This document analyzes the financial performance of PT PLN Java-Bali Power 2 (PJB2) from 1995-1997 in preparation for going public. It finds that while PJB2's liquidity and solvency ratios are healthy, its profitability ratios are very low compared to other public companies. Specifically, PJB2's return on equity was 5.71% in 1996 and 2.29% in 1997, while its return on assets was 4.78% in 1996 and 1.85% in 1997. However, PJB2's cost structure shows a positive contribution margin, meaning market share gains could increase profits. Electricity demand projections also indicate rapid growth for PJB2 through 2003. To improve
Financial Comparative Analysis of SPV and SPT Power Plants for a Village in R...IRJET Journal
This document analyzes the financial feasibility of solar photovoltaic (SPV) and solar parabolic trough (SPT) power plants for a village in Rajasthan, India. Population and energy consumption data for the village are forecasted for years 2015, 2019, and 2024. Based on the projected energy demands, SPV and SPT plants of appropriate sizes are proposed. Capital costs for SPV and SPT plants are estimated for the analysis years. A financial analysis is conducted for each plant type under four scenarios: pre-tax, post-tax, pre-tax with equity, post-tax with equity. Key financial indicators such as IRR, payback period, and NPV are calculated and
This document provides an overview of different methods for long-term electric load demand forecasting. It begins with an introduction to the importance of long-term demand forecasting for electric utility planning. It then describes several traditional parametric forecasting methods, including trend analysis, end-use modeling, and econometric modeling. The key differences between these methods are discussed. The document then introduces several artificial intelligence-based methods that have been used for long-term load forecasting, including neural networks, genetic algorithms, fuzzy logic, support vector machines, wavelet networks, and expert systems. Specific network architectures for neural networks that are suitable for long-term load forecasting are also described, such as recurrent neural networks, feed-forward back
IRJET- Predicting Monthly Electricity Demand using Soft-Computing TechniqueIRJET Journal
This document proposes using soft-computing techniques like multi-layer perceptron, support vector machine, and decision tree algorithms to predict monthly electricity demand in Ghana. It analyzed three years of historical weather and electricity demand data from the Bono region to train and test the models. The decision tree algorithm achieved 80.57% accuracy, multi-layer perceptron achieved 95% accuracy, and support vector regression achieved 67.2% accuracy according to the results. The models were efficient at predicting future electricity load.
Contents lists available at ScienceDirectThe Electricity JAlleneMcclendon878
Contents lists available at ScienceDirect
The Electricity Journal
journal homepage: www.elsevier.com/locate/tej
Electricity demand modeling in Saudi Arabia: Do regional differences
matter?
Jeyhun I. Mikayilova,b,*, Fakhri J. Hasanova,c, Waheed Olagunjud, Mohammad H. Al-Shehrie
a King Abdullah Petroleum Studies and Research Center, PO Box 88550, Riyadh, 11672, Saudi Arabia
b Azerbaijan State University of Economics (UNEC), Istiqlaliyyat Str., 6, Baku, Azerbaijan
c The George Washington University, 2115 G Street, NW, Washington, DC, 20052, USA
d Ministry of Energy, King Saud St., Al Wizarat, Riyadh, 12622, Saudi Arabia
e Saudi Electricity Company, Takhassusi St., Riyadh, 12333, Saudi Arabia
A R T I C L E I N F O
Keywords:
Electricity demand
Price elasticity
Cointegration
Regions
Saudi Arabia
A B S T R A C T
The paper examines the electricity demand behavior for Saudi Arabia, using annual data for the period of
1990–2016, at regional level. The study finds that income, price and population are the main drivers of elec-
tricity demand at regional level. Although, the impacts vary across regions (central, eastern, southern and
western), the estimated elasticities all are statistically significant, in both long and short run, and have the
expected signs for all the regions. The income, price and population elasticities range from 0.10 to 0.93, from
-0.63 to -0.06, and from 0.24 to 0.95, respectively, across regions in the long run. In the short run these intervals
are (0.05, 0.47), (−0.27, −0.01) and (0.13, 1.49) respectively for income, price and population across the
regions. The findings reported in this paper, should assist policy makers to develop insights about the potential
regional impact of changes to electricity prices, income and population patterns.
1. Introduction
Since energy is a pervasive input to all business and recreational
activities, total energy demand is an important indicator that helps
explain the pattern of economic development within a country.
Identifying and understanding the key determinants of electricity de-
mand is therefore important for the economic prosperity of a country,
since the availability of reliable electricity directly affects the prospects
of sustainable economic development. With important mega projects
already in the works and national transformation programs such as the
National Industrial Development and Logistics Program (NIDLP, 2019)
already being implemented, understanding the existing and projected
behaviour of electricity demand is more important now than ever be-
fore.
While it is relevant to conduct a study that investigates the de-
terminants of aggregate electricity demand in KSA, this is a topic that
has already been addressed by the existing literature to some extent
(Atalla and Hunt, 2016, inter alia). However, aggregate level electricity
demand has not been studied at regional level. Hence, there is a need
for a research to investigate the aggregate level electricity demand
...
Analysis of Maximum Demand of Educational Buildings and its Impact on Electri...IRJET Journal
This document analyzes the maximum electricity demand of an engineering college in Rajasthan, India over two years to identify opportunities to reduce electricity bills. It finds that the college was paying for 75% of its connected load as a minimum demand charge each month, even when actual demand was lower. By analyzing monthly bills and demand patterns, opportunities were identified to more accurately forecast connected load closer to actual consumption, reducing unnecessary demand charges. Plotting load curves provided transparency into consumption patterns. With infrastructure and technology upgrades also considered, connected load could be reduced while maintaining satisfaction, lowering electricity costs.
Efficacy of Power Distribution Companies (PDCs): A Review of Selected StudiesAJHSSR Journal
ABSTRACT: The electricity distribution sector plays a vital role in the modern economy, and the efficiency
of power distribution companies (PDCs) has a significant impact on the cost of electricity and the reliability of
the power supply. This paper reviews selected review papers on the efficacy of PDCs and identifies key factors
that affect their performance. The review finds that the efficiency of PDCs is influenced by several factors,
including the regulatory environment, the structure of the electricity market, and the technological capabilities
of the companies. The paper also identifies several challenges faced by PDCs in improving their efficiency, such
as the need to invest in new technologies and the need to manage the increasing electricity demand. The findings
of this review can be used to inform policymakers and regulators in their efforts to improve the efficiency of
PDCs and, in turn, the overall performance of the electricity distribution sector.
KEYWORDS: power distribution companies (PDCs), AT&C Losses, Power Sector Reform, KPIs.
Comprehensive Evaluation Model for the Implementation Effect of China's Trans...AI Publications
This document proposes a comprehensive evaluation model to assess the implementation effect of China's transmission and distribution tariff reform. It establishes a four-dimensional index system including 12 indicators to evaluate economic efficiency, safety and reliability, energy saving and environment protection, and satisfaction. A hybrid model is proposed using the Best-Worst Method to determine indicator weights and the Matter-Element Extension Model to rank performance. This evaluation model can provide references for policymakers to improve tariff reform policies.
This document compares conventional and modern techniques for electrical load forecasting based on artificial intelligence and expert systems. It summarizes the key differences between short-term, medium-term, and long-term load forecasting and describes some common methods used, including regression analysis, time series analysis, artificial neural networks, expert systems, and fuzzy logic. The document advocates that modern soft computing techniques provide more accurate load forecasts than traditional analytical methods by better representing the complex nonlinear relationships between load and influencing factors.
