Demand variability is a predominant feature of the Indian electricity market. Since demand forecasting is mainly done on a day-ahead basis, the actual electricity demand in the country has been neither fully met nor determined accurately so far. In addition, supply variability has also become a regular feature, with the growing share of renewable energy sources in the fuel mix. This has led to an inc-rease in the power demand-supply gap, especially during peak hours, forcing distribution utilities to resort to load shedding.
In this scenario, utilities have the option to utilise pricing and control mechanisms to influence consumption patterns. In this, pricing is a far more suitable format than control because there are liability and complexity concerns involved with controlling. The presence of an adequate pricing signal is the key for consumers to voluntarily adjust their demand. Under this, tariffs should be fixed in a way that consumers are willing to pay more for electri-city in certain time blocks.
Different options are available for variable pricing for the wholesale and retail power markets. In India, the share of power exchanges in the total power transacted is very limited, which makes the wholesale market option for variable pricing unviable. In contrast, the consumption pattern of consumers can be influenced effectively by the application of methodologies such as time-of-day (ToD) pricing, real-time pricing (RTP) and critical peak pricing (CPP).
ToD metering, also known as time-of-usage or seasonal ToD, is an essential element of demand response (DR) as it enables the implementation of time-variable prices. DR is the ability of consumers to reduce electricity consumption at their location when tariffs are high or the electricity grid is overloaded. It is a competitive resource that can be used to maintain the balance between demand and supply for grid operations through the introduction of load flexibility instead of concentrating on only the adjustment of generation levels at all operational time periods. In India, most states have ToD metering for commercial consumers.
Under ToD pricing, the price per unit of electri-city varies, with higher rates being charged during peak hours and lower rates being charged during off-peak hours. It is a method of incentivising consumers to shift a portion of their loads from peak times to off-peak times, thereby improving the system load factor by reducing the demand on the system during peak periods. ToD tariff assumes importance in the context of propagating and implementing DR and achieving energy efficiency.
The two-part tariff structure in ToD metering sends price signals to consumers to curtail or shape demand, thereby reducing the load on the electricity system during peak hours. While this can be used to automatically control usage on the part of the customer (resulting in automatic load control), it is the customers’ responsibility to control their usage, or pay accordingly. It is, therefore, a voluntary load control mechanism. It also allows utilities to plan their transmission infrastructure appropriately.
A key assumption in ToD pricing is that it is not essential that everyone will benefit from it. There will be some consumers who will be better off with this kind of pricing and others who may be worse off. This is based on the time period of their consumption and their ability to shift their load. Further, the extent to which ToD tariffs can be fully implemented depends on the customers being served, that is, the practicality of implementation and consumers’ ability to respond to the pricing signal. Any ToD tariff introduced on its own to promote efficiency will not be successful if it does not take into consideration the consumer perspective.
Besides being a DR measure, another important objective of ToD tariffs, particularly in the context of the country’s peak-demand-deficit scenario, is that the introduction of such a tariff mechanism will help in developing a pricing mechanism for setting up generation plants that could meet the peaking power requirements of the system.
Other pricing mechanisms
Under RTP, consumers are charged prices that vary over short time intervals, typically hourly, and are quoted one day in advance or less to reflect contemporary marginal supply costs. RTP has not been able to gain much acceptance among consumers as it transfers the wholesale prices directly to them, thus taking away the entire risk from the utility and passing it on to the consumers. Further, RTP is complex in nature from an implementation point of view.
CPP is generally applied in addition to ToD pri-cing. In case of unforeseen circumstances (such as line tripping or generator failure), a utility can declare CPP as an add-on to ToD pricing. Reportedly, the benefits derived from ToD pricing are 60 per cent to 80 per cent more as compared to RTP and it is much easier to implement. The major difference between the above-mentioned pricing options lies in their complexity and acceptance rather than their effectiveness.
Challenges and the way forward
There are various challenges that utilities encounter in implementing variable pricing techniques. For instance, the foremost challenge in implementing ToD metering is that it requires a change in infrastructure as the meters need to be capable of ToD measurements and this, in turn, requires huge investments.
In addition to transaction costs and consumer resistance, the other major challenge that variable pricing faces in India is the absence of a significant wholesale market. Unlike in the West, the majority of the power procured in India is through power purchase agreements. In Western countries, when a part of peak power is saved, it reduces the wholesale price for the entire generated power. In India, this benefit is not available, which makes the job of implementing variable pricing difficult. Further, utilities should take steps to procure short-term power in order to meet the increased demand during peak hours. However, owing to the high costs, only a few states such as Maharashtra and Delhi systematically procure power at present. In order to address this issue, utilities can either increase tariffs for all consumers or make consumers who draw more power pay more. However, utilities prefer to resort to load shedding, not realising that the cost of backup power is even higher.
A viable solution to meet peak demand is to introduce ToD pricing as well as DR programmes. However, given the current state of utility finances, they will undertake the latter only if the incentives offered to consumers cost less than peaking power.
Utilities will have to work with the regulators to enable increased ToD metering. Furthermore, from an accountancy perspective, utilities associate a zero accounting cost to load shedding. Attributing value to load shedding will improve the business case for ToD pricing. Also, utilities should try to develop and extend the ToD metering infrastructure in an integrated manner, taking into consideration the metering standards envisaged in the Restructured Accelerated Power Development and Reforms Programme, under which all the meters that are to be installed should have a ToD compatibility feature.
The government recognises the inherent value of ToD metering. The next step is to operationalise it. One of the main concerns is the uncertainty involved in the process of implementation as there is no prior data to rely on. An appropriate solution would be to implement the project on a pilot basis, to learn from its results, and then design a suitable policy framework.
Based on a presentation by Dr Rahul Tongia, Adviser, India Smart Grid Task Force; Adviser, India Smart Grid Forum; Adjunct Professor, Carnegie Mellon University; and Fellow, Brookings India, at a recent Power Line conference