Electrical Power and Energy Systems 44 (2013) 520–529

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Electrical Power and Energy Systems

journal homepage: www.elsevier .com/locate / i jepes

Potential impacts of emission concerned policies on power system operationwith renewable energy sources

Yajvender Pal Verma a,⇑, Ashwani Kumar b

a Electrical & Electronics Engineering Department, UIET, Panjab University, Chandigarh 160 014, Indiab Department of Electrical Engineering, National Institute of Technology, Kurukshetra, India

a r t i c l e i n f o a b s t r a c t

Article history:Received 27 June 2011Received in revised form 23 November 2011Accepted 10 March 2012Available online 26 September 2012

Keywords:Emission tradingRenewable purchase obligation (RPO)Emission allowancesBilateral contract

0142-0615/$ - see front matter � 2012 Elsevier Ltd. Ahttp://dx.doi.org/10.1016/j.ijepes.2012.03.053

⇑ Corresponding author. Tel.: +91 172 2534990; faxE-mail addresses: yajvender_verma@yahoo.com (Y

co.in (A. Kumar).

Electricity sector is considered as major source of green house gas emission. A huge opportunity existswithin this sector to cut down the emission and contribute significantly to mitigate the climate change.The Emission Trading Schemes (ETSs) and inception of renewable energy sources (RESs) into the gener-ation mix contribute to the reduction of emission and impact electricity market operation. This paperinvestigates the impact of emission concerned policies, such as: (a) fixed emission quota; (b) cap andtrade; and (c) bilateral contract commitments; on the operation of power system. The renewable supportmechanisms, such as renewable purchase obligation (RPO) and feed-in-tariff are incorporated so as toaccount the relative costs of cleaner and renewable generation technologies. Each generator is allocatedcertain amount of emission allowances, which they can use to cover emission during energy generation.The electricity and emission prices are obtained from the interaction of carbon and energy market. It isobserved that, the renewable support mechanisms affect the generating and emission trading schedule ofindependent power producers (IPPs). They help them meet their emission targets and increase overallwelfare. A balance between the emission regulation and renewable support mechanisms is essential,otherwise they make each others effect redundant. The performance of the proposed model is demon-strated by its implementation on a five generators system.

� 2012 Elsevier Ltd. All rights reserved.

1. Introduction

Global climate change is the greatest environmental concernworldwide. The most important and critical issue is to cut downthe level of emission of greenhouse gases (GHGs) by adopting differ-ent measures limiting harm to the environment. Among various ini-tiatives taken, the United Nations Framework Convention onClimate Change (UNFCCC) aims at stabilizing carbon dioxide emis-sions at sustainable level (1990 levels). The Kyoto Protocol puts leg-ally binding emission level on Annex B countries. It provides marketbased mechanisms as cost effective ways of doing that. These mech-anisms are: (a) Clean Development Mechanism (CDM); (b) JointImplementation (JI); and (c) emission trading. The Clean Develop-ment Mechanism (CDM), as a market mechanism allows emis-sion-reduction projects in developing countries to earn certifiedemission reduction (CER) credits, each equivalent to 1 tonne of car-bon dioxide. These CERs can be traded and sold, and used by indus-trialized countries to meet a part of their emission reduction targetsunder the Kyoto Protocol. It is argued that the mechanism stimu-lates sustainable development and emission reductions, while

ll rights reserved.

: +91 172 2547986..P. Verma), ashwa_ks@yahoo.

giving industrialized countries some flexibility in how they meettheir emission reduction limitation targets. Under JI, firms caninvestment in any emission reduction project based in any industri-alized country. Thus, the firm investing in such project can earnadditional emission allowances. In emission trading, the countryputs limit on carbon allowances and these allowances can be eitherused or traded in the emission market. The specified amount ofemission allowances are further allocated to different installationsand generators. The main advantage of this mechanism is to reducethe cost of emission reductions by allowing those installations withlower abatement costs to sell the allowances to the rest of installa-tions [1,2].

Electricity supply industry worldwide has been identified as amajor source of greenhouse gas emissions. In Europe, electricpower generation accounts for one-third of the CO2 emission; inNetherlands this is more than 50% of the sectors under carbonemission trading (CET). In India, more than 45% generation of emis-sion is from electric power sector. A huge opportunity exists withinthis sector to cut down the emission and contribute significantly tomitigate the climate change [3]. Consequently, many countrieshave started implementing ETS to reduce the emission. Though,emission trading is the least cost alternative to reduce emission,but there are reasons to incorporate other measures as well. TheEmission Trading Schemes and support mechanisms for renewable

Y.P. Verma, A. Kumar / Electrical Power and Energy Systems 44 (2013) 520–529 521

contribute to the reduction of emission and impact the electricitymarket operation. Thus, while framing policies it is important toconsider interaction among electricity market, carbon market,and renewable market [4]. The ‘20–20–20’ goals postulate a reduc-tion of GHGs of 20%, a share of RESs of 20%, and an increase of en-ergy efficiency of 20% by 2020. In [5] carbon market design forpower market is presented for the sustainable growth of powerindustry, with relevant policy recommendations. The analysis iscarried out for setting up of carbon trading market consideringallocation of carbon emission rights, carbon pricing mechanism,platform for carbon emission trading, and scarcity of environmen-tal resources. A model for generation expansion planning is pro-posed with the multiple objectives of reduction in investmentand operational costs, along with minimization of GHGs emissionfrom power generation plants, considering carbon abatement pol-icies under CDM and ETS [6].

In [7], the potential impacts of CET on China’s electricity sectorare presented, which internalized environmental cost and influ-enced relative cost of different power generation technologiesthrough carbon prices. The effect of CET on the power sector isinvestigated using different allowance allocation options. Theemission based allocation helps in higher electricity and carbonprices than output based allocation which encourages producersto be environment friendly. Thus, allocation of emission allow-ances for electric power sector is important to reduce emission.The allocation of emission allowances is dependent upon emissionreduction targets and cost of generation technologies commer-cially available [8]. Different countries adopt different methods ofemission allocation to generators in power sector. The emissionquota may change the decisions of power producers and as a resultgeneration schedule and power output. Hence, emission con-strained unit commitment (UC) problem requires a medium-termscheduling. An estimation of the daily or weekly allowances ofeach unit is obtained by means of annual allowances [9]. The emis-sion allowance quota (selling and purchasing) and the electricityprice variation influence the market operation significantly. Thesame has been investigated for combined pool and bilateral mar-kets with emission trading. The power producers are bound tomeet bilateral contract obligations without violating emission con-straints. This has a significant effect on producers’ decisions andresulting generation scheduling [10].

