Postponement of investments in transmission and distribution

transmission investments are driven by the increased demand for electricity in a given region. in this context, distributed photovoltaic generation can contribute, if there is a coincidence between generation and peak demand, to postpone the need for investments in this network.

17 in this case, already discounting the generation of other non-dispatchable power plants, such as wind power.

according to denholm et al. (2014), in terms of benefits for transmission, distrib- uted photovoltaic generation can influence both the congestion relief of the lines¹⁸ and the reliability of the transmission system. Just as panels avoid the need for power gen- eration, they also alleviate the need to transmit power because the generation is close to the load, so that the need to add transmission capacity is reduced. since the transmis- sion line is sized to meet the peak demand, it is necessary that there is a coincidence between distributed photovoltaic generation and consumption within the area served by the considered transmission network so that any benefits can be verified.

This feature of postponing investments in transmission can be a positive factor not only in terms of cost reduction but also environmental impacts. The brazilian genera- tor park is usually built far from the cargo centers, and there are plans to build new hydroelectric plants in the amazon region. Thus, it is necessary to construct transmis- sion lines that can extend through areas being little anthropized, with large areas of preserved natural forest and relevant ecosystems, or in proximity to indigenous lands, quilombola communities and conservation units. it is inferred, therefore, that distrib- uted photovoltaic generation can have a positive influence in postponing the need for these investments.

There are several approaches used to estimate the impact of distributed photovol- taic generation on the value of the transmission capacity. among these approaches, we highlight the analysis that this generation would have on the differences in the mar- ginal costs of operation of the bars in which expansion could occur, called, Congestion Cost relief. it can also be called the marginal benefit of transmission¹⁹. These could be a proxy of the value of eliminating restrictions on transmission, and may reduce the load in regions where these prices were high. For example, in locality a, the marginal cost is 50 $/MWh, while in locality b the marginal cost is 300 $/MWh. Thus, the mar- ginal benefit is 250 $/MWh. photovoltaic generation of 1 MWh in b would reduce by 1 MWh, the import of energy from a with a value of 250 $. it is observed that this is a method that considers only the marginal impact of photovoltaic generation.

a second methodology to estimate the value of the postponement of transmission investments is with the use of dispatch optimization models, as discussed in section 3.1. it compares the expected operation with and without photovoltaic generation and observes the changes in network congestion costs. This methodology allows to evalu-

18 The occurrence of congestion in the network is an indication of the need for new investments in transmission, since it shows that the line is operating at its maximum capacity.

19 The marginal cost difference between two buses (or subsystems) indicates how much would be saved if there was more than 1 MWh/h transmission capacity. Therefore, it is the marginal benefit of expand- ing transmission capacity.

ate this benefit even in case of higher penetration levels, which change the dispatch decision and the expected power flows (denholm et al., 2014). it is worth mentioning that the simulation methodology requires a high volume of data and a large number of simulations, depending on the number of scenarios considered, which tends to gener- ate computational complexity.

in the case of distribution, the expansion of distributed generation has dubious effects on the need to increase network capacity. under certain circumstances, this generation could reduce or avoid the need for investments by providing power locally and reducing the required electricity flow in the network. However, accommodating large distributed photovoltaic diffusion can be challenging and require improvements in wires, transformers, and voltage regulation equipment. The benefits of this genera- tion are greater in systems where there is greater operational flexibility on the part of the distribution system operator (e.g., management according to the demand, electric vehicles and storage).

in this way, it is possible to consider that the distribution system installed will not be impacted in situations of low penetration of distributed photovoltaic generation. in this case the value of the distribution capacity is simply considered zero. in this case, the potential gains or costs linked to the peak demand reduction are not considered.

another methodology is to estimate the average cost of investment in expansion of distribution capacity and to verify how distributed photovoltaic generation decreases peak demand. it is necessary to check how much of the photovoltaic generation coincides with the peak period of local demand. it is also necessary to consider the possibility that the maximum energy requirement of the network occurs at another time when there is no photovoltaic generation. a reliability analysis, similar to elCC, could be made to estimate the reduction of peak demand. However, denholm et al.

(2014) emphasize that there is no formal and widely accepted methodology for this estimate.

Thus, it is clear that the benefit that photovoltaic energy can generate for the trans- mission and distribution networks depends on the characteristics of these networks and on the photovoltaic generation patterns and the load curve of the electric power systems considered, mainly from the existence of the coincidence between this gen- eration and the demand. Therefore, a more accurate cost-benefit assessment of this diffusion for transmission and distribution systems depends on a detailed analysis that considers the characteristics of each of these systems.