA is the estimated Working Capital Allowance required for Year t+1 in PhP,
AA is the Administration Allowance to be implemented in Year t+1 in PhP,
DA is the Disbursement Allowance to be implemented in Year t+1 in PhP,
FNSis the Forecast National Sales, in kWh, to be applied for Year t+1 in PhP,
And, t is the year the petition for setting the FIT-All is filed with the ERC.
The paper focuses on the FIT Differential (FD) component, which makes up bulk of the FIT-All rate. The
following formula represents the FD3:
𝐹𝐷 = ∑ [(𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡 𝑅𝐸 𝐺𝑒𝑛𝑥,𝑡+1 ∗ (𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡 𝐹𝐼𝑇 𝑅𝑎𝑡𝑒𝑥,𝑡+1 − 𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡 𝐶𝑜𝑠𝑡 𝑅𝑒𝑐𝑜𝑣𝑒𝑟𝑦 𝑅𝑎𝑡𝑒𝑥,𝑡+1))]
𝑥
+ 𝐹𝐷𝑡−1, (𝑜𝑣𝑒𝑟)/𝑢𝑛𝑑𝑒𝑟
Where:
Forecast RE Genx,t+1 is the Forecast RE Generation of Eligible RE Plant x in kWh,
Forecast FIT Ratex,t+1 is the FIT Rate, as degressed (if applicable) and adjusted for local
inflation and foreign exchange (FOREX) as forecasted for Year t+1 that Eligible Plant x is
forecasted to receive for each kWh delivered,in PhP/kWh,
Forecast Cost Recovery Ratex,t+1 is the applicable Forecast Cost Recovery Rate to be
implemented in Year t+1 for Eligible RE Plant x, in PhP/kWh,
FDt-1, (over)/under is the variance between the actual FIT Differential for year t-1 (Actual FD
t-1) and the FIT Differential collected for year t-1 (Collected FD t-1). There is over recovery
if Collected FD t-1 > Actual FD t-1 and under recovery if Collected FD t-1 < Actual FD t-
1. Any over recovery shall be reflected as a negative number and any under recovery shall
be reflected as a positive number.
4
The plants eligible for FIT scheme enrolment were limited by capacity per type of technology. The table below
shows the guaranteed FIT rates and the installation targets for each RE technology at the start of implementation:
Initial Installation Targets
RE Technology FIT Rates (Php/kWh) Installation Targets (MW)
Solar 1* 9.68 50
Wind 1 8.53 200
Biomass 6.63 250
ROR-Hydro 5.90 250
Total 750MW *Applies only to Solar plants that commercialized before March 16, 2016
5
Main Contents
Scope and Limitations
In this rate analysis, the following are not considered as part of the paper’s scope:
The use of grid energy battery storage
Projection and comparison with fossil fuel rates
Analysis of peak shedding by solar sources
The additional ancillary services costs to address intermittency of RE sources, such as solar and wind,
which are usually addressed by more expensive peak load plants
Economic effects in the long-term by changes in investment expectation (base load de-prioritation in
dispatch order, peak load flexibility, etc.)
Feed-in Tariff (FIT) scheme implementation timeline
The significant developments regarding the FIT scheme implementation over the past few years are listed below:
2010
July The FIT Rules were promulgated by the Energy Regulatory Commission (ERC).
2012
July Two years after promulgation, the FIT Rates were approved by the ERC.
2014
February The FIT-All Guidelines were promulgated.
April The Philippine Department of Energy (DOE) increased the installation target for Solar
technology from the previously set at 50MW to 500MW.a
2015
February The FIT-All of PhP0.0406/kWh was implemented. The FIT-All was included in the
distribution billing statement as a separate line item to be imposed and collected by the DUs
from the consumers connected to their respective systems.
March The ERC approved a new Solar FIT2 rate of PhP8.69/kWh.
April The PhilippineDepartment of Energy (DOE) increased the installation target for Wind
technology from the previously set at 200MW to 400MW. a
October The ERC approved a new Wind FIT2 rate of PhP7.40/kWh.