Economic load dispatch problem is solved under three differentemission reduction policy environments (carbon tax, CO2 quota,and CO2 cap and trade). The solution provides the generator’s re-sponse to complexities involved in implementation of these poli-cies [11,12]. Fossil fuelled power plants posing different emissionlevels should be considered in a way, what decide their generationdecision such as emission cap, and carbon prices. The effects ofemission constraints and ETS on generation scheduling and marketclearing results are studied in [13]. Generation scheduling problemwhich considers fuel and emission constraints along with marketprices, load and reserve pattern is solved using hybrid of Lagrang-ian relaxation and evolutionary programming in [14]. Another ap-proach based on hybrid genetic algorithm-ant colony optimizationis applied to obtain generation schedule of power producers withmaximum profit by solving unit commitment problem consideringprices of emission allowances (sale/purchase) [15]. Along withemission concerned policies, addition of the renewables in the gen-eration mix have very significant role in the operation of a gener-ator and electricity market as a whole. Among renewable sourcesof energy, wind is one of the most promising technologies. It hasalready been in use for a significant period of time and, comparedto other forms of alternative energy resources, has the greatest po-tential to reduce the conventional generation. In addition, beingcleaner and cheaper source of energy, it can displace emission toa great extent. Hence, impact of wind integration on system

operation under these policies need to be studied. It helps in fram-ing green energy government policies that recognize the contribu-tion of renewable energy (RE) for the reduction of national orregional carbon emission [16].

Renewable support mechanisms should be able to support theinvestments in renewable energy sector. This is done by givingspecial benefits to the renewable power producers such as feed-in-tariffs, tradable green certificates and tax rebates. The greenpower producers can sell the electricity to the grid and receive cor-responding numbers of green certificates. These certificates arefinancial assets and are tradable. Thus, the price obtainable topower producers will be sum of market-based selling prices forphysical power and green certificates. A comparative analysis is gi-ven between the benefits provided by CO2 emission reduction cer-tificates with other payment schemes like feed in tariff, tax rebates,etc., offered to wind power investors. The prices of carbon can re-place the existing support for wind, if they adequately capture itsbenefits. The thermal producers’ supply of power reacts positivelyto power prices and negatively to emission prices. However,renewable based power supply reacts positively to increase inemission prices. Thus, the share of renewables can be increasedby issuing green certificates and emission permits to renewablepower producers [17,18]. In India, in order to promote investmentin renewable energy sector and increase their share in the genera-tion mix, renewable purchase obligation (RPO) and feed-in-tariffhave been introduced. Each state has to generate certain percent-age of power from renewable energy sources depending upon theirRPO targets. Renewable Energy Certificates (RECs) are issued togreen power producers and the states which do not have sufficientpotential of renewable sources can purchase power from thepower producers who have obtained RECs [19,20].

This paper assesses the impact of interaction of emission trad-ing with different renewable support mechanisms on the operationof the power system. A mathematical model is proposed whichincorporates conventional and renewable generation technologies.The operation of power system is studied under different policiessuch as: (a) fixed carbon quota; (b) cap-and-trade; and (c) bilateralcommitment of IPPs. Under fixed quota, the trading of emissionallowances is not considered and renewables are introduced tomeet the emission targets of IPPs. In cap-and-trade, the IPPs areunder renewable purchase obligation with fixed quota of emissionallowances allocated to them. The IPPs plan their generation andtrading schedule considering these restrictions, and maximizetheir profit. The renewable purchase obligation and feed-in-tariffare the support mechanisms for renewable energy sources. TheIPPs meet their obligation under RPO by combination of windand pumped storage (PS) units.

The rest of the paper is structured as follows: in Section 2 mod-eling of emission function is presented; then, emission allocationand pricing, which is very important in trading, are described inSection 3. The mathematical formulations of the model are pre-sented in Section 4. Case studies, results and discussions are shownin Section 5; finally, conclusions are given in Section 6.

2. Emission function modeling

Types of fuels used by generating units decide the amount ofemission permit required for per kW h power generation. IPPs par-ticipate in energy and carbon market as buyers or as sellers, whichyield them higher revenue. The generation scheduling affects car-bon emission, and the profit earned by power producers in a gen-eration mix of conventional units and renewable. The derivation ofthe emissions function is given in [10] and is presented here. Theamount of fuel consumed for a particular value of CO2 emissionsis expressed based on the following incremental heat rate or in-put/output (I/O) characteristics,

522 Y.P. Verma, A. Kumar / Electrical Power and Energy Systems 44 (2013) 520–529

HiðPiðtÞÞ ¼ ki1 þ ki2PiðtÞ þ ki3P2i ðtÞ ð1Þ

Therefore, the emission functions EmCi(Pi(t)) of generator i can bedefined as [22]:

EmCiðPiðtÞÞ ¼ Eei ki1 þ ki2PiðtÞ þ ki3P2i ðtÞ

� �ð2Þ

where ki1, ki2 and ki3 are the heat rate coefficients and Eei is an emis-sion coefficient for generator i. As the value of coefficient Eei

depends on a type of a generating unit, as well as on a quality ofthe used fuel, its value needs to be estimated or calculated in away that accounts for these variations.

