Inability to Forecast is not the Disability of Regulation

With openly accessible documents/regulations/ on Deviation Settlement Mechanism (DSM), due to forecasting and scheduling (F&S) of wind and solar power generation at different SLDCs like Punjab, Haryana, U.P., A.P., Telangana, Tamil Nadu, Rajasthan, Madhya Pradesh, Chhattisgarh, Gujarat (Mock-trial), it is surely that the forecasting of the variable generation is under litmus-test. The F&S of solar and wind energy is a high requirement to stabilize the existing grid, as the penetration of wind and solar energy is very high (and will be higher in the future with the target of 175 GW). Hence, proper, accurate DSM regulation is a requirement to bring grid discipline and CERC and other SERCs have aptly designed the F&S regulations.

Abhik Kumar Das, Del2infinity Energy Consulting

As per F&S regulation, the key issues are the cost of maintaining grid stability or grid discipline, which is the grid requirement, and penalty due to DSM, which is the focus of IPPs. In between two issues, RE forecasters play the vital role to minimize the cost of maintaining the stability of the grid and to reduce the DSM charges for the IPPs. The balance of convenience between DSM penalty to IPPs and grid stability has to be considered, if grid is not stabilized, then events like (i) frequent failure of grids, (ii) non-availability of grids for smooth evacuation, (iii) backing-down by SLDC, (iv) increase of maintenance of grid (v) transmission losses will crease, which will affect the IPPs in the long run.

The regulation aptly states the requirement of F&S at PSS levels to stabilize the grid and to minimize the cost of maintaining grid-stability. Interestingly, only 2SERCs out of 12 SERCs, namely Karnataka & AP are reluctant to accept the requirement of forecasting at PSS level for grid stability or grid discipline, and considers the geographical integration of different PSS. But how KERC and APERC are minimizing the cost of maintaining the grid stability is still unknown as the DSM are not available as open or public documents, unlike other state SLDCs like Rajasthan, MP, Gujarat, CG etc. Probably, either these 2 states have conducted technical researchs and designed something exceptionally well methodology or technical developments (but not available in research communities) or they are not trying to minimize the cost of maintaining the stability unlike other states.

The concept of forecasting and scheduling of RE generators and the commercial settlement was introduced in Indian context by CERC through Indian Electricity Grid Code (IEGC), 2010 and the Renewable Regulatory Fund mechanism was envisaged to be implemented from January 1, 2011. Due to several implementation issues, the mechanism was never made operational. To formulate an implementable framework, CERC on 31.03.2015 issued a draft Amendments. Based on comments and suggestions received from various stakeholders, CERC published the third amendment to IEGC which is issued on 07.08.2015. On the same date CERC also issued 2^nd amendment to regulation for DSM and other related matters. Since the system operators in India have to do curtailment, backing down of variable renewable energy due to intermittency and variability of the wind and solar power generation, the forecasting takes an important role in creating a sustainable solution for maximum utilization of renewable energy. After CERC regulation, Forum of Regulators (FOR) and other state regulators issued or drafted regulation related to the forecasting and scheduling of Wind and Solar power. Hence it is a long journey of nearly 10 years of F&S regulation & grid discipline and still it is a burning issue (2:12 ratio of SERCs) whether PSS level forecasting or geographical integration forecasting is required for grid discipline and grid stability.

Inability to perform forecasting at PSS level by few forecasters does not prove the inefficiency or ineffectiveness of regulations. Aggregation of different PSS does not increase the accuracy of forecasting nor help the grid discipline; it only reduces the error by dividing a value with large available capacity (simple mathematics). But does it really reduce the cost of maintaining grid-stability? Will aggregated forecasting help to resolves the issues like (i) frequent failure of grids, (ii) non-availability of grids for smooth evacuation, (iii) backing-down by SLDC, (iv) increase of cost & frequency of maintenance of grid (v) higher transmission losses, which will affect the IPPs in the long run.