Financial Comparative Analysis of SPV and SPT Power Plants for a Village in R...IRJET Journal
This document analyzes the financial feasibility of solar photovoltaic (SPV) and solar parabolic trough (SPT) power plants for a village in Rajasthan, India. Population and energy consumption data for the village are forecasted for years 2015, 2019, and 2024. Based on the projected energy demands, SPV and SPT plants of appropriate sizes are proposed. Capital costs for SPV and SPT plants are estimated for the analysis years. A financial analysis is conducted for each plant type under four scenarios: pre-tax, post-tax, pre-tax with equity, post-tax with equity. Key financial indicators such as IRR, payback period, and NPV are calculated and
This document provides an overview of different methods for long-term electric load demand forecasting. It begins with an introduction to the importance of long-term demand forecasting for electric utility planning. It then describes several traditional parametric forecasting methods, including trend analysis, end-use modeling, and econometric modeling. The key differences between these methods are discussed. The document then introduces several artificial intelligence-based methods that have been used for long-term load forecasting, including neural networks, genetic algorithms, fuzzy logic, support vector machines, wavelet networks, and expert systems. Specific network architectures for neural networks that are suitable for long-term load forecasting are also described, such as recurrent neural networks, feed-forward back
IRJET- Predicting Monthly Electricity Demand using Soft-Computing TechniqueIRJET Journal
This document proposes using soft-computing techniques like multi-layer perceptron, support vector machine, and decision tree algorithms to predict monthly electricity demand in Ghana. It analyzed three years of historical weather and electricity demand data from the Bono region to train and test the models. The decision tree algorithm achieved 80.57% accuracy, multi-layer perceptron achieved 95% accuracy, and support vector regression achieved 67.2% accuracy according to the results. The models were efficient at predicting future electricity load.
Contents lists available at ScienceDirectThe Electricity JAlleneMcclendon878
Contents lists available at ScienceDirect
The Electricity Journal
journal homepage: www.elsevier.com/locate/tej
Electricity demand modeling in Saudi Arabia: Do regional differences
matter?
Jeyhun I. Mikayilova,b,*, Fakhri J. Hasanova,c, Waheed Olagunjud, Mohammad H. Al-Shehrie
a King Abdullah Petroleum Studies and Research Center, PO Box 88550, Riyadh, 11672, Saudi Arabia
b Azerbaijan State University of Economics (UNEC), Istiqlaliyyat Str., 6, Baku, Azerbaijan
c The George Washington University, 2115 G Street, NW, Washington, DC, 20052, USA
d Ministry of Energy, King Saud St., Al Wizarat, Riyadh, 12622, Saudi Arabia
e Saudi Electricity Company, Takhassusi St., Riyadh, 12333, Saudi Arabia
A R T I C L E I N F O
Keywords:
Electricity demand
Price elasticity
Cointegration
Regions
Saudi Arabia
A B S T R A C T
The paper examines the electricity demand behavior for Saudi Arabia, using annual data for the period of
1990–2016, at regional level. The study finds that income, price and population are the main drivers of elec-
tricity demand at regional level. Although, the impacts vary across regions (central, eastern, southern and
western), the estimated elasticities all are statistically significant, in both long and short run, and have the
expected signs for all the regions. The income, price and population elasticities range from 0.10 to 0.93, from
-0.63 to -0.06, and from 0.24 to 0.95, respectively, across regions in the long run. In the short run these intervals
are (0.05, 0.47), (−0.27, −0.01) and (0.13, 1.49) respectively for income, price and population across the
regions. The findings reported in this paper, should assist policy makers to develop insights about the potential
regional impact of changes to electricity prices, income and population patterns.
1. Introduction
Since energy is a pervasive input to all business and recreational
activities, total energy demand is an important indicator that helps
explain the pattern of economic development within a country.
Identifying and understanding the key determinants of electricity de-
mand is therefore important for the economic prosperity of a country,
since the availability of reliable electricity directly affects the prospects
of sustainable economic development. With important mega projects
already in the works and national transformation programs such as the
National Industrial Development and Logistics Program (NIDLP, 2019)
already being implemented, understanding the existing and projected
behaviour of electricity demand is more important now than ever be-
fore.
While it is relevant to conduct a study that investigates the de-
terminants of aggregate electricity demand in KSA, this is a topic that
has already been addressed by the existing literature to some extent
(Atalla and Hunt, 2016, inter alia). However, aggregate level electricity
demand has not been studied at regional level. Hence, there is a need
for a research to investigate the aggregate level electricity demand
...
Analysis of Maximum Demand of Educational Buildings and its Impact on Electri...IRJET Journal
This document analyzes the maximum electricity demand of an engineering college in Rajasthan, India over two years to identify opportunities to reduce electricity bills. It finds that the college was paying for 75% of its connected load as a minimum demand charge each month, even when actual demand was lower. By analyzing monthly bills and demand patterns, opportunities were identified to more accurately forecast connected load closer to actual consumption, reducing unnecessary demand charges. Plotting load curves provided transparency into consumption patterns. With infrastructure and technology upgrades also considered, connected load could be reduced while maintaining satisfaction, lowering electricity costs.
Efficacy of Power Distribution Companies (PDCs): A Review of Selected StudiesAJHSSR Journal
ABSTRACT: The electricity distribution sector plays a vital role in the modern economy, and the efficiency
of power distribution companies (PDCs) has a significant impact on the cost of electricity and the reliability of
the power supply. This paper reviews selected review papers on the efficacy of PDCs and identifies key factors
that affect their performance. The review finds that the efficiency of PDCs is influenced by several factors,
including the regulatory environment, the structure of the electricity market, and the technological capabilities
of the companies. The paper also identifies several challenges faced by PDCs in improving their efficiency, such
as the need to invest in new technologies and the need to manage the increasing electricity demand. The findings
of this review can be used to inform policymakers and regulators in their efforts to improve the efficiency of
PDCs and, in turn, the overall performance of the electricity distribution sector.
KEYWORDS: power distribution companies (PDCs), AT&C Losses, Power Sector Reform, KPIs.
Comprehensive Evaluation Model for the Implementation Effect of China's Trans...AI Publications
This document proposes a comprehensive evaluation model to assess the implementation effect of China's transmission and distribution tariff reform. It establishes a four-dimensional index system including 12 indicators to evaluate economic efficiency, safety and reliability, energy saving and environment protection, and satisfaction. A hybrid model is proposed using the Best-Worst Method to determine indicator weights and the Matter-Element Extension Model to rank performance. This evaluation model can provide references for policymakers to improve tariff reform policies.
This document compares conventional and modern techniques for electrical load forecasting based on artificial intelligence and expert systems. It summarizes the key differences between short-term, medium-term, and long-term load forecasting and describes some common methods used, including regression analysis, time series analysis, artificial neural networks, expert systems, and fuzzy logic. The document advocates that modern soft computing techniques provide more accurate load forecasts than traditional analytical methods by better representing the complex nonlinear relationships between load and influencing factors.
This document compares conventional and modern techniques for electrical load forecasting based on artificial intelligence and expert systems. It summarizes the key differences between short-term, medium-term, and long-term load forecasting and describes some common methods used, including regression analysis, time series analysis, artificial neural networks, expert systems, and fuzzy logic. The document advocates that modern soft computing techniques provide more accurate load forecasts than traditional analytical methods by better representing the complex, nonlinear relationships between load and influencing factors.
This document summarizes an electrical energy audit conducted at the Nandi Institute of Technology and Management Sciences (NIT&MS) campus in Bangalore, India. The audit found that the total average monthly electrical energy consumption across the campus was 3,842.842 kWh. Personal computers in labs, offices, and libraries accounted for the highest consumption at 39.14% of total usage. Fans were the second highest usage at 21.53%. Recommendations to improve energy efficiency included replacing conventional ballasts with electronic ones, installing motion sensors, replacing CRT monitors with LCDs, and switching to LED lights. Implementing all recommendations could save an estimated 10,435.84 kWh per year and reduce electricity costs by
Prevalence of Electricity Power theft in Nueva Ecija II Electric Cooperative,...IJAEMSJORNAL
This research focused on the prevalence of electricity power theft in areas covered by NEECO II- Area 2. The data from the Special Energy Recovery Group (Apprehension Group) revealed that there were 386 apprehended electric pilferers from 2014-2016 and that the towns of Sta. Rosa and San Leonardo recorded the highest number of consumers and also have the highest number of electric pilferers as compared to other towns covered by NEECO II – Area 2. Among all the types of electric theft, the jumper is the most prevalent in areas covered by NEECO II – Area 2 from 2014-2016. Based on data available, the towns of Sta. Rosa registered the highest number of electric power theft by means of jumper (91) and illegal connection (30), followed by the town of Gen. Tinio (42), San Leonardo (32), Peñaranda (32), Bongabon (23), Gen. Natividad (16) and the rest of the towns are minimal in number. By comparing the total number of electric power theft regardless of its type, the year 2014 registered the highest number of violators (173) and significantly decrease in the year 2015 and 2016 (119 and 95, respectively) and up to August 2017 (39). Based on the computation from the Special Energy Recovery Group (Apprehension Group) and that of the Finance Department, the total non-technical losses occurred from 2014-2016 was 6.50 % and it is equivalent to P81,464,791.83 or on the average P2,292,910.88 per month. Losses can be even higher because the actual non-technical losses cannot be easily detected, meaning the apprehended party might consume higher than the average consumption because as being said, it is electric theft.