A practical way to determine the value of this emission coeffi-cient Eei is given in [23]. The combustion emission for generator iis calculated as:

ERiðtÞ ¼ fueliðtÞ�net caloric value�i emission factor�i oxidation factori

ð3Þ

The above CO2 emissions calculation is based on a measurement ofthe amount of fuel (in t or Nm3) consumed by generating unit i dur-ing a monitoring period. Net calorific value and emission factor ofgenerator i depend on the particular type of a fuel used, and haveto be measured regularly. Emission factor is based on a carbon con-tent of a fuel, and is expressed as tCO2/TJ, while net calorific value isexpressed in TJ/t or TJ/m3. Finally, oxidation factori accounts for thefact that a portion of carbon content remains unburned or partlyoxidized, and is therefore, not emitted into the atmosphere. Now,emission coefficient Eei used in (2) can be calculated by matchingvalue of emissions function (2) and reported values defined by(3), such that:

Eei ¼EmCiðPiðtÞÞ

ki1 þ ki2PiðtÞ þ ki3P2i ðtÞ¼ ERiðtÞ

ki1 þ ki2PiðtÞ þ ki3P2i ðtÞ

ð4Þ

The above value can then be used by a generator to define emissionfunction (2).

The fuel cost function, FCi(Pi(t)) of generator i is also related tothe incremental heat rate of (1), such that,

FCiðPiðtÞÞ ¼ Pftðki1 þ ki2PiðtÞ þ ki3P2i ðtÞÞ ð5Þ

where Pfi is the fuel price. In that case, each generator will beallowed to submit its offer function, and only one parameter, overallemission coefficient Ei will be used to calculate the emissions func-tion (2),

EmCiðPiðtÞÞ ¼ Eeiðki1 þ ki2PiðtÞ þ ki3P2i ðtÞÞ ¼ Eei

FCi

Pft¼ Ei � FCi ð6Þ

In this paper, this approach is used so that coefficients of the emis-sion function, EmCi(Pi(t)) submitted by generator i are related to theoffer function, FCi(Pi(t)) and defined as

Ki1 ¼ci

Ei; Ki2 ¼

ai

Eiand Ki3 ¼

bi

Eið7Þ

3. Emission allocation and pricing

Allocation of emission allowances is very important componentof ETS. European Union Emission Trading Scheme (EU ETS), whichis a cap and trade system, the allowances are fixed through Na-tional Allocation Plans (NAPs). Each member state in the EuropeanUnion has to submit its NAP to the European Commission for eachphase considered. Each member must decide how many allow-ances each plant covered by ETS will receive per year of the com-pliance period. The allowances distributed to the companiescovered by the directive in the EU ETS are called European UnionAllowances (EUA). In EU ETS as well, grandfathering practice is

used for emission allocation. A very small proportion of the totalallocations are auctioned (EU member states could auction up to5% of allocations in phase 1 and up to 10% in phase 2). The totalnumber of allowances allocated is actually not much less than100% of previous emissions. Grandfathering allowances are allo-cated at ‘need’ or close to need based on previous emission levels,whereas, benchmarked allocations are determined according toagreed industry sector standards. Grandfathering is viewed asnot encouraging early action as well as rewarding polluters. Grand-fathering does not provide a transparent cost of carbon and can beseen as equivalent to a property right being given away and repre-sents a transfer of wealth from the community to polluters. Emis-sion costs are real costs in the sense that they have a direct impacton the welfare of the ecosystem, for example, they impact onhealth, materials and crops [8].

3.1. Allocation of emission allowances

The allowances allocation is one of the challenging tasks and acritical factor while designing Emission Trading Schemes. There arethree different methods through which emission allowances areallocated. The most common exogenous criterion is grandfather-ing. In this method, nearly all allowances are allocated for freedepending upon previous levels of emission. The previous year’semission proportion is the standard for setting emission quotafor following year. The emission quota allocated to a particularproducer is decided as follows [7]:

Em maxiðtÞ ¼EmCiðt � 1ÞP

iEmCiðt � 1Þ � Em maxðtÞ � c ð8Þ

where EmCi(t � 1) is generator i carbon emission in period (t � 1);Em max (t) is total carbon quota in period t; and c is the decreasein the rate of the quota.

Another method of emission allocation is based on output ofgenerator. The supply proportional to previous year’s electricityis used as standard for setting emission quotas for the followingyear, given as:

Em maxiðtÞ ¼Piðt � 1ÞP

iPiðt � 1Þ � Em maxðtÞ � c ð9Þ

where Pi(t � 1) is generator i’s generation in period (t � 1).In power industry, the most commonly used method is based on

the generation performance standard, in which allowances areallocated freely to all generators according to generation amountin the year concerned. This paper assumes this approach for theallocation of emission allowances for different generating units.

The third method of allocation is auctioning, in which permitsare allocated starting from highest bidders. Auctioning providestransparency in carbon prices, as well as a stable market dependingupon how often the auctions are held, and how much allowancesare auctioned each time. Generally, economists favor auctions,while firms tend to favor free allocations. These issues are oftenhotly contested and politicized. This makes it not an easy task eventhough technically it might not be difficult to implement any ofthese schemes. The carbon emissions once allocated become valu-able and can impact power producers generation, economy andinvestment for the development of renewable and thereby frame-work of ETS. Thus, the allocation of emission permits becomes verysignificant. Different possibilities can also be tried, such as, allocat-ing few allowances for free, and then auction can be adopted. Theexperiences based on these strategies play a vital role in selectingappropriate method for allocation of emission allowances inemission market.

Y.P. Verma, A. Kumar / Electrical Power and Energy Systems 44 (2013) 520–529 523

3.2. Pricing mechanism of carbon emission

From past few years, the concept of mandatory renewable tar-gets is being adopted by many countries so as to increase the shareof cleaner non conventional energy sources. One of the largest driv-ers of cleaner renewable energy sources is introduction of renew-able portfolio standards in US. In India as well, RPO has beenintroduced in which each state has to obtain certain percentageof electricity generation from the renewable. The states set theirtargets for electricity generation through RE and frame policiesso as to increase investment for the development of RE sources.The pricing of carbon is very crucial in this context, as implicationon RE sources will be slightly different with emission trading. Trad-ing could provide credible transaction with a carbon price that ishigh enough to drive energy structural change. Switching a fractionof generation from fossil fuels to RE technologies such as wind, hy-dro, biomass, solar, and nuclear, would be helpful in reducing car-bon emission however; the cost of establishing these technologiesis on higher side. Thus, pricing of carbon emission must be decidedjudicially so as to create incentives for the investors, electricityproducers, and consumers to make power sources mix, modes ofproduction and consumption optimum in terms of economy as awhole. The carbon price thus, must be kept higher than the indus-try’s lowest cost of reducing emission and lower than the highestcost of reducing emission. Moreover, it should play the role ofreduction incentives. In this model, the prices of carbon allowancesallocated for trading have been taken as given input which discour-ages emission. However, modeling for the pricing can be done or itcan be decided on the basis of auction in carbon market.

