# Planning & Decision Making

Could there be a fairly reliable way to forecast future electricity demand by taking into account various variables in order to make economic and technical decisions? Here is an article which looks into a method of doing precisely such a thing. - K Ramalingam, C S Indulkar

The economic growth of the country depends on the generation of power and also on the per capita consumption. Therefore, it is necessary to make an advance plan for the future, since the economic growth is crucially dependent on the power sector. The total power generated in India with non-renewables and renewables up to 2014 is shown in Fig.1.

As of now 5GW power is generated from nuclear, 25 GW from oil and gas,154 GW from coal, 21, GW from wind, 2GW from solar,41 GW from hydropower, and 7 GW from biomass. The Gujarat Energy Research and Management Institute in Gandhinagar, Gujarat (Reference 1) has suggested that a target of 612 GW (which is about 2.4 times the 2014 capacity) consisting of both non-renewable and renewable generation can be achieved in 10 years, by 2024, as shown in Fig.2.

In this article, we apply the random number theory to project the total expenditure that will be required over a 10 -year period to increase the GW capacity of renewable and non-renewable sources. First, we apply the theory to non-renewable sources. Fig.3 shows the GW power of non-renewable sources in 2014, target in 2014, and increase in power over the 10-year period, and the total assumed expenditure for increase in power in 2024.

Random number theory

On an Excel spreadsheet if you type a function ‘ =R AND BETWEEN(1,4)’ and say fill 5 spaces in a column you will get the set of numbers, 2,3,4,3,2 or any other which are within the range (1,4). Similarly, for example, the random number table for nuclear power is generated as shown in Fig.4 and the corresponding cost is calculated.

Costs for increasing the generation capacity of all non-renewable plants over a ten-year period

The random numbers and corresponding costs are generated for all nonrenewable plants as shown in the previous section. The total costs for all non-renewable generators are then added and arranged in an increasing order of total costs, as shown in Fig.5 (below). It can be observed from Fig.5 that increasing the capacity of non-renewable sources from 201GW to 401 GW in ten years will increase the expenditure on non-renewable sources from Rs 2890000 to Rs 5805000 crores.

Costs for increasing the generation capacity of all renewable plants over a ten-year period

Fig.6 shows the GW power in 2014 for renewable plants, target in 2014, increase in power over the 10-year period, and the total assumed expenditure for increase in power in 2024.

Next, the random numbers and corresponding costs are generated for all renewable plants as shown in the previous section. The total costs for all renewable generators are then added and arranged in an increasing order of total costs, as shown in Fig.7. It can be observed from Fig.7 that increasing the capacity of non-renewable sources from 305 to 396 GW in ten years will increase the expenditure on renewable sources from Rs 5745000 to Rs 7590000 crores.

Summary

In this article, we have suggested a planning and decision making method in the power sector for its future demand by using the method of random variables. The method is similar to the method of Monte Carlo analysis but is much simpler. We have assumed the total expenditures over a 10- year period for both renewable and non-renewable generation, based on the reported cost of generation as in 2014 for various energy sources. However, the costs of generation, especially for renewable sources are drastically coming down now.

The procedure may accordingly accomadate the current cost of generations of sources to arrive at the correct figure of expenditure. These can be changed easily if the expenditures appear to be excessive, and the random number analysis can be repeated. As the technology grows and matures, the cost of generation especially of renewable sources is likely to come down. The main advantage of random number analysis is that we are able to decide the types of generations and the GW increase in their capacities over a 10-year period depending on the availabilty of funds, because the increased capacities are ranked from a low initial expenditure to the highest expenditure in the 10-th year.

Reference: 1. “An Innovative solution for power shortage in India” by T. Harinarayana (GERMI, Gandhinagar, Gujarat), Electrical India, Vol.56, No.2, February 2016, pp.24-26.