2016
April The ERC granted provisional approval to a new FIT-All rate of PhP0.1240/kWh.b
After more than a year of the FIT scheme implementation, the Energy Regulatory Commission (ERC)
provisionally-approved the new FIT-All rate of PhP0.1240/kWh. This rate is more than three times higher than
the FIT-All rate implemented in 2015 which was at PhP0.0406/kWh. This came after the National Transmission
Corporation (Transco), the FIT-All rate administrator, filed their 2016 FIT-All Rate Application in March 2016.
As presented in the calculations contained in their rate application, the sharp increase was primarily caused by the
rise in projected energy generation of FIT-eligible plants.
Noteworthy events were formatted in boldface for emphasis:
a. The increase in installation targets for Solar and Wind technologies to 10x and double their initial levels,
respectively.
b. The first recalculation of the FIT-All rate whichnotably tripled from its initial level a year before. FIT-
All rate was amplified mainly because of the adjustment in the FIT Differential (FD) component, which
was in turn driven by the upsurge in its RE Forecast Gen component, and further pushed upmore by its
FD (over)/under recoverycomponent.In its first year of implementation, FD posted an under recovery
due to the unforeseen lower rates in the wholesale electricity spot market (PEMC).
The two FIT rate components mentioned in b are also the most likely to be affected by recent policy changes
stated in a. With the FIT-All rates being shouldered by all the consumers, there’s a need to simulate the effects
caused by these policy changes, and foresee if the succeeding rates are going to continue to grow substantially
and become a heavier burden for them.
One the other side of the coin, the Philippine DOE justified the raise of installation targets under Solar and Wind
technologies. There was oversubscription for the said RE sources, indicating strong investor confidence. In other
6
words, applications and planned developments were more than the required capacity under the FIT scheme. This
urged the Energy department to revisit and revise the installation targets and accommodate the investors.
The Energy department also claimed that they decided to hike the allocation for solar projects to address supply
problems during summer due to limited available power generation capacities. In June 2014, Energy Secretary
Jericho Petilla said that he wants additional solar plants because the profile of solar fits summer, and that “solar
(panels) work best during summer, so that’s the most efficient.” Notwithstanding the technicality of this statement
being questionable, the Energy department sought to address reliability of power supply by using intermittent
sources with higher costs.
The RE Law aims to promote investments in RE, but this support to sustainable energy sources should be balanced
with consumer interests such that financial burden are endeavored to be minimized. This paper would also like to
note that the government did not commission any study and assess this balance.
The installation targets with the additional capacity allocated for Solar and Wind sources are shown in the table
below:
Updated Installation Targets
RE Technology FIT Rates (Php/kWh) Installation Targets (MW)
Solar 1 9.68 50
Solar 2 8.69 450
Wind 1 8.53 200
Wind 2 7.40 200
Biomass 6.63 250
ROR-Hydro 5.90 250
Total 1,400MW
The table below shows the latest FIT Monitoring Board Summary as of January 20164:
RESOURCE
For Nomination /
Conversion
With Certificate of
Confirmation of
Commerciality
With Certificate of
Endorsement to
ERC TOTAL
No. of
Projects
Capacity
(MW)
No. of
Projects
Capacity
(MW)
No. of
Projects
Capacity
(MW)
Hydro - 66 610.93 4 26.60 637.53
Wind 7 1,023.55 5 431.00 6 393.90 1,848.45
Solar 18 681.30 30 892.54 6 131.90 1705.74
Biomass - 4 24.37 11 94.25 118.62
TOTAL 25 1,704.85 105 1,958.84 27 646.65 4,310.34
In applying for a Certificate of Eligibility (COE) from DOE, RE developers must first secure a Confirmation of
commerciality. The certificate of commerciality upgrades the status of the project from pre-development stage to
development stage. This confirmation will also serve as the “go” signal for the construction phase of the project.