4. Mathematical formulation

The proposed model solves the power system optimizationproblem under three different policy scenarios: (i) CO2 quotabased; (ii) Cap and trade with RPO; and (iii) IPPs having bilateralcontract commitments. Each generator behaves as an IPP and sche-dule of their units is decided such that IPPs maximize their profitover a defined time horizon. The allocation of emission allowancesis based on the output of individual generating unit of IPPs. Themathematical models under three different policy environmentsare given below:

4.1. Carbon dioxide quota-based operation

Under this policy, IPPs are allotted maximum amount of carbonemission for a fixed amount of time, usually a year. The IPPs sche-dule their units and maximize their profit and adhere to the max-imum emission and generation limits. The consumption ofelectricity generated from the renewable is encouraged by provid-ing special incentives to the electricity generated from renewablesin terms of feed-in-tariff. The prices of power for renewables andconventional units of IPPs are obtained from the electricity marketand considered as given inputs, which remain fixed over entireoperating time. The objective function is to maximize profit:

Max ProfitiðPi;t; PREi;tÞ ¼ Revenuei � Operating � Costi ð10Þ

where

Revenuei ¼XT

t

Ui;t � Pi;t � EPi;t þ PRt � REPt ð11Þ

Costi ¼X

Ui;t � OCi;t þ STCi;t ð12Þ

Subject to the following constraints

� Power balance equation

XN

i

ðUi;t � ðPi;tÞ þ PREi;tÞ ¼ PLt ð13Þ

� Generation limits

Ui;t � Pmini;t 6 Pi;t 6 Ui;t � Pmaxi;t ð14Þ

� Ramp constraints

DRi 6 Pi;t � Pi;t�1 6 URi ð15Þ

� Reserve requirement

XN

i

Ui;t � Pmaxi � PLt þ Rest ð16Þ

� Emission constraint

XT

t

EmCi;t 6 Emmaxi ð17Þ

The maximum permissible emission allowance is allotted by (9).The IPPs tend to schedule their generators considering two factors;maximum generation limits, and maximum emission allowances.Wind and pumped storage (PS) units provide the electricity fromrenewable energy sources to the power producers. These have beendescribed in the following section.

4.2. Cap and trade with renewable purchase obligation

The EU ETS is a Cap and Trade system, where total emissions arefixed or ’capped’ and excess allowances can be traded. The IPPs areallocated limited emission allowances for a fixed duration. The IPPsuse these emission allowances to meet their electricity generationrequirement and trade the rest in carbon market. Renewable pur-chase obligation on each power producer and feed-in-tariff encour-ages the use of electricity from renewables sources. It eases theburden on conventional generating units and helps power produc-ers meet their emission targets. In this model, the objective is tomaximize profit by selling power in electricity market and tradingemission allowances in carbon market. The price projections forthe electricity generation from conventional sources EPi,t, renew-able sources REPi,t and for emissions (sale or purchase CPSi, CPBi)have been assumed to be obtained from the electricity marketand carbon market respectively. The decision variables are not onlypower generation at each time step, but also the amount of allow-ances sold or purchased in the emission market. The maximumamount of allowances available for trading can be calculated from(9). At the end of the period, the physically emitted allowances andallowances traded must match the initial allocated emission allow-ances. The optimization problem is formulated mathematically asdescribed below:

Maximize profit, i.e. revenue earned by selling electricity andemission allowances minus operating cost, start up cost and costsassociated with the purchase of emission allowances, i.e.,

Max ProfitiðPi;t ; PRt; ESi;t ; EBi;tÞ ¼ Revenuei � Costi ð18Þ

where

Revenuei ¼XT

t

ðUi;t � Pi;t � EPi;t þ PREi;t � REPt þ ESi;t � CPSiÞ ð19Þ

Costi ¼XðUi;t � OCðPi;tÞ þ STCi;t þ EBi;t � CPBiÞ ð20Þ

The following constraints have been used in addition to the con-straints (13)–(17).

� RPO constraints

524 Y.P. Verma, A. Kumar / Electrical Power and Energy Systems 44 (2013) 520–529

XT

t

PREi;t � r% �XT

t

Pi;t � Ui;t ð21Þ

XN

i

PREi;t ¼ Pwt þ Pugt � Pupt ð22Þ

� Emission constraints:XT

t

ðEmCi;t þ ESi;t � EBi;tÞ 6 Emmaxi ð23Þ

0 6 ESi;t 6 Uesi;t � ESmaxi;t ð24Þ

0 6 EBi;t 6 Uebi;t � EBmaxi;t ð25Þ

Uesi;t þ Uebi;t 6 1 ð26Þ

where

Ui;t and Uesi;t ¼ f0;1g ; i ¼ 1;2; . . . ;N; and t ¼ 1;2; . . . ; T ð27Þ

The IPPs meet their RPO from the power obtained by the combina-tion of wind and pump storage units. Since wind power is stochasticin nature, PS unit is used to cater the variability of the wind power.The equations describing their behavior are given in [24] and men-tioned below:

