SysCon 2008 - IEEE International Systems ConferenceMontreal, Canada, April 7-10, 2008

Minimizing the Environmental Impact of theEnvisaged Expansion in Power Generation in

Main Interconnected System of OmanArif S. Malik

College of Engineering, PO Box 33Sultan Qaboos University

Sultanate of Omanasmal duo

Abstract - This paper presents the results of a study The first DSM study in Oman (1998), "Thecarried out to estimate the DSM energy saving potential in Study on Demand Supply Management for Powercommercial, and government/institutional sectors of Oman Sector in Sultanate of Oman", was conducted byand evaluates its impact on generation capacity, energy Japan International Cooperation Agency (JICA).and pollutants savings in the main interconnected system.

The st entified severati es (JIAlThe end-use (lighting and air-conditioning) energy The study identified several strategies for potentialconsumption data have been collected in two major load management [4]. However, thesegments of the commercial sector for simplicity. The study recommendations of the study have not beenhas found that due to DSM the capacity saving is about 300 implemented since then.MW, the overall energy saving is about 23.7 TWh and C02equivalent saving is about 13 million tons for the whole This paper presents the results of a recent study,planning horizon. The total avoided cost in generation and undertaken at Sultan Qaboos University, thatcapacity saving is about 346 million dollars. estimated the DSM energy saving and load

management potential in commercial andIndex Terms Power planning, Demand-side government/institutional sectors in Oman and

management, Energy conservation. evaluated its impact on generation capacity andenergy savings [5]. The study of [5] is extended to

I. INTRODUCTION include the savings in greenhouse gas pollutants. Theenergy saving potential in only two end-use

The utility planning process which takes into functions, i.e., lighting and air-conditioning, is lookedaccount both the supply- as well as demand-side at because these two end-use functions constitute aoptions to meet the demand forecast is known as major energy consumption (79%-96% of theintegrated resource planning (IRP) [1]. In many IRP surveyed samples) in these sectors regardless of theprocesses the resource contribution from DSM activity in both physical and economic terms. Theprograms could be very large because of untapped scope of the study is further limited to find the DSMresources that exist. For screening the large number potential in large customers of commercial andof DSM options available and identifying the most government/ institutional sectors only. Thepromising options avoided costs method is used to commercial sector represents about 16% andestimate their value to the utility system [2]. To government sector represents about 18.4% of thereduce the large number of DSM options in the total consumption in 2003 161. The load forecast andresource planning process the individual DSM generation data was taken from Ministry of Housing,options are bundled together into larger resource Electricity and Water (MHEW) of Oman and theblocks. The economy of aggregated bundles of DSM software used to optimize the generation plan isoptions is tested by the avoided cost method. The Wien Automatic System Planning (WASP) [7]. Theavoided cost has two components of savings the software has its own modeling limitations; forenergy costs savings and capacity cost savings. The example the transmission and distribution are notplanning horizon is optimized twice; one with a base modeled. Because of this limitation the saving incase set of loads and another with load shape (T&D) capacity cost due to DSM measures is notchanged by the expected load impact of DSM. quantified. The emission factors for natural gas-firedAvoided cost is then calculated by the difference in gas turbines are taken from US Environmentalenergy and capacity costs of the two optimized cases Protection Agency report 181.131.

978-1-4244-2150-3/08/$25.00 ©)2008 IEEE

The paper is arranged in six sections. Section one 1. An aggregate energy saving potential isis an introduction. Section two in brief provides a worked out with the assumption that the reduction ingeneral methodology adopted to carry out the study. power consumption due to DSM in the sample data isSection three provides generation and load data of representative of the actual potential in both themain interconnected system. Section four presents sectors. With this assumption the load forecast is alsothe results of generation capacity, energy and modified.pollutants savings and the last section concludes the 2. The utility benefit in terms of avoided cost ofpaper. generation capacity and energy is then worked out

by optimizing the planning horizon twice; one with abase case set of loads and the other with load shapechanged because of DSM.

The estimate of DSM potential is based on a survey 3. The emission factors, for natural gas-firedof 6 large commercial (shopping malls) customers gas turbines (almost all the generation in Oman is onand 6 large government/institutional customers. The natural gas), in lb/MMBtu for C02, CH4 and N20annual energy consumption of these 12 customers taken from [8] are then converted to gm/kWh usingrepresents about 4.6% (127.6 GWh) of the total the heat rate information of all the units. Theseconsumption (2,775 GWh, year 2003) in these two emission factors in gm/kWh are then multiplied withsectors. The energy saving potential is worked out in energy generated in GWh by each unit gives theonly two end-use functions, i.e., lighting and air- amount of greenhouse gas (GHG) pollutants in tons.conditioning, because these two end-use functions The difference is then calculated from the base caseconstitute the major energy consumption (79%-96% and DSM case.of the surveyed samples) in these sectors regardlessof the size of the activity in both physical and 1 GENERATION AND LOAD FORECAST DATAeconomic terms.To work out the potential of DSM, in these two The generation expansion planning is carried out