Only those with Confirmation of Commerciality are qualified to get the FIT COE. To qualify for FIT COE, the
developer must inform the DOE of the date of the successful commissioning of the plant. Upon validation, the
DOE issues the COE on a “firstcome first served” basis.5 As of January 2016, there were 157 projects that applied
to be included in the FIT scheme. 25 out the 157 projects are still in the process of applying for
nomination/conversion to commerciality. There are still 105 projects that are still in the development and
construction stage while 27 projects have successfully acquired a COE of DOE.
These figures will be used in the simulations later in the paper to demonstrate the effect of the policy changes
promulgated by the Philippine DOE.
7
Breaking down the components of the FIT-All Rate
The FIT Differential (FD), Working Capital Allowance (WCA), Administration Allowance (AA), Disbursement
Allowance (DA), and Forecast National Sales (FNS) mainly drive the overall FIT-All rate. Among all of the
factors included in the numerator, the FIT Differential has the strongest effect on the overall FIT-All Rate
𝐹𝐼𝑇 − 𝐴𝑙𝑙 =𝐹𝐷 + 𝑊𝐶𝐴 + 𝐴𝐴 + 𝐷𝐴
𝐹𝑁𝑆
Where:
FIT-All is the Feed In Tariff Allowance to be implemented in Year t+1 in PhP/kWh,
FD is the estimated Total FIT Differential required for Year t+1 in PhP,
WCA is the estimated Working Capital Allowance required for Year t+1 in PhP,
AA is the Administration Allowance to be implemented in Year t+1 in PhP,
DA is the Disbursement Allowance to be implemented in Year t+1 in PhP,
FNS is the Forecast National Sales, in kWh, to be applied for Year t+1 in PhP,
And, t is the year the petition for setting the FIT-All is filed with the ERC.
The FIT differential represents the difference between: (1) the forecast applicable FIT Rate for Year-t+1 that each
eligible RE Plant is forecasted to receive for each kWh delivered and (2) the forecast applicable cost recovery rate
as determined under the Guidelines, multiplied by the projected annual energy generation from eligible RE plant
for yeart+1.6 FD is represented by the formula below:
𝐹𝐷 = ∑ [(𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡 𝑅𝐸 𝐺𝑒𝑛𝑥,𝑡+1 ∗ (𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡 𝐹𝐼𝑇 𝑅𝑎𝑡𝑒𝑥,𝑡+1 − 𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡 𝐶𝑜𝑠𝑡 𝑅𝑒𝑐𝑜𝑣𝑒𝑟𝑦 𝑅𝑎𝑡𝑒𝑥,𝑡+1))]
𝑥
+ 𝐹𝐷𝑡−1, (𝑜𝑣𝑒𝑟)/𝑢𝑛𝑑𝑒𝑟
The FIT Differential directly affected by policy changes (i.e. changes in installation targets) and the merit order
effect allegedly caused by the increase of RE plants that are tagged as must-dispatch or priority dispatch units.
This paper will simulate the effects of the increase in installation targets to the FD and FNS and understand how
the lower spot market prices affect the FD component and the entire FIT-All rate.
The lower spot prices brought by ‘merit-order effect’ results to higher FIT Differential and overall
FIT-All rate
In the 2016 FIT-all Rate Application, the FIT-All fund administrator, TransCo, stated that the FIT-All fund posted
a 2015 deficit of PhP1.84 billion. Hence, TransCo included an under-recovery component in its 2016 rate
application. The 2015 under-recovery resulted from the lower spot market prices. The lower-than-expected spot
market price made their initial forecasted applicable cost recovery overstated. This means that the FD was under-
estimated due to the unforeseen lower spot prices.The inclusion of FIT-eligible plants to the electricity spot market
is also considered in the FIT-All rate analysis. Since RE plants under the FIT system are considered as must-
dispatch or priority dispatch units, the inclusion of RE plants creates a merit order effect (MOE) that allegedly
results in lower spot market prices.
Electricity spot prices come in the equation through the Forecasted Applicable Cost Recovery in the FIT
Differential component of the FIT-All Rate.