PLtþ1 ¼ PLt þM� gp � Pupt �Pugt

gg

!ð28Þ

Pug mint 6 Pugt 6 min Pug maxt ;gg �PLt

M

� �ð29Þ

PupMin;t 6 Pupt 6 Pupmax;t ð30Þ

PLMin;t 6 PLt 6 PLmax;t ð31Þ

PLð0Þ ¼ PLo ð32Þ

PLðTÞ ¼ PLT ð33Þ

The notations used in above formulations are as follows: subscript idenote number of IPPs, t is the time period, p and g are used forpumping and generation respectively. Pi,t is the power generatedby unit i at time t; Ui,t is status of the generator; STCi,t is the startup cost; CPSi, CPBi are the carbon emission prices generators arewilling to sell or buy; Pwt is the power of wind unit at time t; Pupt

and Pugt are the power supplied by PS unit for pumping and gener-ation respectively; Pugmaxt and Pupmaxt are the maximum limit ofpower available for generation and pumping from PS unit, PLt isthe level of reservoir, PLo is the initial level of reservoir; PLT is thefinal level of reservoir; ESi,t and EBi,t are the emission allowancesfor selling and purchase; Uesi,t, and Uebi,t are the binary variablesindicating the sale or purchase of emission allowances by unit i attime t; and OC (Pi,t) is the offer curve submitted by generating unitsof power producers for electricity generation. Each generating unitsubmits following information in addition to offer curve:

� emission function EmCi(Pi(t)), that gives a relationship betweenits power output and amount of CO2;� amount of allowances for sale ESmaxi;t and purchase EBmaxi;t

during operating period t, and total emission allowancesEmmaxi for overall scheduling period T;� carbon emission prices generator is willing to sell or buy;� Renewable purchase obligation on it, PREi,t.

Under RPO, each IPP has to generate certain percentage (r%) oftotal generation from renewables (21), which in this case is

supplied by the combination of wind and PS unit ensuring avail-ability over entire operating horizon (24 h in this case) (22). Theemission constraints are modeled by (23)–(26). Emission limit con-straints on each generating unit are given by (24) and (25). Thegenerators are not necessarily awarded sufficient emission allow-ances to operate as they did in past. Hence, if necessary, they canbuy or sell emission allowances to meet their generation require-ment due to emission constraints. Each IPP is allowed to either sellor purchase allowances at a particular time interval, but not bothsimultaneously as defined by (26). The pumped storage modelingis described by (28)–(33). The first equation describes the reservoirlevel, second, third and fourth put the constraints on generation,pumping and reservoir level respectively. The combination of windand PS unit helps to counter wind power variability. It is assumedthat each IPP has invested in wind power and PS technology tomeet its RPO requirement and power available from it will be usedby all. The IPPs choice to use renewable energy above RPO dependsupon feed-in-tariff and prices of emission allowances. The sale andpurchase of allowances take place in emission market. Each IPP cansubmit different selling or buying prices for each hour. Hence, ithas more control on a decision, when it wishes to use these allow-ances. Thus, the generation of each unit is decided by factors suchas emission limit and prices. The operating cost is given by the qua-dratic equation given below:

OCðPi;tÞ ¼ ci þ ai � Pi;t þ bi � P2i;t ð34Þ

where ai, bi, ci, are the cost coefficients of thermal unit i. The start-up cost of the thermal units depends upon the time the unit hasbeen off prior to start up. The start-up cost is given by the followingexponential cost curve:

STCi ¼ ri þ di 1� exp�Toff ;i

si

� �� �ð35Þ

where ri, di are the hot and cold start-up costs respectively, si is theunit cooling time constant and Toff,i is the time for which unit hadbeen off.

4.3. Bilateral contract commitments of IPPS with ETS

The power generated by each generating unit and amount ofrenewable energy used depends upon number of factors like,prices offered in electricity market, emission allowances available,etc., as discussed in Section 4.2. The power producers can also optfor bilateral contracts if it offers good revenue to them. Thus, themodel is modified to incorporate the bilateral contracts of differentIPPs if any. The following equation has been used to implementbilateral contract agreement,

Pi;t ¼ Pgpi;t þ Pgbi;t ð36Þ

where Pgpi,t is the power generated in pool and Pgbi,t is the bilateralcontract power. To ensure the commitment of power in bilateralcase the following condition is imposed, i.e.,

Pi;t � Pgbi;t � ui;t ð37Þ

The power under bilateral contact has fixed value therefore, themarket clearing solves for pool power Pgpi,t, which also includesthe loss component. The power generated by IPP under bilateralcontract is now decided on one more factor, i.e. power required tomeet bilateral commitment in addition to the factors mentionedabove. The model thus, helps IPPs plan their operating strategiesunder these varied conditions. The model objective function isdefined by (18) with system and other constraints defined by(13)–(17), (23)–(33) and (36), (37). The flow chart describes theimplementation process of the model and is shown in Fig. 1.

Obtain the data (Gen cost ,emission curves , energy prices , emission allowances prices,

emission allowances , quota etc.) for Independent Power

Producers

Is Power produced from RE by IPPs > Renewable Purchase Obligation

YesNo

Are Emission Allowances with each

IPP > Required to meet load demand

Purchase Power from RE sources having RECs

Prepare generation and emission trading schedule

to meet the load demand including Bilateral Commitment if any

Purchase Emission permits from carbon market

No

Calculate the Profit earned from selling Power in

Energy Market and sale of the surplus Emission

allowances

Yes

Fig. 1. Flow chart for implementation of model.

Y.P. Verma, A. Kumar / Electrical Power and Energy Systems 44 (2013) 520–529 525

5. Case studies

The proposed model is illustrated on a system with five thermalgenerating units, whose data are given in Appendix A. Each gener-ating unit participates in electricity market and submits offer curveand other information as discussed in Section 4.2. The coefficientsof emission functions are related to offer function and obtained asdescribed in (7). The units have ramp rate limits of 20% and thereserve has been kept 10% of the total load demand [10]. Theallowances are allocated to each generator based on their output.The allowances allocated have been approximated based on resultsobtained from output based allocation method. This ensures thatgeneration meets the total load demand and gives feasible solu-tions. The participation of renewables is encouraged by RPO andfeed-in-tariff. The competitive prices for the sale and purchase ofthe emission allowances are obtained by IPPs from carbon market.The aim is to study the effect of interaction of emission trading andrenewable energy support mechanism on generator’s strategies.The impact of renewables and emission trading on profit has beeninvestigated. The following case studies have been considered:

Case 1: CO2 quota-based operation.Case 2: Cap and trade with renewable purchase obligation.

