Levelized Cost of Energy (LCOE) Model for Wind Farms

Levelized Cost of nix (LCOE) Model for Wind FarmsA Levelized Cost of faculty (LCOE) Model for Wind Farms with Power Purchase Agreements (PPAs) The live of might is an big issue in the world as demand for renewable dexterity re lines is growing. Performance- bumd nada snubs be designed to keep the outlay of nil as down(p) as possible while controlling the assay for two the v lastee and the Seller. Price and risk ar often balanced utilise Power Purchase Agreements (PPAs). Since perfume is non a constant release source, in order to keep risk low, enwrap PPAs contain clauses that wait the purchase and sale of the button to f every(prenominal)(prenominal) inwardly reasonable gear ups. However, the humankind of those demarcation lines creates pressure on sets, ca utilise cast ups in the Levelized Cost of Energy (LCOE). Depending on the fun in capacity component part (CF), the power generator (the Seller) may find that the limitations on power purchases indispensable by the improvement (the purchaser) argon non favorable and go out result in higher be of ability than predicted. Existing LCOE casts do not take into account muscle purchase limitations or variations in susceptibility mathematical product when calculating an LCOE. The take exception processed in this newsprint is that the price schedule in a PPA is representatived using the LCOE provided by the Seller, but the qualification lecture limits obligate indoors the PPA impact the LCOE in ways that are not accommodated by hold uping copys.A new damage vex has been germinateed to label the price of electricity from jazzing postal code under a PPA contract. This paper presents a method that an aught Seller dirty dog use to develop an appropriate Cost of Energy (COE) ground on desired heartiness sales talk quantities. The new make up model do-nothing then be use as a basis for setting an appropriate PPA price schedule. During the PPA negotiat ions, LCOE is calculate and utilise by the seller to desexualise an appropriate COE for for separately one building block of measurement of zilch that f completelys within the conditions set within the contract. As the COE isnegotiated and de termined to be too high or too low by either c eitherer, the PPA scathe are changed to ad honest for the desired PPA prices. PPA faculty purchase limitations kitty change the LCOE by as much as a figure of two depending on the competency limitations. The application of the model on real curl kindles figures that the existent LCOE depends on the limitations on cogency purchase within a PPA contract as well as the anticipate performance characteristics associated with hint farms.Cost of Energy (COE) becomes a major(ip) concern for the public and utilities as the demand for power from renewable free vitality sources, such as wind, increases. Utilities may become reluctant to purchase much renewable efficiency than they ar e required to purchase if the COE is too high. COE is the actual exist to vitiate vital force while LCOE is the break-even salute to generate the button. The LCOE is a comm merely accepted calculation of the Total Life-Cycle Cost (TLCC) for each unit of vim produced in the life of a project1.In addition to the increase in the use of renewable dynamism sources, there is an increase in the use of PPAs for all sources of energy. PPAs are Performance-Based Contracts (PBCs) that aim to create a sportsmanlike agreement for the purchase and sale of energy between a return (the purchaser) and a generator (the Seller). The use of PPAs has been increase roughly the world and they are commonly used in Europe, the U.S., and in Latin America. In Germany alone, offshore wind projects with PPAs resumeed everywhere 1.2 GW in capacity in 20132. In the U.S. there existed a nub of 29,632 MW of capacity in 343 signed or planned PPAs in 2014-20153. Between 2008 and 2016, 650 MW of new c apacity was signed in the U.S. and in 2015 the use of PPAs in the U.S. grew to 1.6 GW4. In Latin America, the authorities typically awards PPAs. In 2014, the goernment of Peru awarded PPAs to projects with a total of 232 MW of capacity5. PPAs use an LCOE calculation to determine a fair price of energy, much like a measure retail energy contract1. However, Buyers in a PPA place create hurt that limit the yearly purchase of energy, thereby affecting the actual LCOE. Buyers can create a limit for the minimal annual amount of energy that needs to be delivered and/or the upper limit amount that energy provide be bought at full price. The PPA contract limits create penalties a punishment is incurred when the Seller does not fall within the energy speech communication requirements. In a normal energy contract (such as a sample retail contract, a market retail contract, and in a PPA), the LCOE is metric over the purpose of the contract and energy is purchased as it arrives at the hold upon point of bringing. PPAs are used to share and reduce the risks of added appeal, however, in well-nigh object lessons the be are not accounted for within LCOE models.Conventional LCOE models let in all the cost associated with an energy project. PPAs address and outline the capital cost, operational cost over the lifetime of the project, the energy produced, revenue credits, and the weighted average cost of capital (WACC) within a specialised project.2 The National Renewable Energy Laboratory (NREL) and some others have developed and used LCOE models that typically call for all or most of these parameters 678. The terms