Distributed Solar Generation - PowerPoint Presentation

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Distributed Solar Generation

Final Presentation – May 12, 2017

Laura Criste ● Josh Grant ● John Hoffman Slide2

Distributed Generation

Distributed generation is energy

at

the point of consumptionCommon modes of generation include:Solar photovoltaic (PV)Small wind turbineCombined heat and powerFuel cellsMicro-turbinesSolar PV is the largest percentage of distributed generationUnited Sates annual solar PV generation is currently about nine gigawatts and in the next few years, it is expected to exceed 20 gigawatts

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NOVEC’s Current Operations

Northern Virginia Electric Cooperative (NOVEC) is a customer-owned, not-for-profit electricity distributor

NOVEC operates 63 electric substations and 7,100 circuit miles of lines

NOVEC sells the resulting electricity to about 165,000 Northern Virginia customers based on their energy consumption3Slide4

NOVEC’s Current Operations

NOVEC recovers annual operating costs using a pricing structure that includes:

Flat fee to all customers

Distribution charge per kilowatt hour of energy usedElectricity use charge per kilowatt hour of energy usedApproximately 0.1% of NOVEC’s customers use solar PV distributed generationNOVEC’s pricing structure is currently the same for solar and non-solar customers4Slide5

Solar Irradiance

Solar irradiance is the amount of light energy

available from

the sun and can be measured in space or at the earth’s surfacePart of the radiation is reflected and part is absorbedAbsorbed radiation raises earths temperature and some of that energy can be converted into electricity by PV cellsThe atmosphere causes some variance in how much actually reaches the surfaceAnnual mean insolation at the top of Earth's atmosphere and at the planet's surface (Source: William M. Connolley)

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Solar Incentives

Historically, there have been tax incentives at the

federal

, state, and local government levels for residential solar panels At the federal level there is a 30 percent solar investment tax credit for residential installation of solar panels through 2019, which drops to 26 percent in 2020, 22 percent in 2021, and then to no incentivePrince William County offers a property tax exemption, which is good for five years as long as the solar equipment is operational during that year6Slide7

Impact of Solar on NOVEC’s Operations

Customers who own solar panels complicate NOVEC’s operations

Panels reduce the amount

electricity that solar customers need from NOVECNOVEC buys back excess solar-generated energy at the cost it provides electricityEnergy generated from solar is unpredictable because it is based on irradiance, yet NOVEC must provide enough electricity to meet all customer needs at any timeNOVEC expects an increase in solar customers due to the interest in renewable energies and decreasing solar costs, which would intensify the problemNOVEC will see reduced revenue without a change in price structure7Slide8

Problem Statement

Cost

to operate and maintain a reliable electric grid

should be recovered in a way that is fair to all who utilize and rely on its powerSolar customers reduce their total purchased electricity from the grid, but are still fully dependent on it and add operational requirementsUnder the current pricing structure, the reduction in purchased electricity due to solar generation is passed onto non-solar customersBy evaluating how solar and non-solar customers utilize the electric grid, we propose two methods of recovering costs in a more balanced way8Slide9

Problem Scope

Ensures NOVEC meets the operational and financial requirements of a healthy utility provider

Does not

discourage NOVEC customers from supplementing power requirements through the installation of solar panelsIncludes recommendations at different solar penetration levels (one, three, five, 10, 15, and 20 percent)Focuses on cost of energy distribution, not cost of energy itselfFocuses on residential customers, not commercial9Slide10

Assumptions

Operating costs

will not

change over timeNumber of customers will remain steadySolar users will not increase the size of their solar panelsThe solar panels have a 17 percent efficiencyNo storage (batteries) at point of generationData the team received is a good representation of all NOVEC customersNot constrained by current legislative environment10Slide11

Data Collection: Customer Electric Use

Monthly non-solar

kilowatt hours delivered

Monthly solar kilowatt hours delivered and received11Slide12

Data Collection: Financials

Financial statements

Current pricing structure

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Model Methodology: Fitting Monthly Non-solar Data to Distributions

Used R to fit historical monthly non-solar kilowatt use

to a

distributionUsed Cullen and Frey graph to narrow possible distributions13Slide14

Model Methodology: Weibull

vs Gamma

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Model Methodology: Weibull Distribution with 95% Confidence

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Model Methodology: Finding Solar Kilowatt Hour