Sapele Thermal Power Station Generator Availability and Units Performance Stu...irjes
This document discusses a study of generator availability and performance at Sapele Thermal Power Station in Nigeria from 2005 to 2011. Data was collected on the availability and performance of 6 generating units at the power station. The study found the average availability of the units ranged from 29.71% to 89.99%, with an overall station availability of 88.35%. Increased forced outages were found to reduce plant availability. The reasons and durations for forced outages were identified to help improve reliability.
Why enincon‟s report upon “ Power Distribution Tariffs in India 2018”?
With power distribution reforms gained momentum soon after the application of EA 2003 (where it was believed to be coined in mid 90‟s) , Indian power distribution utilities came along way since then. With, introduction of reforms and multiple cognitive steps undoubtedly the power distribution sector stands improved by leaps from the erstwhile levels. Having said that, it indeed still represents the weakest link of the power generation, transmission and distribution chain
Are hydropower investment in Nepal economically viableDilip Jena
This document discusses approaches to conducting cost-benefit analyses for hydropower investments. It reviews the perspectives of economists, funding agencies, the US Federal Energy Regulatory Commission, and a hydropower project developer in Costa Rica. The key steps in economic analysis are identified as: identifying the project, estimating associated costs and benefits, and comparing costs to benefits. Cost elements generally include capital expenditures, operation and maintenance costs, while benefits include the value of electricity generation. The literature aims to determine if hydropower investments are economically viable for Nepal by applying these cost-benefit analysis methods.
26 jurnal internasional factor affecting the implementation of gcg in contro...Aminullah Assagaf
This document summarizes a research study that examined factors affecting the implementation of good corporate governance (GCG) in controlling operations and finances at PT PLN (Persero), Indonesia's state-owned electricity company. Specifically, it analyzed the impact of inflation rate, installed capacity of consumer sectors, and installed capacity of productive consumer groups on GCG implementation in controlling operational and financial efficiency. The study found that inflation rate did not significantly impact the dependent variable, while installed capacity of consumer and productive consumer groups did significantly impact it. Installed capacity of consumer sectors had a negative effect, while installed capacity of productive consumer groups had a positive effect. It recommends PT PLN prioritize managing these two installed capacity variables to optimize GCG values
Assessment of Energy Losses and Cost Implications in the Nigerian Distributio...Dr. Hachimenum Amadi
Energy shortages is the major challenge facing the industrial sector in Nigeria. This paper assessed the energy shortages due to technical losses in the Nigerian distribution network and the cost implications. The study was carried out based on network data collected over the period 2011-2015 from three electricity distribution companies (DisCos) drawn from the three major industrial cities of Nigeria. These data were simulated on the Electrical Transient Analysis program (ETAP) Version 12.6. The calculated energy losses for these cities for the said period are 108,959.87 MWH, 149,256 MWH and 72,743.08 MWH respectively. The corresponding revenue losses are N2,434,164,012, N3,538,754,758.8 and N1,699,751,530.1 respectively. The paper suggested remedial measures to reduce energy losses, mitigate losses arising from unannounced electricity cuts as well as achieve a more efficient and reliable electricity distribution network. The outcome of this research provides a data bank for policy makers and future researchers in the areas of electricity generation, transmission and distribution.
Before we kick-off a new line-up of insightful studies and conversations on energy this 2021, we take a snapshot of the previous working papers which were featured last year.
These studies were produced under the Access to Sustainable Energy Programme-Clean Energy Living Laboratories (ASEP-CELLs) project implemented by the Ateneo School of Government (ASOG), and funded by the European Union.
To receive updates on our latest events and publications, please subscribe to our mailing list through this link: http://bit.ly/ASEPCELLsMailingList
IRJET- An Energy Conservation Scheme based on Tariff ModerationIRJET Journal
This document discusses an energy conservation scheme based on tariff modification for domestic users. It proposes a new tariff rate structure that provides incentives for low consumption and penalties for high consumption. This aims to motivate consumers to reduce energy usage without causing losses for electric utilities. The existing structure provides 100 free units, which does not encourage conservation and causes losses. The proposed system calculates bills based on consumed units and compares to averages to determine incentives or penalties. The goal is to reduce residential energy usage through this modified tariff approach.
Analysis of Electric Power Consumption using Smart Meter DataIRJET Journal
This document proposes an analytical model to analyze electric power consumption using smart meter data. The model consists of two modules: 1) A consumer-oriented module that clusters consumers with similar appliances and analyzes consumption patterns to provide customized recommendations for reducing usage. 2) A predictive module that uses historical consumption data to identify trends and predict future usage or irregularities. The proposed system first collects smart meter data, preprocesses it, then clusters consumers using k-means clustering based on appliance type and number. Consumption profiles are analyzed within each cluster to develop standards and suggest recommendations. Historical data is also used for predictive modeling and outlier detection.
IRJET- Economic Valuation of a Wetland by using Statistical Method: A Cas...IRJET Journal
This document summarizes a study that estimated the economic value of Chalan Billabong wetland in Bangladesh using statistical methods. The study used the contingent valuation method to estimate the current non-use value of the wetland by surveying 300 local households. Key findings from the survey and statistical analysis include:
1) The majority of survey respondents were male, younger (18-30 years old), and had a bachelor's degree level of education.
2) Statistical models including a logit model and multiple regression model were used to analyze responses on willingness to pay for wetland conservation.
3) The results of the study estimated the current annual economic value of the wetland's non-use attributes to guide government
The document discusses three key causes of Pakistan's power crisis: 1) Consumers are unwilling to pay the full economic cost of electricity, despite wanting an end to power cuts. 2) Subsidies disproportionately benefit higher-income households and industries rather than the poor. 3) High administrative and line losses due to theft and inefficiency, which account for billions in lost revenue annually. The National Power Policy aims to address these issues through cost-reflective tariffs, targeted subsidies for the poor only, and increased accountability to curb losses. However, bold reforms are needed to phase out subsidies faster and incentivize performance to truly solve Pakistan's long-standing power issues.
The document discusses load profiling arrangements for the NSW gas market as it transitions to full retail competition (FRC). It summarizes that net system load profiling (NSLP) using regional profiles will be used to facilitate FRC. Key aspects include annual apportionment of loads to retailers, forward reconciliation over 28 days, and global settlements to spread errors across all participants. The arrangements aim to balance objectives like equity, efficiency and minimizing barriers to competition during the transition to FRC.
Energy demand forecasting of remote areas using linear regression and inverse...IJECEIAES
Efficient energy demand forecasting is pivotal for addressing energy challenges in remote areas of Bangladesh, where reliable access to energy resources remains a concern. This study proposes an innovative approach that combines linear regression analysis (LRA) and inverse matrix calculation (IMC) to forecast energy demand accurately in these underserved regions. By leveraging historical energy consumption data and pertinent predictors, such as meteorological conditions, population dynamics, economic indicators, and seasonal patterns, the model provides reliable forecasts. The application of the proposed methodology is demonstrated through a case study focused on remote regions of Bangladesh. The results showcase the approach's effectiveness in capturing the intricate dynamics of energy demand and its potential to inform sustainable energy management strategies in these remote areas. This research contributes to the advancement of energy planning and resource allocation in regions facing energy scarcity, fostering a path towards improved energy efficiency and development. These techniques can be applied to estimate short-term electricity demand for any rural or isolated region worldwide.
The document presents the Kalimantan Tengah Green Economy Model (KT-GEM), a provincial-level application of Indonesia's national Green Economy Model (I-GEM) tailored for Central Kalimantan province. KT-GEM simulates the impacts of policies and scenarios on key indicators like GDP of the rural poor, green GDP, and decent green jobs. The model's business as usual scenario projects population growth, increasing GDP driven primarily by industry/services and tourism, and declining natural capital as agriculture and settlements expand onto forest lands. KT-GEM can help officials assess whether their plans will reduce poverty, create jobs, and protect the environment to transition Kalteng to a green economy.
