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Economic Currents

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UHERO 101.12: What is the Value of the Environment?

The Earth’s environment is divided into different combinations of living organisms and their nonliving surroundings: air, water and soil. These different organic communities are called ecosystems. Humans receive benefits from these ecosystems in the form of “ecosystem services”, a term that covers a range of benefits from artistic inspiration to soil detoxification. (See below for a list of example ecosystem services)*

In 1997 Robert Costanza and 12 other authors wrote an eye-opening article in Nature called “The value of the world’s ecosystem services and natural capital” (Costanza et al. 1997). It stoked interest in environmental valuation because of the $46 trillion/year value (in 2007 US dollars) it placed on the planet’s services. After factoring land use change the value of Earth's services in 2011 was updated to $125 trillion/year (in 2007 US dollars) (Costanza et al. 2014). The goal of Costanza et al. (1997) was not to commodify the environment, but more so to raise awareness to what these environmental benefits are worth in a capitalist market economy. The methods for arriving at these dollar figures were questioned and the valuation was controversial because some people are naturally inclined to ask…

How can you put a dollar value on the environment?

Putting aside the ethical question of assigning dollar values to experiences and connectivity with other people and nature, the below table sums up how previous academic research has addressed environmental valuation: 

 

These valuation methods are further described in Module 4, Session 2 of this training resource from The Economics of Ecology & Biodiversity (TEEB).

Prices of goods and services sold in markets can be used to arrive at a dollar value for certain aspects of the environment, but in the case that market values are not available, non-market based methodologies have been used to arrive at a value. Ecosystem service valuation is a relatively new field and researchers are collecting results from previous studies to help future researchers confirm what valuation methods work best for different ecosystem services (Ecosystem Services Valuation Database). A paper was written by De Groot et al. (2002) which includes a table of ecosystem functions and their compatibility with different valuation techniques to help guide in assigning a dollar value to ecosystem services. With some ecosystem services there are intrinsic values (such as existence values) that are hard to put into dollar terms. It doesn’t always have to be about money....

There is more than one way to value the environment

Ecosystem services do not have to be valued in terms of dollars. Any unit can be the common denominator such as time, energy, or freshwater, for example. Environmental valuation differs from financial valuation in that it is rarely done to account for an entity’s profit, it is done to account for alterations humans have made on the environment, or to help decision makers evaluate consequences of their actions. Farber et al. (2002) defines valuation as an assessment of trade-offs toward achieving a goal such as reduced carbon emission, increased habitat or improved water quality.

An important concept to keep in mind is that people do not directly benefit from ecosystems without human, social and built capital. The valuation of the environment’s natural capital must be parsed out from the entire interaction between people, communities and their built environment. It is only through institutions as well as human management and invention that we extract benefit from nature (Costanza et al. 2014). The scope, precision, techniques and units used in an environmental valuation depend on the purpose. Ecosystem service valuations are done at different spatial scales to suit different objectives such as raising awareness, national income and well-being accounts, specific policy analyses, land use planning, payment for ecosystem services, full cost accounting and common asset trusts. For more information on the field of ecosystem service valuation check out references below:

Ecosystem Services:
The Ecosystem Services Partnership
The Economics of Ecosystems & Biodiversity Initiative

Referenced Papers:
Costanza, Robert, Rudolf de Groot, Paul Sutton, Sander van der Ploeg, Sharolyn J. Anderson,
          Ida Kubiszewski, Stephen Farber, and R. Kerry Turner. 2014. “Changes in the Global
          Value of Ecosystem Services.” Global Environmental Change 26 (May): 152–58.           doi:10.1016/j.gloenvcha.2014.04.002.

De Groot, Rudolf S., Matthew A. Wilson, and Roelof MJ Boumans. 2002. “A Typology for
          the Classification, Description and Valuation of Ecosystem Functions, Goods and           Services.” Ecological Economics 41 (3): 393–408.