Use

Due to small sample size, couldn’t determine solar kilowatt hours required from NOVEC using a distribution

Instead, for each month, compared the electricity required from NOVEC during hours with sunlight to those without sunlightThis resulted in the difference in NOVEC-distributed electricity used between solar and non-solar customers16Slide17

Model Methodology: Create Populations For Each Penetration Level

Using monthly distributions, randomly generated the electricity that NOVEC would distribute to 154,000 customers for each month

For the current and each increased solar penetration level, created the appropriate number of solar customers by reducing the amount of electricity they require from NOVEC for that month

17Snapshot from model of the population with a 20 percent solar penetration levelSlide18

Model Methodology: Create Populations For Each Penetration Level

Combined months to create one annual population for each penetration level

Determined

the anticipated annually total population electric consumption and the amount NOVEC would receive in revenue from distributing electricity18Slide19

Model Methodology: Changing the Pricing Structure

Increase

the flat fee

Increase per kWh distribution ratesCharge solar customers a higher distribution rate that covers the loss in distribution revenueCharge solar customers to distribute excess solar back to NOVEC at same rate electricity is delivered to them and if costs are not covered, increase distribution rate for all customers19Slide20

Results: Two Fair Ways To Recover NOVEC’s Costs

Solar covers the decrease in distribution revenue with an increase in pricing structure

Solar

pays to distribute excess energy back to NOVECAny remaining lost revenue is equally distributed across all customers, solar and non-solarIn both methods, solar customers have a different pricing structure from non-solar customers

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Results: Option 1

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Results: Option 2

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Evaluation: Average Customer Payment Increase

Analyzed the two

options to find the average increase in solar and non-solar customer monthly distribution payments

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Evaluation: Return on Investment

Analyzed the two results to determine how much longer it would take for solar customers to see a return on investment

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Sensitivity Analysis

One of our stated assumptions was that our

solar

users are using solar panels that are 17 percent efficientFor our first sensitivity analysis we decided to see how solar users having more efficient solar panels going forward would impact our modelThe sensitivity analysis are the last of our analysis work, and we’ll be looking to expand and improve over the next few days25Slide26

Proposed Price Increase for Option 2

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Yearly Saving for Solar Users

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Recommendation

For solar penetration levels under three percent, either do not change

the pricing structure or

increase the distribution rate only for solar (Option 1)At and above 3 percent solar penetration, change the pricing structure to Option 228Slide29

Limitations

Sample data wasn’t a good representation of total

population

Received about three years worth of data for 450 non-solar customers and 38 solar customersSample population led to a distribution that used 13 percent more kilowatt hours annually than residential totals (the difference ranged from 15 percent less and 41 percent more depending on the month)Non-solar data consisted of almost 4 million entries, which made the data difficult to work with in ExcelHad to move the data to R in order to sort, filter and clean up the dataNot all teammates had the technical expertise to use R29Slide30

Future Work

Separate solar population into different groups based on solar use to explore charging each group a different rate

Explore residential customers buying larger solar panels that produce more energy

Study customers being able to store excess solar energyDetermine the impact if NOVEC isn’t required by law to buy back excess solar energyComplete analysis using data for all residential customersConvert Excel files into a database30Slide31

Acknowledgements

Robert Bisson, NOVEC’s Vice President Electric System Development

Angie

Thomas, NOVEC Manager, Forecasting and NERC Compliance & Business SystemsKevin Whyte, NOVEC Manager, Distribution EngineeringDr. Kathryn Laskey, George Mason University Professor and Capstone Project InstructorSpring 2017 SEOR Capstone Class31Slide32

Questions?

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Earned Value

BCWS – Budgeted Cost of Work Scheduled

BCWP – Budgeted Cost of Work Performed

ACWP – Actual Cost of Work PerformedCV – Cost VarianceCPI – Cost Performance IndexSV – Schedule VarianceSPI – Schedule Performance Index34Slide35

Roles and Responsibilities

John

Project Manager

Lead researcherWebsite designerLauraMethodology developerData analystLead communicator and presenterJoshR guruSensitivity analystLead data visualizer35Slide36

Monthly Distributions

Shape and scale of Weibull distribution corresponding to kilowatt hours distributed to non-solar customers for each month

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Finding Solar Kilowatt Hour Use

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Finding Solar Kilowatt Hour Use

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