Black book project on power generation companyAkash Gupta
To study the performance and analyze the valuation of power generation Companies namely NHPC and its peer company like Tata Power, Neyveli Lignite, and Reliance power.
Multivariate analysis of the impact of the commercial banks on the economic g...Alexander Decker
The document analyzes the impact of commercial banks on economic growth in Nigeria from 1970-2009 using multivariate analysis and the ordinary least squares method. It finds that commercial bank credits, deposit liabilities, and lending rates had a positive relationship with GDP, indicating they help achieve economic growth. However, the number of banks had a negative but insignificant relationship with GDP. The study concludes that policies aimed at increasing commercial bank capital bases should be pursued to increase loanable funds and sustainable economic growth and development.
Modeling and Analysis of Wholesale Competitive Electricity Markets: A Case Fo...IJERA Editor
Electricity markets all over the world are moving towards greater reliance on competition and this has become a global trend as a method of best practice. However, before competition is introduced in electricity markets it is imperative to model and assess the behavior of the market. The assessment includes calculating the market performance indices to determine the levels of market power exploitation by the Generating Companies (GenCos) that will participate in the market. This paper presents a study on modeling and analysis of wholesale competitive electricity market for a developing country to help regulators assess and predict market behaviour. It involves modeling and simulation of the Zambian power system network in Agent-Based Modeling of Electricity Systems (AMES) using real system data to pick out critical information that enables us to assess the status of the market. The results indicate that market power exploitation is prevalent for the two largest GenCos assessed.
This document provides a detailed project report for implementing smart meters and DT modems at Uttar Pradesh Power Corporation Limited (UPPCL) in India. UPPCL aims to improve efficiency, revenue collection and consumer services through this project. The project will install smart meters and DT modems across UPPCL's distribution areas to digitize billing and enable online payment options. This is expected to reduce costs, improve reliability of power supply and enhance consumer experience. The report discusses UPPCL's existing IT systems, the objectives and benefits of the project, and provides cost estimates and an implementation timeline.
This document compares conventional and modern techniques for electrical load forecasting based on artificial intelligence and expert systems. It summarizes the key differences between short-term, medium-term, and long-term load forecasting and describes some common methods used, including regression analysis, time series analysis, artificial neural networks, expert systems, and fuzzy logic. The document advocates that modern soft computing techniques provide more accurate load forecasts than traditional analytical methods by better representing the complex, nonlinear relationships between load and influencing factors.
This document summarizes an electrical energy audit conducted at the Nandi Institute of Technology and Management Sciences (NIT&MS) campus in Bangalore, India. The audit found that the total average monthly electrical energy consumption across the campus was 3,842.842 kWh. Personal computers in labs, offices, and libraries accounted for the highest consumption at 39.14% of total usage. Fans were the second highest usage at 21.53%. Recommendations to improve energy efficiency included replacing conventional ballasts with electronic ones, installing motion sensors, replacing CRT monitors with LCDs, and switching to LED lights. Implementing all recommendations could save an estimated 10,435.84 kWh per year and reduce electricity costs by
Prevalence of Electricity Power theft in Nueva Ecija II Electric Cooperative,...IJAEMSJORNAL
This research focused on the prevalence of electricity power theft in areas covered by NEECO II- Area 2. The data from the Special Energy Recovery Group (Apprehension Group) revealed that there were 386 apprehended electric pilferers from 2014-2016 and that the towns of Sta. Rosa and San Leonardo recorded the highest number of consumers and also have the highest number of electric pilferers as compared to other towns covered by NEECO II – Area 2. Among all the types of electric theft, the jumper is the most prevalent in areas covered by NEECO II – Area 2 from 2014-2016. Based on data available, the towns of Sta. Rosa registered the highest number of electric power theft by means of jumper (91) and illegal connection (30), followed by the town of Gen. Tinio (42), San Leonardo (32), Peñaranda (32), Bongabon (23), Gen. Natividad (16) and the rest of the towns are minimal in number. By comparing the total number of electric power theft regardless of its type, the year 2014 registered the highest number of violators (173) and significantly decrease in the year 2015 and 2016 (119 and 95, respectively) and up to August 2017 (39). Based on the computation from the Special Energy Recovery Group (Apprehension Group) and that of the Finance Department, the total non-technical losses occurred from 2014-2016 was 6.50 % and it is equivalent to P81,464,791.83 or on the average P2,292,910.88 per month. Losses can be even higher because the actual non-technical losses cannot be easily detected, meaning the apprehended party might consume higher than the average consumption because as being said, it is electric theft.
Sapele Thermal Power Station Generator Availability and Units Performance Stu...irjes
This document discusses a study of generator availability and performance at Sapele Thermal Power Station in Nigeria from 2005 to 2011. Data was collected on the availability and performance of 6 generating units at the power station. The study found the average availability of the units ranged from 29.71% to 89.99%, with an overall station availability of 88.35%. Increased forced outages were found to reduce plant availability. The reasons and durations for forced outages were identified to help improve reliability.
Why enincon‟s report upon “ Power Distribution Tariffs in India 2018”?
With power distribution reforms gained momentum soon after the application of EA 2003 (where it was believed to be coined in mid 90‟s) , Indian power distribution utilities came along way since then. With, introduction of reforms and multiple cognitive steps undoubtedly the power distribution sector stands improved by leaps from the erstwhile levels. Having said that, it indeed still represents the weakest link of the power generation, transmission and distribution chain
Are hydropower investment in Nepal economically viableDilip Jena
This document discusses approaches to conducting cost-benefit analyses for hydropower investments. It reviews the perspectives of economists, funding agencies, the US Federal Energy Regulatory Commission, and a hydropower project developer in Costa Rica. The key steps in economic analysis are identified as: identifying the project, estimating associated costs and benefits, and comparing costs to benefits. Cost elements generally include capital expenditures, operation and maintenance costs, while benefits include the value of electricity generation. The literature aims to determine if hydropower investments are economically viable for Nepal by applying these cost-benefit analysis methods.
26 jurnal internasional factor affecting the implementation of gcg in contro...Aminullah Assagaf
This document summarizes a research study that examined factors affecting the implementation of good corporate governance (GCG) in controlling operations and finances at PT PLN (Persero), Indonesia's state-owned electricity company. Specifically, it analyzed the impact of inflation rate, installed capacity of consumer sectors, and installed capacity of productive consumer groups on GCG implementation in controlling operational and financial efficiency. The study found that inflation rate did not significantly impact the dependent variable, while installed capacity of consumer and productive consumer groups did significantly impact it. Installed capacity of consumer sectors had a negative effect, while installed capacity of productive consumer groups had a positive effect. It recommends PT PLN prioritize managing these two installed capacity variables to optimize GCG values
Assessment of Energy Losses and Cost Implications in the Nigerian Distributio...Dr. Hachimenum Amadi
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These studies were produced under the Access to Sustainable Energy Programme-Clean Energy Living Laboratories (ASEP-CELLs) project implemented by the Ateneo School of Government (ASOG), and funded by the European Union.
To receive updates on our latest events and publications, please subscribe to our mailing list through this link: http://bit.ly/ASEPCELLsMailingList
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1 jurnal pjb go public
1. IOSR Journal of Business and Management (IOSR-JBM)
e-ISSN: 2278-487X, p-ISSN: 2319-7668. Volume 13, Issue 5 (Sep. - Oct. 2013), PP 01-12
www.iosrjournals.org
www.iosrjournals.org 1 | Page
Financial Performance Analysis of PT PLN Java-Bali Power 2
(PJB2) In Order Execution Go Public
Aminullah Assagaf
Department of Master Management, Post Graduate Program, University Dr. Sutomo Surabaya,
East Java, Indonesia
Abstract: The purpose of research is the study of financial indicators to ensure the success of PT PLN PJB2 go
public, and identify the factors that influence financial performance. Besides, it presents an alternative wisdom
to improve the financial performance of PT PLN PJB2.
The data used are time series data to study the function of electricity demand Java-Bali system, while
the analysis of the financial performance using financial statement data from 1995 to 1997 and the action plan
of the data companies (CBP) in 1998.
The results showed that: The financial performance is quite healthy in terms of liquidity and solvency.