As stated by Nicolosi and Fursch, “The integration of the ambitious RES-E targets is going to change the
economics of the power market.”7
It has been shown in various studies and through different methodologies that the infeed of electricity
from wind power plants has a price reducing effect. This is not surprising, since the provision of “free
power” to the conventional power market reduces the demand for conventional power and thereby
lowers the intersection between the demand and supply curve, which means basically that a cheaper
power plant sets the power price. The power is free to the conventional power market for two reasons.
First, the variable costs of wind power are virtually zero. The wind power costs are mainly based on the
investment costs, which mean fixed costs. These fixed costs are not relevant for the conventional power
8
market, since the pricing is purely based on the variable costs. Second, in feed-in tariff support schemes,
such as in Germany, the remuneration of wind power is based on fixed tariffs for every produced kWh
independent of the time of generation. Therefore, the wind power becomes fed into the market whenever
the wind blows.
Stacking of Generation Plants in the Spot Market
Merit Order Effect on the Stacking of Generation Plants in the Spot Market
In the case of the Philippines, the most supported RE technologies are the solar and the wind, as validated by the
over-subscription, increased installation targets, and the continued flow of applications to the Philippine DOE.
The priority dispatch to these sources may have pushed the supply curve to the right, as was the case in the paper
on Germany power market and wind generation, which would effectively lower prices for a fixed demand.
9
+ -
Law of Supply and Demand
There is also the unquantified effect of base load plants bidding lower than their variable costs to avoid ramp
down. The driver is the opportunity costs, since technical restrictions might result in missed potential earnings
once demand inches up again.
Because the FIT scheme entails that all FIT-eligible RE plants shall receive guaranteed revenue, this means that
end-users would bear the necessary costs—only the channel of compensation may shift from one component of
the formula to the other. The alleged merit order effect (MOE) would result in Under-recovery in current year,
which is later “corrected” in the FIT rate application for the succeeding year. A lower Forecast Cost Recovery
Rate (FCRR) on the other hand, is by inspection inversely proportional to the FIT-Differential, FD.
𝐹𝐷 = ∑ [(𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡 𝑅𝐸 𝐺𝑒𝑛𝑥,𝑡+1 ∗ (𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡 𝐹𝐼𝑇 𝑅𝑎𝑡𝑒𝑥,𝑡+1 − 𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡 𝐶𝑜𝑠𝑡 𝑅𝑒𝑐𝑜𝑣𝑒𝑟𝑦 𝑅𝑎𝑡𝑒𝑥,𝑡+1))]
𝑥
+ 𝐹𝐷𝑡−1, (𝑜𝑣𝑒𝑟)/𝑢𝑛𝑑𝑒𝑟
Thus, the short-term tempering effect on electricity spot prices brought by the MOE is cancelled out in full by the
Under-recovery correction term and the lower FCRR.
10
Increase in Installation Targets also Increases the FIT-All rate
The effect of FIT-related policy changes, i.e., the increased installation targets for solar and wind, were simulated
by using scenario analysis.
Baseline scenario – Assumed full subscription to the initial installation targets set by the Philippine
DOE.
Scenario 1 – Assumed full subscription to the updated installation targets, in which the Philippine DOE
approved the addition of solar and wind capacity of 450MW and 200MW, respectively.
Scenario 2 – Aggressive scenario. Assumed full subscription and accommodation of all FIT-applicants
beyond the installation targets, using data from the FIT monitoring report of the Philippine DOE.
Forecast RE Gen is computed using the installation targets and the net capacity factors for each technology based
on ERC orders. For Scenario 2, FIT applicants’ data were used as input as well. For simplicity, and without loss
of generality, assumed starting years of 2016 and 2017 were used for Scenarios 2 and 3. After all, revenues were
all in real terms, and the capacity and rates at the end of the 20th year of FIT scheme implementation was analyzed.
Scenario 1 resulted in increased RE generation by 1.36x by the end of the 20th year of FIT scheme implementation
compared to Baseline, while Scenario 2, by 4.79x.
FIT Rates are computed per year with an adjustment for foreign exchange rate and inflation, based on data from
Philippine Statistical Authority (PSA), Bangko Sentral ng Pilipinas (BSP, the central bank) ERC orders as well.
