An estimate of the cost of electricity outages in Zimbabwe
- Authors: Kaseke, Nyasa
- Date: 2012
- Subjects: Electric power failures -- Zimbabwe , Electric utilities
- Language: English
- Type: Thesis , Doctoral , DCom
- Identifier: vital:8997 , http://hdl.handle.net/10948/d1011119 , Electric power failures -- Zimbabwe , Electric utilities
- Description: This thesis estimates the cost of electricity outages in Zimbabwe for the year 2009. Much reference is made to government, the power utility - Zimbabwe Electricity Supply Authority (ZESA) and other countries in the Southern African Power Pool (SAPP), also experiencing electricity outages. An electricity outage is a complete loss of power supply to an area. An outage may result from planned or unplanned load shedding or faults. Load shedding is accelerated by power supply shortages. The shortages are experienced during peak demand times. In 2009, Zimbabwe’s peak demand was about 1574MW. ZESA had the capacity to supply 1080MW and imported 100MW (guaranteed from Mozambique), leaving a shortfall of 394MW. This shortfall is worsened by transmission losses (about 108MW) and consumption by ZESA properties (about 200MW) bringng down the supply to customers of about 700MW. The supply shortage is the result of a lack of investment in the power sector by government for expanded generation capacity, incorrect pricing, droughts, internal conflicts, skills flight, government energy sector regulation, vandalism of equipment and under supply of coal to thermal power stations. Consumers in all sectors are experiencing power outage incidences of different duration. The severity of the inconvenience depends on the load shedding time table, preferences of the power utility and arrangements that can be made with the utility. Power outages negatively affect (and result in cost to) the productive sectors (industry, mining and farming) and households. The main objective of the thesis is to estimate the cost of power outages to the sectors. Sub-objectives of the study include: to identify the main features of power crisis in Zimbabwe and government response to it with a regional power generated setting; to formulate a model that clearly identifies the different cost components of power outages in Zimbabwe; to identify appropriate methods by which to estimate these cost components; to estimate the cost of power outages to the productive sectors (mining, agriculture and industrial) and households of Zimbabwe; to critically analyse the credibility of these estimates, and to consider the saving of the costs of outages achieved through increased investment in generating capacity in Zimbabwe. ZESA undertook reforms (institutional and tariff) in order to improve management efficiencies and supply. It was divided into five entities resulting in management and financial improvement, but its reform of tariffs has been stiffled by subsidies and price regulations. ZESA adopted the cost plus rate of return pricing strategy in 2004 but regulation kept the tariff below cost. The regulation is pro-poor in aim but it encourages wasteful consumption. Similar supply shortages are affecting the whole SAPP group. The power pool load shed 758MW in 2009. In Zimbabwe alone load shedding was 315MW. In an attempt to solve the problem, member utilities engage in bilateral contacts and short-term trading through Short Term Energy Markets (STEM). A number of Southern African countries have to load shed - the average frequency being three to five (3-5) times per week for the region. A number of studies have been carried out by different scholars attempting to assess the impact and cost of outages. The general conclusion is that power outages cause significant costs to consumers, both direct and indirect. From a global perspective, the increase in the quality of electricity supplied has fallen behind the increase in quantity demanded, causing an increase of incidence in power outages. An analysis of Sub-Saharan Africa shows that the causes of supply shortages are natural (drought), oil price shocks, conflict and the lack of investment in generation capacity. This generates two outage cost estimates – a direct cost (welfare loss) and indirect cost (backup cost). The sum of these estimates is the total outage cost. The direct cost estimate is based on direct loss incurred during the power outages - lost production, lost materials, and lost time or leisure. In order to derive an estimated direct cost, it is necessary to obtain an accurate respondent self-assessment, which, in turn depends on the keeping of good records of hours of outages and losses incurred during outage times. The estimated indirect cost (backup cost) is derived from the cost of investment in backup sources and running of these sources as a mitigating measure during a power outage. The expected gain from self-generated kWh is assumed to be equal to the expected loss from the marginal kWh electricity not supplied by the utility (the outage). The annualised capital cost of backup source plus the variable cost of generating electricity by the backup source are another element of the cost of power outages. The prices of backup sources were obtained from the two leading retailers, Tendo Power and Ellis Electronics. To the extent that the captive generation includes investment in emergency or optional plant (as part of normal production infrastructure), it may overestimate cost.