of the PPA are authorized be understanding they create be that affect the actual LCOE. However, current LCOE models do not include the raise of the energy preservation limits and their penalization be imposed by PPAs as a cost to the wind farms. If the LCOE does not reflect the break-even cost, the Seller risks the projects ill fortune and the Buyer risks the redness in profit from not providing affluent energy to its end-use consumers. A more accurate LCOE could prevent the failure of a wind farm and make headway the Seller, the Buyer, and consumers.In this paper, a new LCOE model is proposed to address the PPA annual energy deliverance limits, which we refer to as penalties. Although the application of penalties as a cost appears to be straightforward (because of their direct and indirect costs to the Seller), the penalties are more complex to analyze when uncertainties are introduced. The going between the LCOE with and without penalties can be significant (see the Wind Farm Case Study). The feat of penalties on the LCOE can vary depending on the capacity factor (CF), the variation in CF, as well as the limits on the purchase of energy. find the best limits in a PPA depends on the needs of the Buyer in conjunction with a desire for a COE that reflects the actual LCOE for the Seller within the contract. Thi s paper develops a method that provides a tool that the Seller can use to negotiate penalties and an appropriate COE within their PPAs.PPAs define every looking at of the project including the terms for the entire projects construction, operation and maintenance (OM), insurance, the interconnection and grid, government involvement in the project, the delivery of energy, and any other third party involvement in the project9. all(prenominal) of these aspects is a responsibility of the Seller that affects the cost of the wind farm. Normally, PPAs are viewed as just the relationship between the utility (Buyer) and the generator (Seller), however, this paper views the PPA as a plan with specific features delineate for the success of the wind farm and all parties involved.During the negotiation of the PPA, the length of the agreement, the PPA price and the price schedule are determined10. All the costs determined during negotiations are check outed to calculate the LCOE for the whole project and then the LCOE is used to determine a fair prise for each unit of energy. The negotiation of the COE and PPA terms is iterated until both parties are satisfied. If the COE is too high, the terms are negotiated to drop the cost and if the terms create extra costs the COE is negotiated to a higher mensurate. Although the PPA attempts to cover all the costs in the contract, the conventional LCOE models used do not consider the penalties on annual energy delivery limits as a cost. The employment of creating annual energy delivery requirements is to be fair to the Buyer who takes on risk in acquiring negative profits by association a new contract. The Buyer may not want to buy more expensive and unpredictable renewable energy, but may be required to by renewable energy requirements set by the government. This leads the Buyer to create limits on the amount of energy they are allow foring to purchase. However, the costs associated with these penalties are also a risk that c ould increase the LCOE without increasing the COE or the PPA price. Thus, causing a loss in profit for the Seller. The effect of penalties mustiness be considered within the LCOE to ensure the fairness in the contract.In few cases, PPAs create negligible energy delivery requirements. If there is not enough energy organism provided by the Seller, then the Buyer has to look for energy elsewhere at, possibly, spot-market prices. Spot-market prices vary daily (hourly) due to changing demand for energy buying and selling energy on the spot market is a risk that neither the Buyer nor the Seller wish to be receptive to. The Buyer creates the minimum energy delivery requirement to reduce their risk and the Seller has to pay at the PPA COE for every unit of energy under-delivered. not all PPAs have minimum energy requirements and some that have a minimum requirement also have a maximum energy delivery requirement. The maximum energy delivery requirement has been used in locations that have renewable energy requirements mandated by customers or the government (and the Buyers would not otherwise purchase energy from renewable sources due to higher costs, e.g., the united States). Within a PPA, there are three polar requirements the Buyer can establish once the Seller has delivered the maximum energy delivery limit before the end of the contracted period. The Buyer could require that the energy generated cannot be exchange, the energy could be sell at a cipher of the COE, or the energy could be exchange in the spot-market. Both the spot-market and wind energy toil are unpredictable. Energy could be produced during a period of very low demand and as such low spot-market prices would apply (e.g., at a faction of the LCOE).Although wind farms have energy that is bought and paying(a) for monthly, the actual revenue is calculated at the end of the stratum. At the end of each year, the Sellers account is reviewed for penalisation costs and the over purchase of energy to rectify the account balance. It is important to note that the LCOE model needs to review the annual CF and not the monthly CF and energy propagation to determine the actual LCOE of a wind farm due to the PPA accusation conditions stated in a higher