Farber, Stephen C., Robert Costanza, and Matthew A. Wilson. 2002. “Economic and
          Ecological Concepts for Valuing Ecosystem Services.” Ecological Economics 41 (3):
          375–92.

Robert Costanza, Ralph D’arge, Rudolf de Groot, Stephen Farber, Monica Grasso, Bruce
          Hannon, Karin Limburg, Shahid Naeem, Rpbert V. O’Neill, Jose Paruelo Robert G.
          Raskin, Paul Sutton & Marjan van den Belt. 1997. “The Value of the World’s Ecosystem           Services and Natural Capital.” Nature 387 (May): 253 – 260.

 - Cheryl Geslani

*(List comes from the Ecosystem Services Valuation Database)

Air quality regulation Fish Pollination of crops
Animal genetic resources Flood prevention Prevention of extreme events [unspecified]
Artistic inspiration Fodder Provisioning values [unspecified]
Attractive landscapes Food [unspecified] Raw materials [unspecified]
Biochemicals Fuel wood and charcoal Recreation
Biodiversity protection Gas regulation Refugia for migratory and resident species
Biological control [unspecified] Genetic resources [unspecified] Regulating [unspecified]
Biomass fuels Hunting / fishing River discharge
Bioprospecting Hydro-electricity Sand, rock, gravel. Coral
C-sequestration Industrial water Science / research
Capturing fine dust Inspiration [unspecified] Seed dispersal
Climate regulation [unspecified] Irrigation water [unnatural] Soil detoxification
Cultural use Maintenance of soil structure Soil formation
Cultural values [unspecified] Meat Solar energy
Decorations / Handicrafts

Microclimate regulation

Spiritual / Religious use
Deposition of nutrients Natural irrigation Storm protection
Disease control NTFPs [food only!] TEV
Drainage Nursery service Timber
Drinking water Nutrient cycling Tourism

Dyes, oils, cosmetics (Natural raw
material for)

Other ESS Various
Ecotourism Other Raw Waste treatment [unspecified]
Education Pest control Water [unspecified]
Energy other Pets and captive animals Water Other
Erosion prevention Plants / vegetable food Water purification
Fibers Pollination [unspecified] Water regulation [unspecified]
Fire prevention    

 


How Do We Manage Our Interdependent Environmental Resources?

Managing water resources requires an understanding of the linkages between key hydrologic factors and direct human influences. The problem is further complicated by the fact that water resources are often interdependent, which suggests that management should also account for ecological interlinkages. For example, a forested upstream watershed may replenish an underlying groundwater aquifer, or a coastal groundwater aquifer may provide positive spillover effects to a downstream nearshore resource such as a fishery. Left unregulated, these spillover effects are economic externalities—additional, unintentional costs or benefits. In general when private parties act in their self-interest in the presence of externalities, the outcome may not be the best for society.

The Kukio Region: Groundwater and Limu

In an application to the Kukio region on the Big Island, Pongkijvorasin et al. (2010) explore how the relationship between submarine groundwater discharge (SGD) and a keystone algal species, Gracilaria coronopifolio (“limu”), in the nearshore affects optimal water management. Lab experiments suggest that moderate levels of SGD influx to a coastal marine environment increase the growth rate of limu due to resulting changes in nutrient loads, temperature and salinity (Duarte et al., 2010). A reduction in the aquifer, and hence SGD, generates a negative externality since there is less water entering the coastal environment. This study shows that optimal water management before accounting for the limu involves only slightly higher water pumping rates (roughly 6 million  per year over 100 years in both cases) because the market value of algae is relatively small compared to the benefits of water consumption. However, the market value of limu does not include ecological and cultural values. One way to account for values that are difficult to monetize is a minimum algae-level constraint. If the stock of limu is constrained to be no less than 90% of its current level, the effect on optimal extraction rates is much more dramatic: extraction starts at approximately 4 million  per year, falls to 3 million  annually by year ten, and stabilizes at less than 0.5 million  per year from year 22 onward.