But in terms of collection of accounts receivable activity showed stunted terms of profitability shows that the
financial performance of PT PLN PJB2 relatively very low compared to other companies that have successfully
gone public. PJB2 PT PLN's financial performance in 1996 and 1997 show a return on equity (ROE) 5.71% and
2.29%, while return on assets (ROA) 4.78% and 1.85%. In comparison PT Indosat financial performance in
1997 showed 20.36% ROE and ROA 18.31%. While the cost structure of PT PLN PJB2 shows that contribution
margin is still positive, which means that any market share gains led to increase profits and demand projections
indicate that up to 2003 PT PLN PJB2 will grow quite rapidly.
Keywords: Financial Performance, Power Java Bali, Order Execution, Go Public.
I. Introduction.
PT PLN PJB2 that are objects of research studies have generating units , namely Generation Unit
Gresik , Brantas Generation Unit , Power Unit Paiton Cirata Power Unit , Power Unit 2 Muara karang and
business units . and in the study of widely used econometric models , as well as some results of studies that have
been obtained , it forecasts electricity demand is influenced by several factors or independent variables . Several
independent variables used in the study tend to be similar , and different is dependent on the specifics of his
research .
Asia Pacific Institute for Management Development put forward the concept of evaluating the
company's performance in the competitive situation . Of the concept is emphasized that the financial statements
and the balance sheets and profit and loss budget analysis company , the company's financial performance can
be measured via the method of comparison or ratios based on financial data available .
Amarullah (1984 ) use an econometric approach with non- linear models , using the data time series
1970 to 1979 the electricity demand of households in Indonesia, with the result : Ln Y = -1.096 - 0.393 Ln Y /
N - 0.484 Ln XPR + 0.910 Ln EXP
where Y demand for electric power sector in Indonesian households , Y / N income per capita , XPR average
price per kWh and EXP residents who have power .
Zuhal (1985 ) use an econometric model of non- linear approach ( 1n ) based on time series data in 1974
and 1980 the demand for electricity the household sector , the commercial sector and the government sector in
Java ( RCELWJT ) with the result : RCELWJT Ln = -20 + 0.72022 Ln HHEX
Where HHEX is household consumption expenditure . In the industrial sector, manufacturing Java
using gross domestic product ( MFIO ) as independent variables that affect the demand for electricity with the
result : INELWJT Ln = -1925.8 + 3.9473 Ln MFIO PLN electricity demand study area VIII South Sulawesi
Tenggara by Aminullah A (1994 ) using non-linear models with cross section data and time series of data on the
household sector , the business sector , industrial sector and hospitality sector . The variables used were
electricity rates , population growth , the installed power of consumers , income per capita and the proportion of
the overall cost of electricity costs incurred concerned consumers .
study of the electricity demand in the United States by Thomson , WF (1976 ) forecast electricity
demand based on data time series 1964 to 1974 with non- linear regression models . The independent variables
used are the growth of gross national product ( GNP ) for 1975 projected demand up to the year 2000 . Demand
scenarios presented in the study are high growth , moderate growth and low growth .
Bangladesh's power demand studies by Russell and Richard (1982 ) using a time series of data to
project the demand for Bangladesh's power until 1994 . The independent variables used in the model are
2. Financial Performance Analysis of PT PLN Java-Bali Power 2 (PJB2) In Order Execution Go Public
www.iosrjournals.org 2 | Page
economic growth and changes in the level of production of each sector such as agriculture , industry , transport
sector , domestic sector , trade and service sectors .
Study of electricity demand by Brazil Cascavel City Munasinghe , M ( 1979 ) using a time series of
data with non- linear models . The independent variables used to project earnings power demand of household
sector , industrial sector , the business sector , the government sector and the social sector .
II. Methods.
Based on several studies will be electricity demand both domestically and in several other countries ,
so in this study used three independent variables to project the demand for Java-Bali power system , the
installed power consumers ( X1 Power ) , gross regional domestic product ( X2PDRB ) and development
population ( X3PDDK ) . The data used are time series in 1980 and 1996 with non- linear models as follows :
YKWHi Ln = Ln Ln X1 Power B0 + B1 + B2 + B3 XPDRBi Ln + Ln X3PDDKi Ui
Where YKWHi Java-Bali electricity demand in the observations to and is the observation error
variable to . The estimation results are used for forecasting electricity demand Java Bali , is then used to
calculate the share of energy demand that will be included in the financial projections of PT PLN PJB2 .
Estimation results according to the data .
The data used in the study are derived from secondary data in accordance with the reported financial
information periodically and financial projections for the medium and long term . Utilization statistics PLN
Java-Bali in particular to gain an overview of the potential demand and the possibility of growth in the future .
The method used for the analysis of financial performance problem solving PT PLN PJB2 , namely :
financial ratio analysis to go public as follows : 1 . Liquidity Ratios, 2 . Activity ratio, 3 . Solvency ratio
(Leverage ), 4 . Profitability ratios ( profitability ).
While the approach of structural analysis in terms of cost and tariff structure projected demand faced
by PT PLN PJB2 . were used , namely : Analysis of the cost structure that reflects the variable costs and fixed
costs in relation to determination of the transfer pricing used in this case contribution margin analysis and
breakeven analysis or break-even point .
a. Analysis contribution margin ( CM ) or variable costing, b. Analysis regression , is used to measure the
influence of independent variables on the demand for electric power .
Exchange rate selected in the determination of the research is at a reasonable level and according to the
variations that have occurred since made the action plan of the company ( CBP ) PT PLN PJB2 until March
1998 , to select the interval between $ 1 = USD $ 3200 up to $ 1 = Rp 10,000 .
ROE is selected in the sensitivity analysis is the variation between 15 % and 20 % , while ROA been
between 10 % and 15 % as company experience who have successfully gone public as PT Telkom and PT
Indosat . Electricity sales tariff or transfer pricing from the scenario depicted is the break even point conditions ,
specific ROE and ROA at various dollar exchange rate ( USD ) .
III. Analysis Of Financial Performance Pt Pln Java Bali Electricity Generation 2 (Pjb2).
Financial Ratio Analysis
In a comparative analysis will be shown in two consecutive periods, namely 1996 and 1997. Financial
statement data are used for 1996 based on audited by Public Accountant Drs. Hadi Sutanto & Partners, while the
1997 data before the audit.
Liquidity levels
This ratio is intended to assess the company's ability to pay short-term debt at maturity by using current assets
available.
(a) Current ratio is obtained by comparing current assets to current liabilities
current assets
Current Ratio = --------------------
current liabilities
- Year 1996 =
165853261
358114684
..
..
x 100% = 261,26%
-Year 1997 =
154218455
691150839
..
..
x 100% = 184,34%
Ability to pay short-term debt of PT PLN PJB2 declined in 1997, but still within reasonable limits or
liquid enough as it is still above 100%.
Quick ratio or acid test ratio, which does not take into account in assessing the inventory with the
inventory comparison:
current assets-inventory
Quick ratio = -------------------------------
current liabilities
3. Financial Performance Analysis of PT PLN Java-Bali Power 2 (PJB2) In Order Execution Go Public
www.iosrjournals.org 3 | Page
- Year 1996 =
165853261
69576064358114684
..
.. ..
x 100% = 236,53%
- Year 1997 =
154218455
414001107691150839
..
.. ..
x 100% = 160,83%
Though not take into account the inventory, but PT PLN PJB2 still quite liquid or above 100%. Cash
ratio, liquidity is assessed only by taking into account the company's cash by comparison:
cash
Cash Ratio =-----------------------------------
current liabilities
- Year 1996 =
165853261
44503586
..
..
x 100% = 32,86%
- Year 1997 =
154218455
94364798
..
..
x 100% = 21,67%
PT PLN PJB2 have cash ratio is relatively small, but the level of liquidity do not need to worry if
supported with good cash flow plan.
Activity level
Asset turnover, measures the ability of the company increased sales turnover as well as to accelerate the return
of assets.
annual sales
Asset turn over =------------------------------------
assets (average)
- Year1996 =
273365405268751812046
0362150302
/)......(
...
= 0,33 kali
- Year 1997 =
287518120462017271946
3806880512
/)......(
...
= 0,33 kali
An increase in sales of 1.06%, but due to the addition of assets that is proportional to the increase in
sales, so the turnover rate remains 0.33 times or it will take about 3 years to reach the same once the turnaround
or sale of assets. It seems that PT PLN PJB2 1997 still experiencing difficulties in increasing sales turnover,
although the potential generating capacity is still sufficient demand to absorb greater amounts. Capacity factor
until the end of 1997, only around 60%.
annual credit sales
Account receivable turn over =------------------------------------
accounts receivable (average)
- Year 1996 =
281840031792547515
0362150502
/)....(
...