Degression rates were not applied yet. For Scenario 3, rates for additional FIT applicants were set at the same rate
as the lowest rate of the same technology as shown in the table.
Resource Installation Target (MW) NCF FIT Rate (Php/kWh)
Solar 1 108.9* 22.00% 9.68
Solar 2 391.1* 18.50% 8.69
Wind 1 200 27.50% 8.53
Wind 2 200 27.50% 7.40
Biomass 250 72.00% 6.63
ROR-Hydro 250 47.00% 5.90
* The indivisibility rule was applied to solar installation targets. Hence, the initial installation target of 50MW was exceeded in Solar 1.
FIT Payments are computed by getting the product of the Forecast RE Gen and the FIT rates for each technology
type.
11
Impact of Policy Changes to Total FIT Payments
Scenario 1 resulted in increased FIT Payment by 1.44x by the end of the 20th year of FIT scheme implementation
compared to Baseline, while Scenario 2, by 5.19x.
Forecast National Sales were from the Philippine DOE projections.
12
Results
The Feed-in-Tariff (FIT) policy mechanism in the Philippines has spurred substantial capacity addition from
emerging renewable energy sources, mainly wind and solar PV and, to a much smaller extent, run-of-river hydro
and biomass. In response to the overwhelming number of FIT applications, particularly, from solar PV and wind
developers, the DOE adjusted the FIT installation targets to accommodate RE developers.
While this seems like an auspicious move for RE in the country, there has been a consequence for end-users. This
consequence came in the form of higher electricity rates. The expansion of installation targets resulted in an
increase in volume of energy generated by FIT-eligible plants that have to be paid and recovered from the end-
users. It is also important to note that the expansion of installation targets was implemented to the two most
expensive technologies included in the FIT Scheme, Solar and Wind.
The merit order effect caused by FIT-eligible plants, on the other hand, tended to lower the clearing price in the
spot market—a short-term effect on the generation charges. However, both the increased volume of generation of
FIT plants and the resulting reduced spot prices would ultimately drive up the FIT-All rate to be collected from
end-users.
13
Conclusion and Recommendation
The Philippines is one of the emerging economies in its region and it has gained momentum as consecutive credit
rating upgrades were given by top credit rating institutions. Despite the positive outlook on the Philippines, the
country still struggles to improve on its competitiveness. Increases in power rates due to policy changes can be
completely controlled by the government. The government should be completely aware on the impact of policies
to the overall welfare of the people. Hence, economic impact studies would be helpful for state regulators and
policy makers to make informed policy decisions that take into account the welfare of all stakeholders especially
the customers. The promotion of renewable energy technologies do help our country reduce or dependence on
expensive fossil fuels and carbon emissions but balancing of interests should always be considered.
The forecast for volume generated by FIT-eligible plants largely affects the FIT-All rate. Abrupt changes in policy,
such as the expansion of installation targets, inflate said volume and, consequently, the FIT-All that all the end-
users will need to bear. Thus, to manage the FIT-All rate and its adverse impact on the electric bills of end-users,
there is a need to carefully consider any proposal to further expand the installation targets. Moreover, rate and
technical impact studies should be done prior to implementation of policy changes to help keep the FIT-All rate
manageable.
Policies should consider the long-term view. Possibilities of flexibility in demand might help ease the pressures
in supply that push up prices. Consideration of investments in “smart grids” is one of the demand-side solutions.
14
References
1 DOE Power Statistics 2014 2 Regional Comparison of Retail Electricity Tariffs by International Energy Consultants (IEC), June 2012 3 ERC ResolutioN No. 24, Series of 2013 4 Department of Energy (www.doe.gov.ph) 5 FIT Application Guidelines from the Department of Energy 6 2016 FIT-All Rate Application submitted by the National Transmission Corporation (TransCo) 7 The Impact of an Increasing Share of RES-E (electricity from renewable energy sources) on the Conventional Power
Market – The Example of Germany, Marco Nicolosi and Michaela Fursch