Incentivizing Externalities

Once we understand how optimal resource extraction rates change in the presence of an externality, the next question is how do we internalize it? In other words, what can we do to incentivize private actors (e.g. water consumers) to behave in a way that provides the most benefits to society? When the externality is negative, as is the case where reducing the groundwater stock slows limu growth in the nearshore, a corrective tax can be implemented to reduce groundwater extraction and increase the benefit of higher groundwater levels over a longer period of time. When the externality is positive, as is the case when watershed conservation activities increase recharge for a downstream aquifer, the socially optimal level of conservation can be incentivized using payments or subsidies. As the number of positive and negative externalities within a water management system increases, so does the complexity of the optimal tax/subsidy formula. Nevertheless, advancing methods for managing linked natural systems is important, especially in the context of water resources, given trends of increasing scarcity worldwide and the expected effects of climate change.

-Christopher Wada

 

References:

Duarte, T.K., Pongkijvorasin, S., Roumasset, J., Amato, D. and K. Burnett (2010), ‘Optimal management of a Hawaiian Coastal aquifer with nearshore marine ecological interactions’, Water Resources Research46, W11545.

Pongkijvorasin, S., J. Roumasset, T.K. Duarte and K. Burnett (2010), ‘Renewable resource management with stock externalities: Coastal aquifers and submarine groundwater discharge’,Resource and Energy Economics32, 277-291.
 

WORKING PAPER


Income Inequality in Hawaii Since Statehood

Posted June 5, 2014 | Categories: Hawaii's Economy, Blog

Thomas Piketty’s best-selling tome on the evolution of inequality in the US, Capital in the Twenty-First Century, has inspired us to ask—how does the distribution of income in Hawaii compare with that in the country as whole?  And how has that distribution changed over time?  To answer these questions, we construct an extended time series of data on income distribution and measures of income inequality for Hawaii. Using tax data from the Internal Revenue Service (IRS) and the State of Hawaii Department of Taxation (HIDOT), we compare various measures of inequality in the US and Hawaii.*

Income Share by Income Class

Here we use the labels used by Piketty to describe various groups in the income distribution. The “Dominant Class” is made up of the top one percent of families; the “Well-To-Do Class” is the group of the nine percent of families below the “Dominant Class”. The next 40 percent is called the “Middle Class” and the remaining 50 percent the “Lower Class.”



Looking at the IRS and HIDOT data,**
 we can see the share of income going to the “Dominant Class” increases while the share going to the “Lower Class” decreases steadily from the mid 1950s up to the present for both the US and Hawaii.   However, we also see that the income distribution in recent years is more compressed in Hawaii than the US.

Let's
 focus in on each of these classes one at a time to more cleanly compare the pattern of inequality in Hawaii to that in the US as a whole.  

The share of income claimed by the top one percent has been lower for Hawaii than for the US overall since the early 1980s. Up until the mid 1990s the share of income claimed by the bottom 50 percent in Hawaii lagged behind the share claimed by the bottom 50 percent in the US overall.

The Gini coefficient is one measure of the distance between a perfectly equal distribution of income and the actual distribution of income. A Gini coefficient of zero represents a perfectly equal society while a coefficient of one occurs when one individual claims all the income and everyone else claims none. Since the mid 1950s, the Gini coefficient has steadily increased from 0.43 to around 0.60 for both Hawaii and the US as a whole.



Income Mobility

One important caveat in this analysis is the importance of mobility. If those who were in the “Lower Class” last year are in the “Well-To-Do Class” this year, inequality is merely temporary.  Unfortunately, recent research on inequality in the US and various Northern European countries suggests that greater inequality of incomes in the present leads to reduced intergenerational mobility in the future (Corak, 2013). 

The Equality of Opportunity Project
 hones in on this issue of income mobility and the New York Times produced an interactive map for exploring the data. From this we can see that a child raised in Honolulu whose family income was in the bottom 20% had a 10.1% chance of reaching the top 20% of family income in adulthood. 