- Full Text:
- Date Issued: 2012
- Authors: Kaseke, Nyasa
- Date: 2012
- Subjects: Electric power failures -- Zimbabwe , Electric utilities
- Language: English
- Type: Thesis , Doctoral , DCom
- Identifier: vital:8997 , http://hdl.handle.net/10948/d1011119 , Electric power failures -- Zimbabwe , Electric utilities
- Description: This thesis estimates the cost of electricity outages in Zimbabwe for the year 2009. Much reference is made to government, the power utility - Zimbabwe Electricity Supply Authority (ZESA) and other countries in the Southern African Power Pool (SAPP), also experiencing electricity outages. An electricity outage is a complete loss of power supply to an area. An outage may result from planned or unplanned load shedding or faults. Load shedding is accelerated by power supply shortages. The shortages are experienced during peak demand times. In 2009, Zimbabwe’s peak demand was about 1574MW. ZESA had the capacity to supply 1080MW and imported 100MW (guaranteed from Mozambique), leaving a shortfall of 394MW. This shortfall is worsened by transmission losses (about 108MW) and consumption by ZESA properties (about 200MW) bringng down the supply to customers of about 700MW. The supply shortage is the result of a lack of investment in the power sector by government for expanded generation capacity, incorrect pricing, droughts, internal conflicts, skills flight, government energy sector regulation, vandalism of equipment and under supply of coal to thermal power stations. Consumers in all sectors are experiencing power outage incidences of different duration. The severity of the inconvenience depends on the load shedding time table, preferences of the power utility and arrangements that can be made with the utility. Power outages negatively affect (and result in cost to) the productive sectors (industry, mining and farming) and households. The main objective of the thesis is to estimate the cost of power outages to the sectors. Sub-objectives of the study include: to identify the main features of power crisis in Zimbabwe and government response to it with a regional power generated setting; to formulate a model that clearly identifies the different cost components of power outages in Zimbabwe; to identify appropriate methods by which to estimate these cost components; to estimate the cost of power outages to the productive sectors (mining, agriculture and industrial) and households of Zimbabwe; to critically analyse the credibility of these estimates, and to consider the saving of the costs of outages achieved through increased investment in generating capacity in Zimbabwe. ZESA undertook reforms (institutional and tariff) in order to improve management efficiencies and supply. It was divided into five entities resulting in management and financial improvement, but its reform of tariffs has been stiffled by subsidies and price regulations. ZESA adopted the cost plus rate of return pricing strategy in 2004 but regulation kept the tariff below cost. The regulation is pro-poor in aim but it encourages wasteful consumption. Similar supply shortages are affecting the whole SAPP group. The power pool load shed 758MW in 2009. In Zimbabwe alone load shedding was 315MW. In an attempt to solve the problem, member utilities engage in bilateral contacts and short-term trading through Short Term Energy Markets (STEM). A number of Southern African countries have to load shed - the average frequency being three to five (3-5) times per week for the region. A number of studies have been carried out by different scholars attempting to assess the impact and cost of outages. The general conclusion is that power outages cause significant costs to consumers, both direct and indirect. From a global perspective, the increase in the quality of electricity supplied has fallen behind the increase in quantity demanded, causing an increase of incidence in power outages. An analysis of Sub-Saharan Africa shows that the causes of supply shortages are natural (drought), oil price shocks, conflict and the lack of investment in generation capacity. This generates two outage cost estimates – a direct cost (welfare loss) and indirect cost (backup cost). The sum of these estimates is the total outage cost. The direct cost estimate is based on direct loss incurred during the power outages - lost production, lost materials, and lost time or leisure. In order to derive an estimated direct cost, it is necessary to obtain an accurate respondent self-assessment, which, in turn depends on the keeping of good records of hours of outages and losses incurred during outage times. The estimated indirect cost (backup cost) is derived from the cost of investment in backup sources and running of these sources as a mitigating measure during a power outage. The expected gain from self-generated kWh is assumed to be equal to the expected loss from the marginal kWh electricity not supplied by the utility (the outage). The annualised capital cost of backup source plus the variable cost of generating electricity by the backup source are another element of the cost of power outages. The prices of backup sources were obtained from the two leading retailers, Tendo Power and Ellis Electronics. To the extent that the captive generation includes investment in emergency or optional plant (as part of normal production infrastructure), it may overestimate cost.
