Incorporating reliability worth in generation planning

The economic planning of electricity production will try to minimise this economic cost by striking the right balance between electricity production cost (tariff) and supply continuity, as detailed in Figure 10.4.

Consumer interruption cost

Total generating system cost

Fuel and other operational cost

Investment and other fixed costs

Economically optimum continuity Continuity (per cent)

Figure 10.4 Total cost of the power system including cost of interruptions

Such a calculation will indicate the percentage continuity figure that minimises total generation system cost (including interruptions cost), and correspondingly the amount of percentage reserves required to attain such a continuity.

This cost factor is useful for power system planning in order to minimise the system cost to consumers. In such cases, a generation simulation model like that of Figure 10.5 is utilised to assess the expected (cost of generation at a future year [cost of electricity (fixed and operational)+ cost of interruptions to the consumers). Sets are added until the optimum continuity is obtained. This will occur when the above sum is at a minimum. Such simulation is carried out for many years into the future, utilising different generation-extension scenarios, in order to plan a programme for generation strengthening over time.

The same approach applies to the planning and the timing of network strengthen- ing, where the economic cost of electricity supply to a particular area is equal to the cost of energy utilised by the area plus the cost of interruption to the consumers in that area, as caused by network problems. A network-strengthening exercise is carried out to assess the economic cost of each new network-strengthening configuration in order to compute the discounted net benefits of each scheme. The net benefits in this case will be the discounted reduction in consumer economic cost due to interrup- tions plus reduction in losses minus the discounted cost of the network-strengthening scheme (including any other system cost). If these net benefits are positive, then the strengthening scheme is undertaken. It has to be recalled that the discounted reduc- tion in consumer economic cost is equal to the discounted amount of reduced energy curtailment in kWhs multiplied by the average economic (social) cost of each kWh curtailed.

Read: load data

Existing sets and future expansion scenario set details

(Repeat over all possible expansion scenarios)

For year y

(i) Compute operation costs

(ii) Compute investment costs for year ( y) (iii) Compute energy curtailment (kWhy)

multiply by social cost per kWh

Total annual system cost in year y

Sc = (i) + (ii) and (iii)

no no no. of sets j = j+1 Sc < Sc–1 y = Y Y = study period y = y + 1

Increase values of load by one year

j = list of existing system a

and new sets

yes

yes Carry out a PV of Sc

over years Y

write: PV costs of system costs of expansion list future set sizes and commissioning date

?

Figure 10.5 System expansion plan (to minimise total system cost (operation+ investment+ interruptions))

Many attempts were made to assess the economic cost of each kWh curtailed in order to utilise this in system planning. In the 1990s, the UK electricity supply industry assessed the value of lost load (VOLL) to be £2.345 kWh−1[15]. The VOLL is defined as the value that customers place on the amount of energy they would have consumed during a supply interruption. A study [13] in North America in 1985, based on the computation of consumers damage function, assessed this to be equal to almost $5 kWh−1(£3.00), which is not very different. However, such values are much lower for developing countries, where electricity is valued by the consumer at a lower value owing to their limited WTP, and the shortage of funds, particularly investment prospects in foreign currency, necessities that lower levels of reliability be tolerated.

It has to be realised that such values are based on certain supply continuity standards and consumer expectations. These are likely to change with changes in continuity as demonstrated by curve (B) in Figure 10.1.

10.7

References

1 BILLINGTON, R., and ALLAN R. N.: ‘Power-system reliability in prospective’ (Applied Reliability Assessment in Electric Power Systems, IEEE Press, 1991, pp. 1–6)

2 BILLINGTON, R., and ALLAN, R. N.: ‘Power system reliability in perspective’, Electron. Power, J. Inst. Electr. Eng., March 1984, pp. 231–236

3 KHATIB, H., and MUNASINGHE, M.: ‘Electricity, the Environment and Sus- tainable World Development’, World Energy Council, 15th Congress, Madrid, 1992

4 ‘Power Shortages in Developing Counties’ US Agency for International Devel- opment, report to Congress, March 1988

5 KHATIB, H.: ‘Economics of reliability in electrical power systems’, (Technicopy Ltd., England, 1978)

6 MUNASINGHE, M.: ‘The economics of power system reliability and planning’ (World Bank Research Publication, 1979)

7 BILLINGTON, R., WACKER, J., and WOJCZYNSKI, E.: ‘Comprehensive bibliography on electrical service interruption costs’, IEEE Trans., June 1983, PAS-102, (6), pp. 1831–1837

8 IEEE Committee: ‘Bibliography of the application of probability methods in power system reliably evaluation’, IEEE Trans., 1984, PAS-103, pp. 275–282 9 BILLINTON, R., WACKER, G., and WOJCZYNSKI, E.: ‘Customer damage

resulting from electric service interruptions’, Canadian Electrical Association, R&D project 907, U131 report, 1982

10 MCGRANAGHAN, M.: ‘Economic Evaluation of Power Quality’, IEEE PER, February 2002, 22, (2), pp. 8–12

11 ‘Senior Export symposium on Electricity and the environment’, Helsinki, May 1991 (International Atomic Energy Agency (IAEA), Vienna 1991) 12 ‘Electricity generating costs for plants to be commissioned on 2000’, UNIPEDE,

Paris, January 1994

13 BILLINGTON, R., and OTENG-ADJEI, J.: ‘Cost/benefit approach to establish optimum adequacy level for generating system planning’, IEE Proc. C, March 1986, 135, (2)

14 BILLINGTON, R., OTENG-ADJEL, J., and GHAJAR, R.: ‘Comparison of two methods to establish an interrupted energy assessment rate’, IEEE Trans., August 1987, PWRS-2, (3)