Forces Behind Distributional Changes

One important finding in our analysis is that, since the mid-nineties, the share of income going to the top 1% is lower and the share going to the bottom 50% is higher in Hawaii than in the US.  The fact of the matter is, economists don’t fully understand all of the causes of inequality, and a full analysis of the causes for Hawaii is well beyond the scope of this blog post.  We can, however, speculate on potential causes based on the rapidly growing research on inequality.

First, higher levels of unionization in Hawaii may be protecting wages in the bottom of the distribution.  In addition, recent evidence from Autor, Dorn and Hanson (2013) has shown that China’s entry into the WTO has severely hit wages of low skilled workers in the US, so the absence of a large manufacturing sector in Hawaii may be responsible for the higher income shares in the bottom half of the distribution in Hawaii vis-à-vis the US mainland.

The top 1% is not as well understood.  Some such as Piketty have speculated the higher top income shares are the consequence of increased rent seeking (i.e., the top 1% increase their slice of the pie, while not increasing the size of the pie overall), while others have opined that the returns to innovation and highly skilled labor have increased for poorly understood reasons.  Many such as Joseph Stiglitz and Michael Roberts in an earlier post have pointed out that Hawaii’s economy has many uncompetitive industries such as electricity production and shipping.  However, this would suggest higher top income shares than elsewhere, not lower.  Another possibility could be that the industrial composition of Hawaii excludes much of finance, technology and biotech.  This suggests that a relative lack of highly specialized professionals in Hawaii may be responsible.

--Jonathan Page and Timothy Halliday




*Both the IRS and HIDOT report the number of returns by adjusted gross income (AGI) group (e.g., less than $1,000; $5,000 to $10,000; etc.). The total AGI reported for each group of returns can then be used to construct the proportion of total income a given group of families can claim (we use the total AGI reported instead of the income component from the national accounts). Income brackets reported by the tax agencies do not perfectly align with the percentage groups used by Piketty. For example, in 2005 those returns with AGI below $50,000 comprised 72.85% of all returns in Hawaii. To overcome this issue, we follow the procedure in Piketty and Saez (2003) to estimate incomes at the top of the income distribution. 

**HIDOT data covers 1958-2005, IRS data are used for 2006-2011.

References:

Autor, D. H.; Dorn, D. & Hanson, G. H. 2013. "The China Syndrome: Local Labor Market Effects of Import Competition in the United States," American Economic Review, 103(6), 2121-68.

Corak, M. 2013. “Income Inequality, Equality of Opportunity, and Intergenerational Mobility,” Journal of Economic Perspectives 27, 79-102.

Piketty, T. & Saez, E. 2003. “Income Inequality in the United States, 1913-1998.” Quarterly Journal of Economics 118 (February), 1 – 39.


Managing a Grid with Green Energy

The calculator in the last post shows that installing solar is an incredibly valuable investment for households and businesses with the physical and financial ability to do it.  The gains are so large that some wonder why the state is nearly breaking its budget to subsidize what would still, even without the state tax credit, be a windfall gain for the typically wealthy households able to take advantage of the situation.

Things can look different at the system level.  Even if there is enough rooftop space available, we can't all install solar, because of a mismatch between electricity generation and electricity use.  It works well when only a fraction of households have solar, because those with solar panels effectively sell their electricity to their neighbors when they can't use all of it, then buy it back later when the sun isn't shining.  Put another way, the existing electric grid effectively serves as the solar household's battery. Under current net metering agreements the household's price for that battery is just $17 per month, plus any surplus generation not used over the course of a year (which might actually be considerable).

The situation is similar for wind.  Few if any of us will have windmills on top of our houses.  But nature's variable supply of electricity from the wind, like the sun, doesn't perfectly match our varying collective desire to consume electricity.