Case 3: IPPs under bilateral contract commitment.

� More than one generators having bilateral contract commitment.� Generator with high emission sale price under bilateral contract.� Generator with fixed bilateral contract commitment.� Operation without renewable.

The case studies have been solved with CONOPT solver in GAMSand MATLAB interface [21].

5.1. Case 1: CO2 quota-based operation

In this case, limited quota of emission allowances is allocated toeach IPP. The IPPs schedule their units based on their emissionquota, renewable energy available and their market prices. In thispaper, the renewable energy is supplied by the combination ofwind power and pumped storage unit. The data used for thepumped storage unit are given in [24]. The operation of the systemis studied under two scenarios: (i) IPPs having limited emissionallowances; and (ii) IPPs with sufficient emission allowances. Theresults reveal that adding renewable in generation mix fetch highrevenue and reduces the impact of emission constraint on net prof-it. However, without renewables the dip in profit margin is large

Table 1Profit earned with and without RES for different quota of emission.

Profit in $/day

Without renewableenergy

With renewableenergy

Fixed carbon emissionquota (tonne)

87094.67 290106.634

Sufficient carbon emissionquota (tonne)

118066.282 297767.23

0 4 8 12 16 20 24-100

-80

-60

-40

-20

0

20

40

60

80

100

Time [Hrs]

Pum

ped

Gen

erat

ion

[MW

] PS GenPumped PowerWind Power

Fig. 3. Operation of renewable (PS with wind unit).

0 1 2 3 4 5 60

100020003000400050006000700080009000

10000

Gen units

Emis

sion

[ton

ne]

Emis with REEmisEmission Quota

Fig. 4. Emission used by generating units for power generation under fixedemission allowance.

526 Y.P. Verma, A. Kumar / Electrical Power and Energy Systems 44 (2013) 520–529

with limited quota operation. Hence, during system operation withlimited emission quota, role of the renewable energy sources be-comes very important. Table 1 show the profit earned under differ-ent scenarios.

The system is simulated under carbon dioxide quota policy. Thetotal allocated quota to the system is 37 K tonne/day. The quota isreduced by 10% in each simulation, but when carbon dioxide quotais targeted at reducing beyond 20%, the optimization could not re-turn a feasible solution. The reduction of 20% is possible only whenthere are renewables in the generation mix. This is a manifestationof the fact that without renewables, the present system cannotmeet an arbitrary goal of CO2 reduction. However, renewable ingeneration mix can reduce emission. Fig. 2 shows the carbon emit-ted by different units with and without renewable energy sourcesduring power system operation over an operating horizon.

The renewable energy is supplied by the combination of windand pumped storage unit. The PS unit compensates for the devia-tions of the wind power. The PS unit works as pump when windpower available is high and as generator when wind power avail-ability is low thus, putting almost negligible burden on conven-tional units during pumping of water. The operation of thepumped storage unit with available wind power is shown in Fig. 3.

With limited emission quota and no renewables in generationmix, most of the units have to use their maximum emission quotato meet load demand. Generating units 2 and 5 offer lower pricesfor sale and higher for buying emission allowances (Appendix A).Thus, they use their full quota of emission allowances for generatingpower even when power from renewables is also available Fig. 4.

This is because, selling emission allowances is not beneficial tothem as they can earn higher profit by selling power in electricitymarket by using their full emission quota for power generation.Depending upon the prevailing prices in electricity and carbonmarket, other units also decide their amount of power generationand tradable emission quota, yielding them maximum profit.

5.2. Case 2: Cap and trade with renewable purchase obligation

Under cap and trade, the emission allowances are allocated tothe generators based on output and they sell their surplus

1 2 3 4 5 60

2000

4000

6000

8000

10000

12000

Generators

Emis

sion

[ton

ne]

Emis with REEmis

Fig. 2. Reduced emission of generating units with renewable.

allowances in carbon market. The emission sale and purchaseprices have been assumed to be obtained from carbon marketand taken as given input. The prices for power generated from con-ventional and renewable are assumed $125/MW and $150/MWrespectively. The power generation from renewable is bindingand each IPP use renewable power to supply certain amount ofload demand. Net CO2 emitted by generators deceases whenrenewables are used, which help IPPs save their emission allow-ances and earn revenue by selling them in emission market asshown in Fig. 5.

The power generated by generators depends upon, carbonprices, electricity prices, emission allowances and the RPO onthem. Each unit has to abide the RPO and if needed, they can pur-chase power from renewable power producers having RenewableEnergy Certificates. They sell their allowances in the carbon marketif they have unused emission allowances. The generators are al-lowed to either purchase or sell the allowances during a particularinterval of operation. Table 2 below gives the trading schedule ofpower producing units over an operating time horizon. The pricesfor the purchase and sale of carbon allowances are decided so as todiscourage the emission and use more of renewable energy. Thegenerating units 1 and 4 purchase emission allowances for powergeneration due to their low operational costs. For them profitearned by selling power is more than the cost of emission allow-ances purchased to generate that power. The other units preferto sell the allowances over power as it is profitable to them.

The total profit earned during emission trading with the RPO is$268536.28. Table 3 shows the emissions associated with differentunits during operation of the system when PS unit’s capacity is en-hanced from 30 MW to 80 MW. The profit rises to $276720.36, andtotal emission decreases from 28355.82 tonne/day to 27920 tonne/

0 4 8 12 16 20 24200400600800

100012001400160018002000

Time [Hrs]

Emis

sion

[Ton

]

Emis With RPOEmis without RE

Fig. 5. Emission with and without renewable energy sources.

Table 2Emission trading schedule of generating units.