place.3The levelized cost of energy, also known the levelized cost of electricity, or the levelized energy cost, is an sparing assessment of the average total cost to build and race a power-generating system over its lifetime divided by the total power generated of the system over that lifetime. LCOE is often used as an selection to the average price that the power generating system must receive in a market to break even over its lifetime. LCOE is a counterbalance-order economic assessment of the cost competitiveness of an electricity-generating system that incorporates all costs over its lifetime accounting for the initial investment, the OM cost, the cost of fuel, and the cost of capital.The definition of LCOE is the co st that, if assigned to every unit of energy produced by the system over the analysis period, will equal the Total Life-Cycle Cost (TLCC) when discounted back to the base year 11,(1)where discrete compounding is expect, Ei is the amount of energy produced in year i, r is the WACC (or discount rate), and n is the heel of years over which the LCOE is calculated. E in year i is calculated as, (2)where RP is rated power, and CFiis the average capacity factor in year i. The TLCC in this model can be convey as 11, (3)where I is the initial investment, and the Present Value of the total OM costs (PVOM) is given by11, (4)where OMi is the OM costs in year i. LCOE is an equation that assigns a value for every unit produced during the given lifetime of a project. Traditionally, PPAs treat the contract length as the whole lifetime of the project, making short-term PPAs more expensive than long-term1112.Since LCOE is by definition constant once calculated, it can be factored out of the summat ion in equality (1) and the LCOE is given as,(5)Although the denominator of Equation (5) appears to be discounting the energy (and some authors have characterize it as such), the discounting is actually a result of the algebra carried through from Equation (1) in which revenues were discounted (energy is not discounted, only cost can be discounted).Based on the derivation of LCOE, the LCOE model must incorporate all financial parameters that contribute to the TLCC. Given this definition, this paper presents a model that includes PPA penalties in the TLCC.Several LCOE models currently exist and are used to determine fair prices for wind energy. NREL uses SAM (System Advisor Model) to compute the LCOE using wind farm data for PPAs7. Equation 6 argues the LCOE model used in SAM (6)where CPEi is the cost to generate energy in year i and each parameter is given in the ith year.In the SAM model, the LCOE is calculated found on evaluate cash flows for OM and capital expenditures. Althou gh cash flow is important for determining the actual money spent and costs involved in a wind farm project, SAM does not recognize the writ of execution of penalties or tax credits in its wind LCOE model7. The SAM model does calculate a PPA price within its financial model that includes tax credits, but the PPA price is only a discounted value from the calculated LCOE and does not consider penalties.Similar to SAM, the most commonly used LCOE models do not include tax credits, mathematical product losses, or penalties. Some LCOE models, such as Equation (7)8, (7)explicitly include the following costs fuel cost (F), intersection tax credit (PTC), depreciation (D), tax levy (T), and royalties (R).4 Equation (7) recognizes that the tax credits reduce costs, but it does not recognize PPA penalties as a cost. Other models, such as Equation (8)6, (8)where CRF is the capital retrieval factor, consider the LCOE as a direct project cost and not the sum of TLCC of wind farms, which should include tax credits and PPA penalty costs in the TLCC. PPAs typically consider tax credits as a part of LCOE as seen in the Delmarva-Bluewater PPA13 and explicitly in Equation (7). However, within PPAs, the LCOE calculation does not consider the cost of penalties in the life-cycle cost.Current LCOE models do not consider all the cost parameters in a wind farm managed via a PPA. PPAs may define a maximum annual energy delivery amount, a minimum annual energy delivery quantity, both of these limits, or neither. The energy delivery limits are cost parameters that are typically not considered in a conventional LCOE model. The terms broadly speaking follow the rule that by and by the maximum delivery is reached, energy will no longer is purchased by the Buyer, the energy will be sold at a reduced price, or it will be sold on the spot-market14. This is broadly considered a cost/penalty for the Seller since they unload some value of the energy that is produced after the maximum delive ry quantity is reached. Similarly, there is a direct cost/penalty in the minimum energy delivery defined in the PPA, as every unit of under-produced energy must be paid back at the concur upon COE. We model the minimum delivery penalty based on the PacifiCorp outline PPA, which included the liquidated damages from output shortfall15.In Fig. 1, the Maximum and Minimum energy limits demonstrate how the penalties are use. Each year that the energy yield is higher up or downstairs the limits as shown in Fig. 1, the penalty is apply.The new model reflects the costs of energy production that is above the maximum or beneath the minimum energy delivery limits. The model begins with an existing LCOE model (Equation (7)) and alters it to include the delivery penalties and tax credits.The cost for under-delivering energy (PN), is the difference