Our Grid Manager

Hawaiian Electric, our grid manager  (unless you're on Kauai) adjusts power from dispatchable sources (fossil fuel power plants) to compensate for variability from renewables.  If the share of renewable energy is modest, this is a fairly easy thing to do.  In fact, a modest amount of solar makes this job easier, because it knocks down peak loads on hot days.  Small, oil-burning generators satisfy peak loads, but these cost about two-and-half times the average cost of generation.

To get a sense of how the whole system works, the graph below shows load activity over the coarse of seven warm days in October, with a high peak load and light, variable wind.  The load curve varies throughout each day, with more electricity consumed in mid-day and early evening, and then falling off at night. Weekend loads (the last two humps) are a bit lower than weekday loads. In the warmer months, midday spikes more, mainly due to air conditioning and industrial uses.  In winter midday loads are a bit lower. 

 


Source:  Hawaii Solar Integration Study by GE Energy Consulting, April 1, 2013.


Different sources of electricity fill up the load curve. The load is typically satisfied with least-flexible, and typically least-expensive sources first.  Oahu's coal power plant generates electricity at just 5 cents/kWh, but its loads are difficult to ramp up and ramp down as demand or renewable supply changes.  This power plant helps to keep Oahu's prices lower than the other islands, but we're probably too small to have another base load powerplant like this one.  Cycling generators are more flexible, but also cost more per kWh.  Peaking generators, in red, are the most flexible, but very expensive and are only turned on when they have to be.  

The load shares beneath the curve were derived from a model developed by GE Energy Consulting.  Validation exercises show this model fits the actual situation extremely well, so it has been the basis of studies considering how different levels of renewable energy can fit onto the grid.

In the graph, we can see that solar provides energy when cycling and peaking generators are also being used.  That means the electricity is worth a lot more than average. However, in this graph solar is just 1.2% of total generation and wind is 3.6%.  In winter, midday load is less and solar would mainly displace cycling generators.

Solar energy can be especially valuable

If solar increases to 7.5% percent of the average load holding all else the same (for perspective, we're currently around 5%), the energy provided remains fairly valuable, displacing peak and cycling generators.  But more reserves are needed to stabilize unexpected variability from renewables.

By knocking down peak loads, Hawaiian Electric's cost savings from solar installations may be substantially greater than suggested in our last post.  The report by GE Energy Consulting shows that, averaging over the whole year, increasing solar by 6.3 percent (from 1.2 to 7.5) reduces HECO's oil generation costs by 9.2%, which suggests that HECO's savings from solar is about 46% higher than their average cost of generation.  This would put HECO's per kWh savings roughly on par with their revenue loss.  And that's not counting surplus generation under net metering agreements or the revenue-decoupling rule.

Bigger challenges at higher penetration levels

At current penetration levels, solar remains valuable.  But Hawaii is striving for 40% renewable energy, possibly much more.  When penetration levels increase, it becomes more difficult to adjust directed sources in response to varying renewables.  The graph below looks at an especially cool but sunny week in March assuming 14.8% solar penetration, or nearly three times our current level.  Under the current system, a lot of the solar energy would have to be “curtailed” (discarded), since base loads could not be economically reduced to accommodate it.  Here, solar becomes a lot less valuable at high penetration levels.  This level of green energy will require more creative grid management, more flexible and expensive generators, batteries, and/or shifting of load from the evening to when the wind is blowing or midday when the sun is shining brightest. These investments could be costly.  Without these major investments, pushing PV solar from 7.5% to 14.8% reduces costs from dispatchable sources by only 6%.  Where the first 7.5% of PV solar is worth considerably more than average, the next 7.3% of solar is worth about 18% less than average.


Source:  Hawaii Solar Integration Study by GE Energy Consulting, April 1, 2013.


Circuit-level challenges

Part of the difficulty is that our electric grid wasn't designed for renewables.  It was made for directing electricity out from power plants to homes and businesses.  But residential solar is distributed, which means electricity may need to flow in different directions than our grid was designed to handle.  To manage the backflow, new transformers need to be installed to allow energy to flow more easily to and from neighborhood circuits.  These potential challenges have recently stalled solar installations in circuits that are approaching risk of backflow. Although, one may wonder why Hawaiian Electric's rapidly increasing net revenue cannot cover the cost of such upgrades.