= 7,42 kali
- Year 1997 =
2792547515100478575
3806880512
/)....(
...
= 3,76 kali
Accounts receivable collection performance in 1997 decreased, this happens because the PT PLN PJB2
not received payment of receivables from PT PLN (Persero). Average age of accounts receivable, accounts
receivable reflects the billing period in one year.
average (receivables)
Average of account receivable =----------------------------------------x 365 day
The median sales
Year 1996 =
0362150302
281840031792547515
...
/)....(
x 365 = 49,17 day = (50 day)
Year 1997 =
3806880512
2792547515100478575
...
/)....(
x 365 = 97,05 day = (98 day).
1997 billing period increased from 50 days to 98 days, resulting in the deposition of about 3 months
sales of funds that have not been transferred from PT PLN (Persero) PT PLN to PJB2.
inventory usage year
Inventory turn over =---------------------------------------------
average (inventory)
4. Financial Performance Analysis of PT PLN Java-Bali Power 2 (PJB2) In Order Execution Go Public
www.iosrjournals.org 4 | Page
- Year1996 =
242386112196576064
83695268
/)....(
..
= 0,74 time
- Year 1997 =
269576064414001107
48218964
/)....(
..
= 0,75 time
Because turnover is less than one, then the average PT PLN PJB2 warehouse inventory exceeds
demand year. On certain types of material possible slow-moving due to emergency reasons or just in case, the
procurement process is relatively long, the default engine spare parts at the time of construction and so on.
Average age of inventory, which measures how long it takes for each inventory turnover.
average inventory x 365
Average age of inventory =------------------------------------------
inventory usage year
Year 1996 =
83695268
242386112169576064
..
/)....(
x 365 = 493,94 day (494 day)
Year 1997 =
48218964
249576064414001107
..
/)....(
x 365 = 488,34 day (489 day)
Although the amount of usage declined in 1997, but the average inventory is lower than the previous year, so
that the deposition of funds PT PLN PJB2 on warehouse inventory shorter time than in 1996.
Solvency levels (Leverage)
These ratios measure the company's ability to restore all its financial obligations. Financial ratios are
often used in analyzing the level of leverage, namely: Debt ratio, comparing the amount of debt with the rest of
the company's assets.
total debt
Debt ratio =--------------------------- x 100%
total assets
- Year 1996 =
8751812046
6659440741
...
...
x 100% = 17,33%
- Year 1997 =
2017271946
3261181771
...
...
x 100% = 19,00%.
Guarantee assets of all financial obligations of PT PLN PJB2 quite high, due to the relatively small percentage.
The increase in the percentage in 1997 is not very meaningful, and the company is still in a position very
solvable. Debt equity ratio, shows a comparison between the long-term debt with its own capital.
long-term debt
Debt equity ratio =--------------------------------------x100%
equity
- Year 1996 =
2102371295
500900813
...
..
x 100% = 15,85%
- Year 1997 =
8756080175
172900721
...
..
x 100% = 14,39%
In 1997 the number of long-term debt is lower, so the percentage is down. The figure shows that the position of
long-term debt is relatively very small compared to the model itself PT PLN PJB2.
Debt to total capitalization, shows how much the company's long-term capital financed by long term
debt
long-term debt
Debt to total capitalization =--------------------------------------------
long-term debt + capital
- Year 1996 =
2102371295500091813
500091813
.....
..
x 100% = 13,68%
- Year 1997 =
8756080175172900721
172900721
.....
..
x 100% = 12,58%
Contribution of long-term debt of PT PLN PJB2 to total capitalization is relatively very small, even in
1997 fell 1.10% over the previous year.
Time interest earned, to measure a company's ability to pay interest on the loan.
5. Financial Performance Analysis of PT PLN Java-Bali Power 2 (PJB2) In Order Execution Go Public
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operating profit + Depreciation
Time interest earned =-----------------------------------------
interest on loans.
- Year 1996 =
56263669
603028335082039363
..
....
= 10,12 time
- Year1997 =
44070663
208702335873514174
..
....
= 8,01 time
Despite the advantages of PT PLN PJB2 down in 1997, but the ability to pay the interest is still quite large. Debt
service coverage, measures the company's ability to pay interest and principal.
Operating profit + depreciation
Debt service coverage =----------------------------------------------
interest on loans + installment loans
- Year 1996 =
4676039856263669
603028335082039363
....
....
= 4,15 time
- Year 1997 =
6859689644070663
208702335873514174
....
....
= 3,18 time
PT PLN PJB2 profit decline in 1997 did not significantly affect the ability to pay interest and debt repayments.
Profitability levels
There are several measurements of the profitability of the company, each of which is associated with
the measurement of assets, equity, and sales. Of measurement, enabling the ability to analyze the level of profit,
economic profitability, measures the ability of the operation to restore the assets invested in the company.
operating profit
Economic profitability =----------------------------------------x 100%
assets (average)
- Year 1996 =
273365405268751812046
082039363
/)......(
..
x 100% = 5,92%
- Year 1997 =
287518120462017271946
873514174
/)......(
..
x 100% = 2,82%
1997 operating profit decline in the ability of PT PLN PJB2 investment returns. This is mainly due to higher
operating costs as the impact of monetary shocks, where the natural gas fuel purchased with dollars (USD) from
Pertamina. While the contribution of natural gas fuel costs account for about 72.44% of the total fuel costs in
1997.
Return on equity (ROE), which measures the level of benefits available to owners of the company
either as holders of common stock and preferred shareholders.
net profit
Return on equity (ROE) =-----------------------------------x 100%
equity
- Year 1996 =
2102371295
237849292
...
..
x 100% = 5,71%
- Year 1997 =
8756080175
307812114
...
..
x 100% = 2,29%
The ability to obtain a net profit of PT PLN PJB2 relatively very small, especially when compared with the
general interest rate on average in the bank. Dropped dramatically in 1997 over the previous year, making it
difficult to successfully go public when transfer pricing remains USD 82 per kWh.
Return on investment (ROI), measures the overall ability of the company to generate profits to return
the investments made in the company's assets.
net profit
Return on investment (ROI) =------------------------------------------ x 100 %
assets (average)
- Year 1996 =
273365405268751812046
237849292
/)......(
..
x 100% = 4,78%
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- Year 1997 =
287518120462017271946
307812114
/)......(
..
x 100% = 1,85%
Investment capability generate profits in 1997 is relatively small, so that the average PT PLN PJB2 it took about
54 years to recover the investment, while the age of the assets is only about 25 years old.
Return on investment with Du Pont system, measures the ability of an investment to benefit by
multiplying the net profit margin and total asset turnover.
net profit sale
Return on investment (ROI) = ----------------- x --------------------------
sale assets
- Year 1996 =
0362150302
237849292
...
..
x
8751812046
0362150302
...
...
= 4,72%
- Year 1997 =
3806880512
307812114
...
..
x
2017271946
3806880512
...
...
= 1,85%
Return on investment calculation results in the usual manner to item (c) above is similar to Du Pont formula, the
result is the same even in 1997 is 1.85%.
Operation margin, measuring the level of operating profit (pure profit) every dollar generated from the
sale of the company
operating profit
Operating profit margin =------------------------------- x 100 %
sale
- Year 1996 =
0362150302
082039363
...
..
x 100% = 17,88%
- Year 1997 =
3806880512
873514174
...
..
x 100% = 8,51%
Operating profit generated by each sale of PT PLN PJB2 dollars, it is very small even in 1997 only reached
8.51%, down sharply from the previous year.
