By
Sustainable electric power supply is the prime mover of technological and social development. There is hardly any enterprise or indeed any aspect of human development that does not require energy in one form or the other – electric power, fuels etc. Nigeria is richly endowed with various energy sources, crude oil, natural gas, coal, hydropower, solar energy, fissionable materials for nuclear energy. Yet the country consistently suffers from energy shortage, a major impediment to industrial and technological growth. The National Electric Power Authority (NEPA)1,is responsible for managing the generating plants as well as distribution of power nationwide. The total generating capacity is about 3000MW, approximately thrice the current level of national demand. However, the actual power available at any given time is less that 40 percent of the total capacity due to poor maintenance; hence there is a perennial shortage. This
situation is exacerbated by a grossly inefficient, poorly maintained distribution system. Industries can only cope with power outages by resorting to internal generating plants (Ajanaku 2007; Adegbamigbe 2007).
However, when electricity goes on and off five times in an hour, this creates serious problems for manufacturing and industrial sectors.
Technological infrastructure is an enabling environment required for rapid growth of technological and industrial development and comprises physical and human variables like energy, water, transport, communication, financial and human capital (Chenery 1960; Afonja 2003). Ability to provide and effectively apply these inputs is a direct indicator of the various levels of development worldwide. The role of private sector in providing technological infrastructure varies significantly between nations. On one extreme is the group of nations (for example United States of American) in which the private sector provides virtually all technological infrastructure while at other end is the group in which the government is responsible for nearly all (for example China). In between is a group comprising mainly developing countries which are in varying degrees of transition from public to private ownership of technological infrastructure. Nigeria falls in this last category (Arikpo 1967; Thirlwall 1989).
Power supply in Nigeria is not a recent issue, judging from the fact that electricity was first generated in Nigeria in 1896, just a decade after its introduction in Europe, according to Ubogu (1985). In 1953, the total electricity consumption was only 77 million KW, however, which grew to 4066 million KW hr in 1980. The consumption has been at increase, with increasing population. But unfortunately, the utility company in Nigeria, the PHCN, is not able to meet up with this increasing demand. Nigeria with population of over 140 million was only able to generate about 4000MW as against over 100,000MW needed to transform the economy of the country.
NEPA which until 31st May 2005, a government Parastutal, has the sole responsibility for
managing the generation as well as distribution of power in Nigeria. Although the name was changed to Power Holding Company of Nigeria (PHCN) since 31st May 2005, most people still refer to it as NEPA with interpretation of “Never Expect power Always” instead of National Electric Power Authority. Despite huge capital investment by government in PHCN up to 2008
the parastatal has not been able to satisfy its major objective of supplying the Nigerian public with adequate power.
The objectives of this research are:-
To study the performance and service share of PHCN within Anambra State.
To identify Electric Power supply problems and proffer solutions for improvement through problem-solving techniques.
To develop models for predicting service improvement.
The method used for the solutions to service delivery problems were as follows:
Structured Questionnaires were produced and administered.
Data collection/interviews from target organizations.
Eighteen (18) Cold rooms were sampled in each State.
Work design/ performance modeling.
Work analysis.
Work measurement techniques.
Data analysis and reports.
Table 1. How long do PHCN supply Power/day in Anambra State?
HOURS SUPPLIED PHCN | NO. OF C/ROOMS | PERCENTAGE |
0 – 2 | 3 | 17 |
3 – 8 | 14 | 78 |
9 – 14 | 1 | 05 |
15 – above | Nil | Nil |
Total | 18 | 100 |
About 78% of Cold rooms had PHCN supplies of 3 to 8 hours per day.
5%
17%
78%
Fig. 1. Electric Power supply assessment.
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
1 2 3 4
Fig. 2. Coldroom Assessment of Supplies.
1= supplies 0-2hrs/day; 2= supplies 3-8hrs/day; 3= supplies 9-14hrs/day; 4= supplies 15-above hrs/day.
Table 2. Electric Power Pricing &Demand.
Yr. | N/KW. | ANAMBRA |
2007 | 4 | 249 |
2008 | 4 | 260 |
2009 | 6.8 | 269 |
2010 | 6.8 | 288 |
Table 3. ELECTRIC POWER DEMAND & SUPPLY (2007 – 2010)
DEMAND(MGW) | 2007 | 2008 | 2009 | 2010 |
ANAMBRA | 249 | 260 | 269 | 288 |
SUPPLY(MGW) | 2007 | 2008 | 2009 | 2010 |
ANAMBRA | 129 | 131 | 136 | 136 |
3 𝑥100
24 1
10 𝑥100
24 1
= 12.5%
= 42%
In terms of power supply by PHCN, services rendered range from 12.5% to 42%. The remaining
hours of the day is being covered by use of private generators.