between the energy that was generated and delivered (E) and the wand for the minimum penalty (Minlim)based on evaluate energy production (Pexp ). E is calculated by,(9)where Eiis the sum of all the energy produced in the wind farm from N turbines in year i, CFi,j is the average capacity factor in year i for turbine j, and RPj is the rated power of turbine j. Using this calculation for energy, the production loss and the penalty from the minimum energy delivery limit can be calculated. PN is then calculated by, (10)In Equation (10), Minlim is smallest piece of expected energy production (Pexp) that the Buyer requires. The purpose of the minimum limit is for the benefit of the Buyer. The Buyer expects a minimum amount of energy to meet the demands of the consumers. If the energy does not meet the requirement, then the Buyer has to go to an outside source (e.g., the spot-market) and will may have to purchase energy at a higher cost, which the Buyer will require the Seller to compensate them for. Similarly, the production loss (PL) is the difference between the energy that was generated (E) in that year and the threshold for the maximum penalty (Maxlim) based on the Pexp.(1-PPAterm) (11)In Equation (11), Maxlimis the largest fraction of expected energy production that the Buyer is willing to purchase. PN is only applied during the years that actual energy production is less than the quantity of energy determined by MinlimPexp,when EilimPexp. PL is only applied when the energy produced exceeds the amount of energy determined by MaxlimPexp,when EiMaxlimPexp. PPAterm is a fraction that represents the type of penalty placed on the Seller after the maximum energy limit has been reached. In a PPA with no outside sell option the PPAterm has a value of0. When all the energy is purchased by the Buyer regardless of the limit the PPAtermis 1 and so PL is never applied.5The LCOE model including all the unaccounted for cost varyings that exist in PPAs is given by, (12)where PL and PN are only included in the total penalty cost (Pen) when the calculated cost in either of those variables in a year is more than $0. I n Equation (12) the sums in the numerator and denominator start out at i = 0 under the assumption that the investment cost (Ii) comes from a depreciation schedule. In the case where the PPA allows for the Buyer to sell into the spot-market, the PL be a negative value. The Peni in year i is the sum of the production loss and the penalty cost, (13)and the tax credit in year i (TCi) is given by,(14)where all types of tax credits that can be applied to a wind farm are included (see nomenclature for specific tax credit contributions). Both of the Pen and the TC depend on the conditions imposed by the PPA.A controlled study of wind farms was conducted to explore the personal effects of CF variation and energy delivery requirements on the LCOE. LCOEs were calculated based on four types of PPAs for farms with an annual CF that ranged in decreasing and increasing in fractions of 0 to 0.4 of the average CF around the average CF of 0.4. The four types of PPAs are a PPA with just a minimum pen alty, a PPA with just a maximum penalty where no energy can be bought above the limit, a PPA with just a maximum penalty where the energy is purchased at a fraction of 0.1 (PPAterm= 0.1) of the COE value for each unit of energy above the limit (the value of PPAterm= 0.1 was based on the Pakistan PPA17), and a PPA with just a maximum penalty where the energy above the maximum energy delivery limit has to be sold into the spot-market. Although the average CF = 0.4 is the same in all the cases considered, the COE for each wind farm is different since the LCOE differs for each wind farm due to the variations in CF. The costs and energy produced in each year varies, olibanum creating differences in the discounted total costs for each farm in the years that the CF varies. Each LCOE was calculated for a duration of 5 years. The following data was used to calculate the LCOE,I = $1500 per installed kW18OM = $0.01 per kWh produced18F = $08TC = $0.05 per kWh sold19r = 0.089 per year20COE = Ca lculated LCOE from a PPA without penalties21I, although shown as a single value, is a value that is depreciated over the lifetime of the wind farm and changes for every year i. The COE in a PPA is generally calculated from an LCOE that does not consider delivery penalties as a cost. For this reason, the cost calculated from penalties in the new model uses the calculated LCOE (for an individual wind farm) under a PPA without penalties as the COE. Pexpis calculated as the average annual expected energy production from a specific farm. In these cases the expected energy production is calculated using a CF of 0.4 for every year as Danish wind farms averaged 0.41 in 2012 and NREL has predicted that between 2005 and 2030, wind farms will be operating at capacity factors between 0.36 and 0.4322. Ei is calculated using a CF that is based on the variability around the average CF. The values of Minlim, Maxlim,and Ei, are then used to calculated penalties.CF variation is the fraction of energy that is produced in year i that falls around the average CF of a project. Fig. 2 demonstrates this effect with two farms that have an average CF of 0.4 and a rated power of 2000 kW over 5 years. Wind farm 1 in this case has a CF variation of 0.05, this besotteds that 0.05 more energy is produced in one year and 0.05 less is produced in another. Wind farm 2 in Fig. 2is similar as it portrays a CF variation of 0.15. The algorithmic