Table 1. Overview of Income (Loss) of 1996 and 1997 PT PLN PJB2
information Year 1997 Year 1998
PRODUCTION AND SALES:
a. MWh production 26,019,858 25,744,095
b. MWh sold (96.07%) 25,020,590 24,758,720
- Fuel energy sources 2,828,409 1,513,552
- Fuel energy water 1,730,592 2,528,451
- Natural gas energy sources 16,314,648 16,644,783
- Coal energy sources 4,146,941 4,071,934
c. MWh own use 936,890 934,877
d. transformer losses 62,378 50,498
e. The average selling price of (Rp/kWh) 82 82
Operating income:
- Sales of electric power 2,051,688,380 2,030,215,040
Number of Operating Income 2,051,688,380 2,030,215,040
Operating costs:
a. Cost of fuel and M. lubricants 1,370,190,851 1,163,463,688
- Fuel oil 217,676,479 145,511,234
- lubricant 723,836 446,626
- water 6,692,583 9,897,730
- natural gas 992,597,772 857,652,165
- coal 152,500,181 149,955,933
b. Maintenance costs: 88,727,688 91,301,763
- Material 64,189,482 68,952,836
- service 24,538,206 22,348,927
c. staffing costs 57,905,614 53,430,504
d. administrative costs 24,647,145 23,951,396
e. depreciation expense 335,702,209 335,028,603
Total Cost of Operations 1,877,173,507 1,667,175,954
Operating Income 174,514,873 363,039,086
Income (charges) Outside Operation:
- income 10,574,697 7,502,884
- other costs (6,570,823) (8,056,167)
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- interest on loans (63,706,440) (69,636,562)
Total Revenues (Costs) Outside Operations (59,702,566) (70,189,845)
Profit (Loss) Current Year 114,812,307 292,849,241
Sources: Annual Report of PT PLN PJB2 Calculation of 1996 and 1997
Table 2. Balance Sheet As of December 31, 1996 and 1997 PT. PLN PJB 2 (in thousands of dollars)
information 31 Des 1997 31 Des 1996
ASSETS
Fixed assets (gross) 5,978,398,483 5,841,545,983
accumulated depreciation (756,714,452) (425,955,519)
Fixed assets (net) 5,221,684,031 5,415,590,464
Work in the implementation of 29,224,203 6,823,759
other assets 104,668,276 97,653,294
current assets:
- Cash and banks 98,647,943 86,035,445
- claim 575,478,100 515,567,076
- Fuel and maintenance materials 107,001,414 64,760,695
- Other current assets 58,023,234 17,751,142
Total current assets 839,150,691 684,114,358
TOTAL ASSETS 6,194,727,201 6,204,181,875
CAPITAL AND LIABILITIES
: equity
- paid-in capital 3,000,000,000 3,000,000,000
- Additional paid-in capital 1,821,579,121 1,821,579,121
- Retained earnings 196,029,754 307,658,089
Amount of own capital 5,017,608,875 5,129,237,210
: Long-term liabilities
- Long-term liabilities 715,827,348 813,091,500
- Other long-term liabilities 6,072,824
Number of long-term liabilities 721,900,172 813,091,500
Short-term liabilities 455,218,154 261,853,165
TOTAL CAPITAL AND LIABILITIES 6,194,727,201 6,204,181,875
Sources: Annual Report of PT PLN PJB2 Calculation of 1996 and 1997
Analysis of Cost Structure and Rates
PT PLN's operating cost structure PJB2 1997 shows the contribution of each component of these costs,
namely fuel and lubricating oil 72.99%, 4.73% maintenance costs, personnel costs 3.08%, 1.31% other
administrative costs and cost of depreciation of fixed assets 17.89%.
Analysis of the connection between the structure and the cost of electricity sales tariff PT PLN PJB2
can use contribution margin approach and breakeven analysis. Of the analysis can be described levels of
profitability and performance of PT PLN PJB2 especially in the development of cost-efficiency and power sales
tariff policy. While the selling price per kWh of Rp 82, so still a positive contribution margin was calculated as
follows:
- Year 1996 = Rp 82 – Rp 50,68 = Rp 31,32.
- Year 1997 = Rp 82 – Rp 58,31 = Rp 23,69.
Differences in variable costs in 1996 and 1997 primarily due to (a) differences in the composition of the
generators, (b) the monetary turmoil since July 1997 that impacted on the price of natural gas and the cost of
spare parts for machinery maintenance and (c) the cost of fuel between machines -generating machines differ
from one another either because of capacity and production volume.
Fuel per kWh according to the type of plant appropriate accounting data and reports produced by PT PLN
PJB2 1996 and 1997, ie
Year 1996 (Rp) Year 1997 (Rp)
- - Generation by Fuel 96,14 76,96
- - Generation with water 3,91 3,87
- - Generation with natural gas 51,53 60,84
- - Generation with coal 36,83 36,77
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Cost difference indicates that the engine is generating the most inexpensive hydroelectric power
(hydropower), following a steam power plant (CPP) of coal, gas power plants and steam (combined cycle) with
fuel and combined cycle natural gas with fuel oil.
Breakeven analysis or break-even point, showing the conditions in which the company does not make a
profit and a loss. Of accounting data and reports the amount of production can be calculated breakeven in 1996
and 1997 as follows:
breakeven = TR = TC
PQ = FC + VQ
PQ – VQ = FC
Q (P – V) = FC
Q =
)VP(
FC
where Q sum kWh sales at the break-even point, fixed costs FC, P and V price kWh variable costs per kWh.
Breakeven in 1996:
Q =
)68,5082(
)603.028.335396.951.23504.430.53(
=
32,31
503.410.412
Q = 13.167.641 MWH
Breakeven in 1997:
Q =
)68,5082(
)209.702.335145.647.24614.905.57(
=
68,23
968.254.418
Q = 17.662.794 MWH
Sales of electric power in a period of two consecutive years, namely:
- Year 1996 = 24.758.720 MWH
- Year 1997 = 25.020.590 MWH
Breakeven in 1997 shifted the MWH larger amount than in 1996 because of the financial turmoil which
resulted in the rising cost of natural gas fuel and engine maintenance cost of spare parts.
For two consecutive years PT PLN PJB2 production above the breakeven point, so there is no advantage
because the excess price above variable costs are still able to cover all fixed costs. But in 1998, PT PLN PJB2
difficult to produce above the break-even when viewed in the action plan of the company (CBP) as follows:
Breakeven in 1998:
Q =
)22,6982(
)293.340.442525.136.27766.314.58(
=
78,12
584.791.527
Q = 41.298.246 MWH
Table 3. Earnings (Loss) unit kWh in 1996 and 1997 PT PLN PJB2
information Year 1996 Year 1997
PRODUCTION AND SALES:
a. MWh production 26,019,858 25,744,095
b. MWh sold (96.07%) 25,020,590 24,758,720
- Fuel energy sources 2,828,409 1,513,552
- Water energy sources 1,730,592 2,528,451
- Natural Gas energy sources 16,314,648 16,644,783
- Coal energy sources 4,146,941 4,071,934
c. MWh own use 936,890 934,877
d. shrinkage transformer 62,378 50,498
e. The average selling price (Rp. / kWh) 82 82
Operating income:
- Sales of electric power 82 82
Number of Operating Income 80 82
Operating costs:
a. Cost of fuel and M. lubricants 54.76 46.99
- Fuel oil 76.96 96.14
- lubricant 0.03 0.02
- water 3.87 3.91
- natural gas 60.84 51.53
- coal 36.77 36.83
b. Maintenance costs: 3.55 3.69
- Material 2.57 2.78
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- service 0.98 0.90
c. staffing costs 2.31 2.16
d. administrative costs 0.99 0.97
e. depreciation expense 13.42 13.53
Total Cost of Operations 75.03 67.34
Operating Income 6.97 14.66
Income (charges) Outside Operation:
- income 0.42 3.00
- other costs (0.26) (0.33)
- interest on loans (2.55) (2.81)
Total Revenues (Costs) Outside Operations (2.39) (2.83)
Profit (Loss) Current Year 4.59 11.83
Sources: Annual Report of PT PLN PJB2 Calculation of 1996 and 1997
Electricity Demand Projections
Table 4. Projected Demand Java-Bali Power Year 1997 - 200
Year power PDRB population MWh
1997 26,270,760 319,232,593 117,682,647 45,108,463
1998 29,693,840 332,576,515 119,000,693 49,084,239
1999 33,562,948 346,478,214 120,333,500 53,410,431
2000 37,936,200 360,961,003 121,681,236 58,117,927
2001 42,879,287 376,049,173 123,044,065 63,240,330
2002 48,466,458 391,768,028 124,422,160 68,814,216
2003 54,781,638 408,143,932 125,815,687 74,879,370
Source: Statistics of PT PLN (Persero) Year 1980-1996, the data is processed
Sensitivity Analysis.