Max hrs of supply to Anambra; 10
24
𝑥100
1
= 42%
Residential average 3
24
𝑥100
1
= 13%
Public Offices = 4
24
𝑥100
1
= 17%
Modeling.
Performance Modeling
If we consider P, to represent Productivity, F to represent Funding, and C to represent Corruption, then Productivity is considered as inversely proportional to corruption. Thus,
P = F/C; 𝑖−𝑥
𝑖
= 𝑃𝑟𝑜𝑑𝑢𝑐𝑖𝑡𝑖𝑣𝑡𝑦
This is supported by productivity and waste equation as shown below:
Productivity,
P = 𝑂�𝑇𝑃𝑈𝑇
𝐼𝑁�𝑈𝑇
= 𝐼𝑁�𝑈𝑇−𝑊�𝑆𝑇𝐸
𝐼𝑁�𝑈𝑇
= 𝑖−𝑋, 𝐴�𝑋⇒ 0
𝑖
When funding increases as corruption increase, performance decreases.
When funding decreases as corruption decrease, performance increases. When funding decreases at slower rate than corruption, P increases.
Cost Modeling.
Average PHCN bill BP = N8.5/kwhr
Average hour of electricity supply by PHCN | AVp | = 7hrs |
Average appliance rating | AVr | = 5kw |
Cost of power provided by PHCN per day | Cp = Bp*A |
Vp*AVr
= 8.5*7*5 = N297.5
Theoretical cost of power provided by PHCN paid per year
= 365*Cp = 365*297.5 = N108587.5
But this cost is subsidized by the Nigerian Government. From the questionnaire recovered the average cost of power provided by PHCN per year = N31,115.8
Generating set energy charge Cg = N22.5/kwhr Average hours of operating generating set AVg = 6hrs
Average Generating set power rating Pr = 6.5hp But 1hp = 750watts, but 1000watts = 1kw
1hp = 750/1000 = 0.75kw
Therefore Pr = 0.75*6.5 = 4.875kw
Cost of operating a generating set in a day = Pr*AVg*Cg
= 4.875kw*6hrs*N22.5/kwhr
= N658.125 per day
Cost of operating a generating set in a year = N658.125*365
= N240215.63 per year
Total cost spent on power per year | T | = | N 240215.63 + N31,115.8 |
T | = | N 271331.43/year |
S/N | Information | Time/charge | |
1. | Average PHCN bill | BP = N8.5/kwhr | |
2. | Average hour of electricity supply by PHCN | AVp = 7hrs | |
3. | Average appliance rating | AVr = 5kw | |
4. | Average cost of power provided by PHCN per year | = N31,115.8 | |
5. | Generating set energy charge | Cg = N22.5/kwhr | |
6. | Average hours of operating generating set | AVg = 6hrs | |
7. | Average Generating set power rating | Pr = 6.5hp = 4.875kw | |
8. | Cost of operating a generating set in a year | N240215.63 per year | |
9. | Total cost spent on power per year | T = N271331.43/year |
4.2 COST ANALYSIS OF PHCN FOR A BUSINESS ENTERPRISE
For a cold room which uses a 20KVA generator
Generator energy charge Eg = N22.5/kwhr
Generator power rating Pr = 20KVA Average hour of operating the generator AVg = 14hrs
Cost of generating power in a day using a generator = Eg *Pr*AVg
= N22.5*20*14
= N6,300 per day Cost of maintenance of the generator in a month = N10,000
Total cost spent on the generator in a year = N (10000*12) + N(6300*365)
= N2.42 million
CONCLUSION. Results showed a poor performance (42%), in Anambea State. Within the areas /towns served by the PHCN, we found reasonable installations. But the very poor manpower attitude remains a cankerworm in the system. In addition to poor manpower attitude to work, response to distress calls were hardly timely.
Within the State, the Cold rooms had up to 33% service share as Residential and Public buildings shared 13% and 17% respectively. Mathematical models were developed for a guide to enhanced Electric power service delivery.
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