sectors, the following procedure is adopted: for the main interconnected system (MIS) from 20051. A survey questionnaire was designed to get to 2024. The MIS area comprises mainly six

the data needed from the commercial and interconnected power stations, which are Ghubrah,government/ institutional sectors. The first section of Rusail, Barka, Wadi Jizzi, Alkamil and Manahthe survey requests some general information about stations. The interconnection between these stationsthe building such as floor area, electric end-use is through 132-kV transmission lines. However,penetration rate, and annual power consumption. recently Barka power station is connected with theThe second section surveyed on lighting end-use Northern grid through 220-kV lines. All the powershare, percentage efficiency and the lifetime of the stations are operating on natural gas as fuel. Thelighting system and devices. The last section of the total capacity of these stations is about 2517 MWsurvey requires information about the air- (year 2005). The power transmission and distributionconditioning system in the sector, its end-use share, system mainly consists of 132-kV, 33-kV, 11-kV andpercentage efficiency and lifetime of the air- 415-V. Until recently 220-kV line from Barka stationconditioning equipment. is constructed to connect the station to the main 132-

2. From the catalogue information available kV grid. Only few kilometers of 66-kV line alsofor the efficient cooling and lighting devices [9-10] exists. The overall system losses reported in 2003the cost of efficient cooling and lighting functions were 20.83%. The generation data collected fromwere then worked out as 9.4 OR/m2 and 2.1 OR/m2 MHEW was manipulated, refined, and made suitablerespectively (1 Omani Rial (OR) = 1000 Baizas (Bz) = for WASP-IV input. For some of the missing data,2.58 US$). typical values found elsewhere were used. The

3. The estimate of total energy saved in lighting generation data for fixed plants, committed plantsand air-conditioning function for each customer was and candidate plants can be seen in [5] the load dataworked out using the percentage of efficiency save in is presented here.lighting and air-conditioning, if the existing lighting A. Load Dataand air-conditioning systems were replaced withmore efficient equipment, and multiplying the The surveyed governmental buildings annualannual consumption in lighting and air-conditioning consumption is 78.76 GWh, which represents aboutrespectively. 5.31% of the total governmental sector consumptionAfter getting the DSM potential the benefit of DSM in Oman. Similarly, the surveyed commercial

from the utility point of view is estimated using the buildings annual consumption is 48.85 GWh, whichexpansion planning approach. represents about 3.78% of the total commercial

sector consumption in Oman (2003) [6]. An TABLE Iaggregate energy saving potential is worked out with IMPLEMENTING DSM IN GOVERNMENTAL ANDthe assumption that the reduction in power COMMERCIAL SECTORSconsumption due to DSM in the sample data is Actual Modified Estimatrepresentative of the actual potential in both the energy energy Energy ed %sectors. Table I shows the percentage of energy consump consump Saved Reducticonsumption reduction by implementing DSM in tion tion (GWh) oncommercial and governmental sectors. (GWh) (GWh)Figure 1 shows the energy consumption forecast of Governmental 78.76 62.12 16.64 21.1%

government and commercial sectors up to 2024 using Sectorlinear regression on the 5 year actual energy Commeconsumption data. The DSM energy forecast is rcial 48.85 30.05 18.8 38.5%made, also shown in Fig. 1, using estimated Sectorpercentage reductions of table I. average system load factor of 53%. The average

system load factor was calculated using the past dataof energy consumption and the actual system peakdemand. To get the peak demand reduction, due to

3500 DSM, from the system peak another assumption isGo\t ---- Comm -o--Go\t-DSM -- x-- Comm-DSM made that the peak coincident factor of government3000 -o , sector is 100% of the system peak and commercial

- 2500 - sector is 80% of the system peak. Figure 2 shows theo 2000 - system peak demand forecast, taken from MHEW,

-1500>=_ t and the modified system peak demand.

l -ooo500 - IV. RESULTS AND DISCUSSIONS

0- To investigate the DSM benefit from the utility1999 2004 2009 2014 2019 2024 point of view the avoided cost method is used. The

Years avoided cost of generation capacity and energy is

Fig. 1. Forecast of energy consumption in Government worked out by optimizing the planning horizonand commercial sector with and without DSM. twice; first with a base case set of loads (Case 1),

second with load shape changed by the expected loadThe energy forecast of government and impact of DSM (Case 2). Table II provides the

commercial sectors is then converted to peak summary of the optimization results. The table showsdemand forecast using (1). the present worth of total cost (cumulative objective

function in thousands of dollars), the average loss-of-Peak Demand (MW) = Annual Consumption (MWh) (1) load probability index, and the major greenhouse gas

LFx8760 hrs pollutants over the planning horizon. The table alsoprovides the cumulative capacity selected in eachcase and the energy requirement for two scenarios.