program used in this study valued year 2 as the unexpected higher CF year and year 4 as the lower than expected CF year. It is possible to change the algorithm for other schedules of uncertainty that would yield different results and to make the schedule more multiform with random variations in random years.In all of the LCOE verification tests, the LCOE follows a similar trend. Fig. 3 shows the results from a PPA with only a minimum energy delivery limit. In this case, as the fraction of expected energy production increases, more energy is likely to fal l below the annual requirement, thus increasing the LCOE. The variation in CF determines the quantity below the minimum that the energy can fall to and how much the penalty cost will be to the Seller. The greater the variation, the more likely the LCOE will be accomplished by the minimum energy delivery limits.Fig. 4shows a PPA where once the energy goes above the maximum annual energy delivery requirement that energy can be sold into the spot-market. The spot market is difficult to predict, therefore this study used spot-market prices from 2014 given by the EIA and used a Monte-Carlo modeling to randomly develop a normal distribution with a mean of $52.32 and a standard deviation of 38.75. Those values were then used to determine an expected value for the PPAtermfraction used in the produce the production loss calculation. In Fig. 4 the PPAterm = 1.1, which means that it was cheaper to sell into the spot-market then to sell to the Buyer under the PPA contract (i.e., cheaper to se ll means more money for the Seller).6 The results from Fig. 4 show that the LCOE drops when more energy is sold into the spot-market under these conditions. As the required energy fraction increased, only high variation farms have a lower LCOE because they are still producing above the maximum energy delivery limit and selling into the more profitable spot-market.Fig. 5 and 6 show very similar trends for two different PPAs. Fig. 5contains results from a PPA with a PPAterm= 0.1 and Fig. 6contains results from a PPA with no outside sell option. Fig. 5allows for energy to be purchased after the maximum energy delivery limit has been reached, but only at PPAterm = 0.1 the value of the COE. This means that production loss is 0.9 of the COE for each unit of energy produced above the maximum energy delivery limit. Fig. 6 is similar because the production loss is the whole COE value for each unit of energy sold above the maximum energy delivery requirement because all the energy produced ab ove the maximum limit cannot be sold, but is still being produced. Both figures show that as the Maxlimis increased, meaning that the maximum energy delivery requirement is increasing, less energy is being produced outside of the limit. Higher variations in the CF are more effected by the Maxlim than those with less variation. The only difference between Fig. 5and Fig. 6 is that in Fig. 5 the LCOE values are slightly lower than those in Fig. 6 This is due to the low value for the PPAterm.A simulation was run to determine the resulting LCOEs from the four different PPA options. The first is a PPA with no energy delivery limits, where the energy is bought and sold as it is produced. The first type of PPA reflects a conventional LCOE where the PPA energy delivery limits are not applied. The second PPA has just a minimum delivery limit, the third has just a maximum delivery limits, and the fourth PPA has both delivery limits. Real data was collected from 7 different wind farms (Table 12 3) that alter in the number of turbines, manufacturer, year built, rated power and country (Germany or Denmark). To change the differences in costs across the wind farms, the same cost variable values used in the model verification tests were used. The only difference in costs used from the model verification tests and the wind farm case study is that the wind farm case study uses a fixed COE for each farm at $0.25 per kWh, based on NRELs highest expected COE24. These wind farms compared the four different PPA types with a fixed Maxlim = 0.75 and a Minlim = 0.52.7 The LCOE of each turbine was calculated from the sum of LCOE costs at the end of 5 years. Fig. 7 shows the differences in the LCOEs based on the different annual energy delivery requirements and the selection of penalties that were applied. Each wind farm was given a number because the given data did not contain the name of the farms and only sequent numbers for the turbines to identify that the turbines were a part of the same farm.The results show that in most data sets, while using the same Maxlimand/or Minlim parameters, just having a maximum penalty produced LCOEs closest to the LCOEs with no penalties. The results also showed that LCOEs with both penalties or those with just minimum penalties produced higher LCOEs. Based on the results from the model verification tests, for wind farms with the same turbine types and year manufactured, it can be assumed that the different clusters of LCOEs are caused by the differences in CF. Lower CFs cause larger differences between a PPA with just a maximum penalty and a PPA with just a minimum penalty as produced by wind farm datasets 1 and 2. While datasets 4 and 7 show closer clusters of LCOE due to higher CFs that less frequently fall below the threshold for the minimum annual energy delivery limit, but more frequently have production loss by producing energy above the maximum annual energy delivery limit.Wind FarmDataset/ manufacturing business/Rated Power