Unit/time Carbon emission sale Carbon emission purchase

1 000000000000000000000000 1111100000000001110000002 011111101111111111000000 0000000000000000000000003 000000111110001101000000 0000000000000000000000004 000000000000000000000000 1000000011100100000110005 000000000000000000000000 001100100000000000000000

Y.P. Verma, A. Kumar / Electrical Power and Energy Systems 44 (2013) 520–529 527

day. Thus, additions of renewable with ETS decrease the net emis-sion and demand for emission allowances. To find out the effect offeed-in-tariff on the usage of renewable, the price for power gener-ated from renewable was considered same as that of power fromconventional units, i.e. $125/MW and then enhanced to $150/MW. It is observed that the feed-in-tariff raised the renewablepower utilization by 6.8% and decreased the net CO2 emission.

Imposing a renewable quota in addition to emission reductionleads to lower emission prices. Due to high share of renewablesin electricity generation, electricity sector avoids significant emis-sion. Therefore, imposing carbon cap becomes non binding andemission prices drops. This is due to the fact that high targets ofrenewable generation leads to excess supply of emission allow-ances and IPPs prefer not to buy allowances, resulting fall in carbonprices. Since carbon cap and renewable promotion have overlap-ping goals, a balance is needed between them while implementa-tion, otherwise they will make each others effect redundant.

5.3. Case 3: IPPs under bilateral contract commitment

Under bilateral contract, the IPP agrees to supply power on anegotiated price for a limited duration. IPP may even purchaseemission allowances to supply the contracted load demand as con-tract power is sold at higher prices. However, in this case study, wehave considered the same price for contracted power as that forpool power. This definitely impacts the generation and tradingschedule of IPPs. To account for physical connotation of the bilat-eral commitment, an additional inequality constraint (29) is addedwith usual generation limits defined by (13) which ensures that

Table 3Emissions of different generating units with different PS unit capacities.

Emission (tonne) PS unit generating capacity of 30 MWGenerators/IPPs

Allowances Allocated 1 2 3 43000 8000 8000 4000

Allowances used 3897.5 6504.6 6667.7 5275.9Allowances sold 1495.4 1332.3Allowances bought 897.5 1275.9

total generation is always greater than or equal to the bilateralagreement. The generation and load is balanced by pool compo-nent of generation as it is decided by the system operator. The fol-lowing cases of bilateral contract commitment are studied:

5.3.1. Case a: More than one generators having bilateral contractcommitment

The system operation is studied when more than one generatorare under bilateral contract commitments. This affects the overallprofit and CO2 emitted by the generators. It depends upon theprices of emission allowances, electricity prices and price of con-tracted power. If the price for bilateral contract power is higher,good revenue is earned. Table 4 below gives emission and profitwhen different generating units are put under bilateral contractcommitments. Since the price for contracted power is same as thatof pool power, the net profit is lower. The decrease in profit is dueto cost used to procure additional emission allowances to meetcontract obligation. However, with higher prices for contractedpower the profit rises, which also increases the demand for emis-sion allowances and in turn the emission prices. Thus, based onabove factors, each power producing unit can decide whether toenter in bilateral contract agreement or not.

5.3.2. Case b: Generator with high emission sale price under bilateralcontract

In this case, a single generating unit 3 having sufficient emissionallowances and their high sale price is considered under bilateralcontract commitment. The results in Table 5 show that the profitearned decreases as unit under bilateral contract loses opportunityto sell emission allowances. In this case, unit uses most of theallowances for supplying the bilateral contract demand; those ifsold in market could have earned higher profit.

It is observed that, the unit having higher sale price for carbonallowances tends to use lesser allowances and sell the remaining inemission market. But, if bilateral contract power is high (40%), gen-erating unit needs to purchase emission allowances, and it resultsin reduction in profit. Thus, power producing unit can make a judi-cious decision whether to enter in bilateral contract or not and upto what extent under different price scenarios. The system givesinfeasible solution for bilateral contract power beyond 10%, in caserenewables are removed from generation mix. This is due to cap onemission which prevents power producers to enter in bilateral con-tract. Thus, power producers will be motivated to invest in cleanerand renewable technologies which can provide them flexibility inoperation.

5.3.3. Case c: Generator with fixed bilateral contract commitment of100 MW

In this case, generating unit 3 is assumed under a bilateral con-tract of 100 MW. The price of contracted power is same as that ofpool power price. The profit with bilateral contract commitment is$379800.3 whereas; the profit earned without bilateral commit-ment is $387571.16. This is due to higher CO2 emitted to generatepower needed to supply contracted power. Hence, low emissionallowances are left for sale with generating unit 3 as given in Table 6.

PS unit generation capacity of 80 MWGenerators/IPPs

5 1 2 3 4 55000 3000 8000 8000 4000 50006010.2 3860.3 6461 6453.8 5148.9 5996.8

1539 1546.21010.8 860.3 1148.9 996.8

Table 4Effect on emission and profit with more than one generating unit under bilateralcontract.

Generatingunits

Bilateralpower (% ofdemand)

Pool power(% of loaddemand)

Totalemission(tonne/day)

Net profitearned($/day)

Generator 3 20 80 32456.2 383558.90Gen 3 + Gen 4 20 each = 40 60 32844.6 380907.21Gen2 + Gen3 +

Gen 420 each = 60 40 33865.4 372179.67

Table 5Effect of bilateral contract commitment on unit offering high selling price foremission.

Bilateral power (%of demand)

Pool power (% ofload demand)

Total emission(tonne/day)

Net profitearned ($/day)

10 90 32174.5 387571.1620 80 32456.4 383558.9140 60 34662.3 346236.11

Table 8Emission without renewable energy sources.

Emission (tonne) Generators/IPPs

1 2 3 4 5

Allowances allocated 3000 8000 8000 4000 5000Allowances used 5661.11 8000 8925.70 8000 7668.70Allowances soldAllowances purchased 2661.11 925.70 4000 2668.70

Table 9Profit earned by power producers under different scenario.