whereptiLF is thde systthe load factor. Here ah The difference in cost, pollutants, capacity andassumption is made that the load factor of bothgovernment and commercial sectors are same as the energy of Case 1 and Case 2 is also shown. The

TABLE IIRESULTS OF OPTIMAL GENERATION EXPANSION PLAN FROM 2005 TO 2024

Present worth Cumulative Pollutantscost (thousand $) Average Cumulative Cumulative

Cases Obj. Fun. B1 LOLP % 002 OH4 Np Capacity (MW) Energy (GWh)

(Cummi.) Mtons Tons Tons

| (Case 1) 3801320 0.797 171 13367 4663 6217 413752 l

(Case 2) 3455248 0.471 158 12375 4317 5900 390075 l

(Casel-Case 2) 346072 0.270 13 992 346; 317 23677 l

overall cumulative cost difference over the planning replacing their inefficient devices. Financing DSMhorizon (avoided cost = Bj, base - Bj, DSM) is 346 remains a significant issue in most places. Manymillion dollars. At the horizon year the capacity and countries have imposed DSM taxes within powerenergy difference from the base case is about 317 tariff schemes. Other governments have opted toMW and 23.7 TWh respectively. The difference of fund DSM programs for low-income customers as a

CO2 is about 13 million tons over the planning social program, and effectively pay the utility tohorizon. Figure 3 shows the CO2 emissions with and implement the program.without DSM. Finally, it can be concluded with confidence that

Demand Side Management has positive outcomes for6500-1 -System Peak Load Forecast consumers, MHEW, environment and the national

i 6000 - +-o- System Peak Load Forecast-DSM c5500- income which makes it strongly recommended to

<s5 5000-start thinking about implementing it in Oman.4500-

a4000-_,3500 - _ = ACKNOWLEDGEMENT AND DISCLAIMER

E 3000-,, 2500 t The author would like to acknowledge Internal" 2000 Research Grant for this project from Sultan Qaboos

2005 2010 Years 2015 2020 University. The views expressed in the paper are

entirely mine and do not reflect the position ofFig. 2. System peak demand forecast with and without MHEW.DSM.

14 REFERENCES12 _CU2Base [1] Kreith F. Integrated resource planning. Journal of Energy

10 0Resources Technology 1993; 115: 80-85.-t 1[2] Busch J, Eto J. Estimation of avoided costs for electric utility0 = = = = 5 ~ demand-side planning. Energy Sources 1996; 18:473-499.2 6 [3] Malik, A. Modeling and economic analysis of DSM programs% 4 in generation planning. International Journal of Electrical

Power and Energy Systems 2001; 23: 413-419.[4] Japan International Cooperation Agency (JICA). The study

0 on Demand Supply Management for power sector in2003 2008 2013 2018 2023 Sultanate of Oman. A final report of JICA to Ministry of

Year Housing, Electricity and Water (MHEW), MHEW CentralOffice: Al-Khuwair, Muscat, Sultanate of Oman, November1998.

Fig. 3. Forecast of energy consumption in Government [5] Al-Hindi M, Al-Mahorouqi Y, Al-Khrousi A.. Demand-sideand commercial sector with and without DSM. management energy saving potential in commercial and

other sectors and its impact on power planning - A casestudy of Central Grid of Oman. Final Year Project Report.Muscat, Oman: SQU, Electrical Engineering Department,

V. CONCLUSIONS 2005.[6] Annual Statistical book of year 2003 of electrical sectors,

The study has shown that by applying DSM Muscat, Oman: Ministry of Housing, Electricity, and Water,programs in the government and commercial sectors MHEWCentral Office: Al-Khuwair, Muscat, Sultanate ofthe energy consumption can be reduced up to 21% Oman 2003.and 38% respectively with 8.6% standard pooled [7] Wien Automatic System Planning Package, (WASP-IV),error. From the supplier (MHEW) point of view the Vienna: IAEA, 2003.

18] Alpha-Gamma Technologies, Inc. Emission Factorcapacity saving at the horizon year is 317 MW due to Documentation for AP-42 Section 3.1 Stationary GasDSM. Likewise, the overall energy saving for the Turbines. Alpha-Gamma Technologies, Inc. 4700 Falls ofwhole planning horizon is about 23.7 TWh and the Neuse Road, Raleigh, North Carolina, 2000.total avoided cost saving is 346 million dollars. The http://www.epa.gov/ttn/chief/ap42/chO3/index.htmldifference in cumulative CO2 accumulation is about [9] Bahwan Engineering Company (BEC). Catalogue of cooling

devices. BEC Head Office: Ruwi-112, Sultanate of Oman,13 million tons and methane and nitrous oxide is 992 2004.and 346 tons respectively. [10] Khimji Ramdas Company (KRC). Catalogue of lightingOne ofthe problems which faced the countries that devices. KRC Corporate Office: Muscat-113, Sultanate of

applied DSM is motivating customers to pay for Oman, 2003.