New solar inverters and transformer upgrades might improve circuit-level problems.  However, it would probably be more cost effective to install solar in circuits with less penetration, or develop more utility-scale solar and wind power plants.  

The plummeting cost of renewables

Where the cost of residential solar now runs about $4/Watt (which pencils out around 20 cents/kWh using our calculator, unsubsidized), utility-scale costs now average under $2/Watt, or 11 cents/kWh unsubsidized, or about half Hawaiian Electric's costs from fossil fuel sources. Wind is even more cost effective than PV solar.  Plus, Federal subsidies alone currently cover 30-40% of the cost of utility-scale renewables.

Thus, despite new grid challenges with renewables, Hawai'i ought to be charting a path toward much greener and much cheaper electricity.  We're starting to see a lot more renewable energy, but prices have been going up, not down.  Current proposed purchasing power agreements at around 15.7 cents per kWh, while lower than existing agreements, still seem too high.

In subsequent posts we'll write more about current policy, rapidly changing technology, and alternative paths going forward.

- Michael Roberts


The Costs and Benefits of Installing Solar PV

Renewable energy presents many new challenges at the system level. Before we get to that, it helps to first look at things from a homeowner’s perspective.

The Homeowner’s Solar PV Decision

If you’re a homeowner, and you haven’t already installed PV solar, you may want to look into doing it very soon.  To see why, and how much you could benefit, we’ve developed a calculator to help you sort out the costs and benefits of your particular situation.  Our wonky calculator includes a few extra features to take into account uncertainties that can factor into your bottom line, or battery backup if you’re inclined to consider it.  This calculator should help you to decide how large of a system to install and maybe help you comparison shop across solar providers.

 

Homeowner Solar PV Calculator

Value to Homeowner
 
Internal Rate of Return
 
Annual Energy Use
 
Annual Energy Production
 
Up Front Costs
 
Up Front Battery Costs
 
 
 

To get started, you need to estimate your electricity use per day, averaged over the whole year.  You can find this number on your electric bill.  Make sure you average over all twelve months of the year.  Adjust that number up or down depending on you future plans: Do you expect to install more air conditioning? Thinking about buying an electric car? If so, you might want to bump the number up.  Do you plan to install solar hot water, more energy-efficient appliances, air conditioning or LED lights?  If so, you might want to start with a lower number.

Your guess may be a little high or low.  Also, generation from your solar panels and your electricity use may vary depending on the weather or other factors.  To account for uncertainty, you can enter a number for how far off you expect your estimate to be.  A conservative number might be 20% of your estimate (say, 4kWh / day if your best guess for average use is 20kWh/day). 

You also need to account for how much sunlight your panels will be exposed to.  This can vary a lot across each island.  Online resources are available to help you approximate this.  Here is an example for Oahu.  Enter the equivalent hours of peak sun for your location. On Oahu this can vary from around 4 to 6 hours.

Uncertainty about electricity generation and use can make a big difference to your bottom line under the standard net-metering agreement.  That agreement allows you to obtain credit for excess generation from your panels in one month, which you may use in a later month when your use exceeds the energy generated by your panels.  But there’s a limit to the amount of credit you can build up.  Each year, any surplus generation is zeroed out.  So far, homes typically install far more solar than they need.  And as you will see, there’s a fairly strong incentive to over-install, especially if you’re highly uncertain about your electricity use.

The default values in the calculator are those for my house.  I don’t have solar yet.  I’m still waiting for my net metering agreement.  My recent quote for installed cost of my panels, $4.04/Watt, is from a large reputable company.  You can find quotes for less if you shop around.  And keep in mind that prices have been falling fast, and may continue to do so.  You can find this number by dividing the size of the system you plan to install (mine is 3.51 kW) by the total cost BEFORE tax credits, and including taxes and everything else.  Once you have the other numbers pinned down, you’ll want to adjust the size of the system to make the net present value as big as possible (do not maximize the internal rate of return).