Component of operating expenses in 1998 of PT PLN PJB2 converted to USD exchange rate at the
beginning of the preparation conditions of the action plan of the company (U.S. $ 1 = Rp 3,200), the
maintenance cost of Rp 66,425,923,000, - and the cost of natural gas fuel Rp 1,131,918,920 .000, -. Such costs
totaled approximately 55.30% of the total operating costs in 1998, and this composition will increase in line
with the increase in the value of the dollar exchange rate.
Loss per kWh is above is not directly linear with the changes in the dollar exchange rate, because the only
change to the cost of maintenance and fuel costs of natural gas. While there are many other factors affecting
income such as rates, other operating income, other operating expenses, operating income and expenses beyond.
Return on equity (ROE) at various dollar exchange rate, will show how much electricity sales tariff
should be treated PT PLN PJB2. Return on equity is recommended to go public is the range in the level of
general interest or ROE refers to companies that have successfully gone public. As a reference according to the
news Bisnis Indonesia on 11 and 18 March 1998 reported that ROE in 1996 and 1997 for PT Indosat,
respectively 20.36% and 21.33%, while the PT TELKOM is 16.95% and 11.95%. In this study selected scenario
ROE 15% and 20% to determine how much the fare should be required PT PLN PJB2 dollar exchange rate at
the various possibilities, namely:
ROE 15% ROE 20%
- Kurs USD ($1 = Rp 3.200) Rp 121,60 Rp 138,49
- Kurs USD ($1 = Rp 7.000) Rp 181,69 Rp 198,57
- Kurs USD ($1 = Rp 8.000) Rp 197,51 Rp 214,39
- Kurs USD ($1 = Rp 9.000) Rp 213,32 Rp 230,20
- Kurs USD ($1 = Rp 10.000) Rp 229,14 Rp 246,02
When the dollar exchange rate of Rp 8,000, the electricity sales tariff PT PLN PJB2 should be adjusted
to 140.87% increase in ROE 15% and 161.45% increase in ROE 20%. If ROE is a benchmark as we have done
PT Indosat and PT Telkom, PT PLN PJB2 difficult to go public, because of the tariff adjustment was not
possible under current conditions. Chooses ROA 5% and 10%, due to age or economic depreciation calculation
based PT PLN PJB2, which on average ranged from 10 years to 20 years. And as a reference ROA in 1996 and
1997 were achieved PT Indosat, respectively 18.31% and 18.11%, while the PT TELKOM reached 8.45% and
5.77%. Rates are to be treated on the ROA of 5% and 10% at various dollar exchange rate, namely:
ROA 5% ROA 10%
- Kurs USD ($1 = Rp 3.200) Rp 100,64 Rp 122,37
- Kurs USD ($1 = Rp 7.000) Rp 160,74 Rp 182,46
- Kurs USD ($1 = Rp 8.000) Rp 176,55 Rp 198,28
- Kurs USD ($1 = Rp 9.000) Rp 192,37 Rp 214,09
- Kurs USD ($1 = Rp 10.000) Rp 208,18 Rp 229,91
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When the desired return on assets or investments for 10 years (ROA 10%), then the exchange rate of U.S. $ 1 =
Rp 8,000 should be charged a rate of $ 198.28 per kWh or need an increase of about 141.80% from a rate of $
82, - in effect now.
When connected between ROA and ROE, then the results can be compared as follows
ROE (%) ROA (%)
- Laba Rp 989.326 juta 15,00 9,83
- Laba Rp 1.389.046 juta 20,00 13,38
- Laba Rp 463.077 juta 7,85 5,00
- Laba Rp 977.407 juta 15,24 10,00
And so on the various possible rates of exchange prevailing when connected between ROA and ROE, which is
smaller than ROA ROA.
Table 5. Projected Balance Sheet As of December 31, 1998 PT PLN PJB2 (in thousands of rupiah)
information 31 Des 1998
ASSETS
Fixed assets (gross) 8,748,626,394
accumulated depreciation (1,179,661,860)
Fixed assets (net) 7,568,964,534
Work in the implementation of 54,000,000
other assets 120,722,732
Investments in subsidiaries 24,800,000
Current assets:
- Cash and banks 109,480,209
- claim 346,158,176
- Fuel and maintenance materials 70,764,459
- Other current assets 39,904,043
Total current assets 566,306,887
TOTAL ASSETS 8,334,794,153
CAPITAL AND LIABILITIES
Equity capital:
- paid-in capital 3,000,000,000
- Additional paid-in capital 2,329,708,946
- retained earnings 106,476,154
- Profit for the period (463,672,190)
Amount of own capital 4,972,512,910
Long-term liabilities:
- Long-term liabilities: 2,693,195,787
- Other long-term liabilities 6,017,986
Number of long-term liabilities 2,699,213,773
Short-term liabilities 663,067,470
TOTAL CAPITAL AND LIABILITIES 8,334,794,153
Sources: Company Budget Plan (CBP) 1998 PT PLN PJB2
IV . Conclusion
Data analysis based on the description above , then the following can be inferred , namely :
Financial performance , PT PLN PJB2 reflect an adequate level of liquidity with current ratio above
200 % . In terms of activity , it is relatively small asset turnover , receivables turnover less current so as to
achieve approximately three months arrears of sales , warehouse inventory piling or exceed the needs of an
average of one year . Performance solvency or leverage is strong enough that the debt equity ratio is only about
15 % , which means the lender is guaranteed . Very low level of profitability , especially in 1997 , which is only
about 2.29% ROE and 1.85 % ROA . This complicates the position of PT PLN PJB2 to go public , because it is
still far from the expected profitability levels of ROE around 15 % per year .
Factors that influence , the poor performance of PT PLN PJB2 profitability mainly due to the limited
market share , cost structure and sale of electricity tariff . Positive contribution margin in 1996 and 1997 ,
showed that each increase market share or sales will increase profits . Market share held by PT PLN PJB2 1997
has surpassed the point of break -even point , which means more and increase profit increase sales . The cost
structure of generation centers showed that hydropower is the cheapest , followed by power plant coal, natural
gas combined cycle and combined cycle oil . While electricity sales tariff has been determined since the
establishment of PT PLN PJB2 , apparently has never been reviewed, although PT PLN ( Persero ) has made
several automatic tariff adjustment ( ETAM ) to consumers .
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Projected demand , power Java - Bali system increased by about 66 % until the end of 2003 , and in the
same period the market share of PT PLN PJB2 increased by approximately 44.37 % . To reach the point of
break even point in 1998, the share of PT PLN PJB2 demand must be increased approximately 65.06 % if the
electricity sales tariff of Rp 82 per kWh is not adjusted .
Monetary shocks , which occurred since July 1997 , led to the financial performance declined
compared to 1996. And the various possibilities dollar exchange rate prevailing in 1998, showed that the PT
PLN PJB2 will experience losses . Electricity sales tariff under conditions break even point at about Rp 101.58
per kWh in the USD exchange rate of Rp 3,200 ( initial condition of planning ) , and Rp 177.49 per kWh in the
USD exchange rate of Rp 8,000 . When the desired level of ROE is 15 % , the electricity sales tariff of Rp
197.51 per kWh in the USD exchange rate of Rp 8,000 .
V. Suggestion
From the analysis above, it can be concluded as follows: To improve the profitability of PT PLN PJB2
advised to review the sale of electricity tariff charged to PT PLN P3B. With a high ROE allow successful public
offering and the results back to PT PLN (Persero) as a shareholder to meet the needs of investment funds.
Generating capacity owned by PT PLN PJB2 only reached about 60% capacity factor and are still more
likely to increase sales. It is recommended for optimal capacity utilization in order to increase the profitability of
the company. Operation of the centers of power to be made according to priority level operating cost efficiency,
and should take into account the constraints of operating in order to avoid excessive unemployment capacities.
Wisdom of the discount rate on excess market share given by PLN P3B as an alternative to improve the
utilization of excess capacity. Recommended for adoption by the discount rate to a greater extent than the
variable cost per kWh or contribution margin is positive, because the company is still profitable.
To anticipate things that may have an adverse effect on the financial performance of PT PLN PJB2, it
is suggested that the financial projections with various scenarios relevant to benchmark the financial wisdom
particularly with respect to rates, capital structure, capital expenditure and operating cost structure
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