- Full Text:
- Date Issued: 2012
Statistical tools for consolidation of energy demand forecasts
- Authors: Motsomi, Abel Pholo
- Date: 2012
- Subjects: Power resources -- Forecasting , Energy conservation -- Standards , Electric utilities
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:10573 , http://hdl.handle.net/10948/d1011578 , Power resources -- Forecasting , Energy conservation -- Standards , Electric utilities
- Description: The electricity market in the South African economy uses specialised instruments in forecast-ing the energy load to be delivered. The current status quo operates with several forecasters from different offices, departments or businesses predicting for different purposes. This be-comes a challenge to derive a consolidated forecast. This study has attempted to develop a consolidating instrument that will merge all the forecasts from different offices, departments or businesses into one so-called ‘official forecast’. Such an instrument should be able to predict with accuracy the anticipated usage or demand. Article [18] examined patterns across G7 countries and forecasters to establish whether the present bias reflects the inefficient use of information, or whether it reflects a rational re- sponse to financial, reputation and other incentives operating for forecasters. This bias is particularly true for any electricity utility as forecasting is undertaken by different divisions; therefore each division has its own incentives. For instance, the generation division will tend to overstate their forecasts so as that there is no possibility of a shortage, whereas distri- bution (sales) might understate so as to give the impression of being profitable when more units are sold to consumers. Thus, the study attempts to rectify this bias by employing statistical tools in consolidating these forecasts. The results presented in this paper propose a newly developed procedure of consolidating energy demand forecasts from different users and accounting for different time horizons. Predicting for the short-term and long-term involves different measuring tools, which is one aspect of prediction this paper tackles.
- Full Text:
- Date Issued: 2012
- Authors: Motsomi, Abel Pholo
- Date: 2012
- Subjects: Power resources -- Forecasting , Energy conservation -- Standards , Electric utilities
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:10573 , http://hdl.handle.net/10948/d1011578 , Power resources -- Forecasting , Energy conservation -- Standards , Electric utilities
- Description: The electricity market in the South African economy uses specialised instruments in forecast-ing the energy load to be delivered. The current status quo operates with several forecasters from different offices, departments or businesses predicting for different purposes. This be-comes a challenge to derive a consolidated forecast. This study has attempted to develop a consolidating instrument that will merge all the forecasts from different offices, departments or businesses into one so-called ‘official forecast’. Such an instrument should be able to predict with accuracy the anticipated usage or demand. Article [18] examined patterns across G7 countries and forecasters to establish whether the present bias reflects the inefficient use of information, or whether it reflects a rational re- sponse to financial, reputation and other incentives operating for forecasters. This bias is particularly true for any electricity utility as forecasting is undertaken by different divisions; therefore each division has its own incentives. For instance, the generation division will tend to overstate their forecasts so as that there is no possibility of a shortage, whereas distri- bution (sales) might understate so as to give the impression of being profitable when more units are sold to consumers. Thus, the study attempts to rectify this bias by employing statistical tools in consolidating these forecasts. The results presented in this paper propose a newly developed procedure of consolidating energy demand forecasts from different users and accounting for different time horizons. Predicting for the short-term and long-term involves different measuring tools, which is one aspect of prediction this paper tackles.
- Full Text:
- Date Issued: 2012
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