The Federal tax credit is currently 30 percent, and the Hawai’i tax credit is 35% up to a maximum of $5000 per 5kW installed.  In my case, the Hawai’i tax credit is just under the cap, $4,963.14. 

Finally, you need to include an interest rate.  If you’re borrowing to finance your solar installation, include the rate on the borrowed funds.  If you’re using savings, you might enter the rate of return you expect on a safe investment vehicle, like a savings bond, certificate of deposit, etc.  This number goes in the first line of the calculator.  I’m using 5 percent.

You can adjust the other assumptions in the list, or just take the default values we’ve entered.  You might ask your solar provider about decay rate, life expectancy of the panels, maintenance, etc. and adjust accordingly.  The price of electricity is assumed to stay constant over the lifetime of the panels.  This may be conservative: most projections we’ve seen anticipate rising prices.  But you can adjust the price level up or down to account for your own expectations.

We’re not considering battery backup now, but some rough numbers are in there in case you want to consider it.  In the not-too-distant future it’s possible our grid may not be able to handle any more solar, which may require you to unplug and use a substantial battery backup if you want to install PV solar.  Note that battery costs vary a lot, depending on the kind of battery, how much you want to store.  Batteries remain expensive, but costs are falling

What’s the bottom line?  Installing this system on our house should net us a present value of approximately $19,949*, with an internal rate of return of 54.4% on our out-of pocket expense of just $5,167, after tax credits. My “pay back” period is about 2.5 years.  Needless to say, you would be very hard pressed to beat this kind of return for any other investment.  Note that I expect to use less electricity than I generate, but installing fewer panels would reduce my net present value. 

Note that I would still net almost $15,000 without the state tax credit and over $10,000 without state or federal tax credits.  Also note that without tax credits, it pays less to over-install.

Hawaiian Electric’s Bottom Line

Although HECO loses sales of 5.5mWh each year when I install solar, amounting to a revenue loss of about $2026, they also save about 7mWh in generation.  At a levelized generation cost of 22 cents/kWh, HECO saves about $1550.  Factoring in a monthly connection fee of $17, HECO nominally loses a net of about $272 per year from my solar installation.

This loss, however, doesn’t account for revenue decoupling, which allows HECO to raise prices on everyone else to make up the full $2026 revenue loss, ultimately providing a net gain of  $1,754.  We expect HECO’s grid management costs have gone up due to high penetration of solar and wind, and these costs would have to be subtracted from this net gain.  Nevertheless, it’s easy to see how HECO can benefit from the revenue decoupling rule and current net metering agreements.

The data do show Hawaiian Electric’s net generation has fallen by a lot more than sales have, a clear indication of widespread over-installations.  In 2009, EIA reports that Hawaiian Electric generated an average of 917.5 million kWh each month, falling to 817.8 in 2013.  Sales, in contrast, fell from 844 to 791.7 million kWh, or just over half the decline in net generation.

Incentives for Energy Efficiency

One side effect from current net metering agreements is that households over-installing solar typically will have little incentive to conserve electricity.  Once it becomes clear that a household will not use all of its solar generation for the year, there is zero cost for leaving lights on and zero benefit from upgrading to LED light bulbs, buying more energy efficient appliances, and so on.  This disincentive is tragic, because most efficient way of reducing greenhouse gas emissions, dependence of foreign oil and generally saving money, is through energy efficiency, even without distorted incentives.

In subsequent posts we’ll discuss alternative regulatory and policy structures that might be more efficient.

- Michael Roberts

 

* Numbers in the text may be slightly different than the calculator due to a random “Monte Carlo” evaluation of uncertainty.  If you refresh the page, the numbers change very slightly each time.


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