Case Profit in $/day

With bilateral contractof 100 MW at unit 3

Without bilateralcontract

With RES 379800.364 387571.16Without RES 62885.084 76700.14

528 Y.P. Verma, A. Kumar / Electrical Power and Energy Systems 44 (2013) 520–529

The unit 3 has higher selling price for emission allowances ascompared to other units which results in reduction in profit. Unit2 has least operating cost, thus, its generation capacity is used toits maximum, but no emission allowances are purchased as the buy-ing cost is higher for unit 2. To meet load demand, additional emis-sion allowances are purchased from the carbon market and theunits 1, 4 and 5 with lesser buying prices purchase allowances.The unit 3 prefers to keep some allowances for sale, as the profitearned by selling emission allowances is large, even if other unitsare forced to generate power by buying additional allowances. Thus,it is essential to understand that for a carbon price it may be bene-ficial to purchase additional allowances than to operate expensiveunits. Table 7 gives the schedule of units for emission trading withand without bilateral commitment. Without bilateral contract, themajor decrease in purchase of emission allowances is observed inthe generating units 4 and 5 due to higher buying prices.

5.3.4. Case d: Operation without renewablesThe capital cost of renewable energy sources is high, but they

offer many advantages like, negligible carbon emission, least oper-ating cost and policy support such as RPO, and feed-in-tariff. To

Table 6Emission with and without bilateral commitment of 100 MW at unit 3.

Emission (tonne) Emission with bilateral commitmentGenerators/IPPs

Allowances Allocated 1 2 3 43000 8000 8000 4000

Allowances used 5176.1 8000 7187.8 6684.4Allowances sold 812.2Allowances bought 2176.1 2684.4

Table 7Emission trading schedule with and without bilateral commitment.

Unit/time Emission trading schedule with bilateral commitment

Carbon emission sale Carbon emission purchase

1 000000000000000000000000 10111111111101000000002 000000000000000000000000 00000000000000000000003 111111111111111111000000 00000000000000000000004 000000000000000000000000 11111111111111111111115 000000000000000000000000 0000011111100000000000

evaluate the effect of renewable, the operation of power systemis studied when there are no renewable sources available in gener-ation mix. It is found that the units having least costs are used andthe most expensive units have least preference for purchase ofemission allowances. Table 8 gives the detail of emission allow-ances used and traded by different units during system operation.The generating unit 2 with least operating cost uses full quota butdoes not purchase emission allowances as the buying cost is highfor it. Other units also follow the same strategy for the purchaseof emission allowances and their use, i.e. carbon prices and theiroperating costs.

In the absence of the renewables, the net profit earned by IPPs is62885.084 $/day when bilateral contract commitment of 100 MWis on generating unit 3. Despite bilateral commitment, the unit 3has allowances for sale. It is because that the second most expen-sive unit 3 supplies small demand only and it prefers to earn rev-enue by selling the remaining allowances in the carbon market.The remaining load is fed by the generating units with lower oper-ating cost and they are operated even if allowances have to be pur-chased to generate power to supply the load demand. The profitearned is 76700.138 $/day, when there is no bilateral contractcommitment on any of the generator. The profit earned by systemoperation is significantly high when there are renewables as givenin Table 9. The CO2 emitted by IPPs with and without renewable

Emission without bilateral commitmentGenerators/IPPs

5 1 2 3 4 55000 3000 8000 8000 4000 50005944.2 5061.2 8000 6917.6 6507.5 5687.8

1082.4944.2 2061.2 2507.5 687.8

Emission trading schedule without bilateral commitment

Carbon emission sale Carbon emission purchase

00 000000000000000000000000 11111111111000110100000000 000000000000000000000000 00000000000000000000000000 111111111111111110000000 00000000000000000000000011 000000000000000000000000 01111111111110000000000100 000000000000000000000000 000000001110100000000000

Appendix A

Gen Pmin (MW) Pmax (MW) C0 ($/h) a ($/MW h) b ($/MW2 h) a ($) b ($) s (h) CSi ($/tCO2) CBi ($/tCO2) Eei

1 25 100 22 1.5 0.0060 50 500 2 13.5 15 0.0212 50 150 20 1.7 0.0026 60 700 3 11 17 0.0803 60 200 52 1.6 0.0054 100 800 5 14 16 0.0554 50 120 62 1.5 0.0055 100 850 5 13.5 16.5 0.0555 70 200 54 1.7 0.0057 100 900 5 12.5 17 0.057

Y.P. Verma, A. Kumar / Electrical Power and Energy Systems 44 (2013) 520–529 529

are 28355.52 tonne/day and 38255.51 tonne/day respectively.Thus, renewable energy sources are not only important from envi-ronmental point of view, but also very significant in power systemoperation for increasing welfare.

6. Conclusions

In this paper, the impact of emission regulations and renewablesupport policies like renewable purchase obligation and feed-in-tariff on power system operation is analyzed. The model incorpo-rates bottom-up feature for electricity generation, and emissionreduction target for electricity, together with 10% quota for elec-tricity generation from renewable is imposed. Emission tradingmainly has an impact on electricity prices and thus, indirect effecton consumption and investment. Emissions trading in general in-crease the prices of electricity, which in turns leads to less electric-ity consumption. In long run it leads to an investment shift in favorof renewable energy sources. Most of the countries are investing inrenewable energy technology to meet emission target and increasethe share of power from renewable energy sources. But large cap-ital cost discourages the investors to invest in renewable energysector. Thus, government policies like renewable purchase obliga-tion and feed-in-tariff to the power generation from renewable canwork as catalyst for it.

It can be concluded that effect of carbon price is decreased byrenewable support mechanisms like renewable purchase obliga-tion and feed-in-tariff. This is due to decrease in demand for carbonemission allowances with increased share of renewables. However,bilateral contract commitments of IPPs keep the demand for emis-sion allowances slightly high. The emission concerned policies playan important role in the growth of renewable energy sources andpower system operation. The renewables provide flexibility to IPPsin preparing their units generation schedule and maximize theirwelfare. The percentage share of renewable under RPO should bedecided such that, it does not make emission regulations redun-dant. On the other hand, strict emission regulation would encour-age the renewable sector to increase its share, thus, makingrenewable support policies like feed-in-tariff ineffective. Thus,emission regulation and renewable support mechanism (RPO,feed-in-tariff, etc.) have to be justified. They not only reduce theCO2 emission, but also help in meeting the rising energy demandat relatively lesser cost, besides encouraging producers to investin renewable energy sector.

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