The RE (renewable energy) can be seen as a transformative solution to meet steadily rising energy demand as well as economic challenges and to mitigate the climate change and to reduce the carbon emission from traditional energy sources. At present, India has a target of 175 Gigawatt (GW) of installed capacity from renewable energy by 2022, of which 100GW is to come from solar, 60GW from wind. In addition, India’s NDC goal is to achieve 40% of total installed power generation capacity from renewable energy by 2030.
With growth of RE (renewable energy) in India, the variability and the intermittency became the two major parameters in the generation-transmission network of the power supply. Hence the large-scale deployment of renewable energy technology involves a combination of interventions involving policy and regulatory mechanisms, technological solutions and institutional structures.
Due to natural phenomena no one can control the generation patterns of the wind and solar energy unlike to the other energy sources. The major issue is to forecast and to schedule the variable generation for a proper grid management. Without proper forecast, the grid become unstable. Hence CERC, FOR and other state regulations propose the mandatory requirement of forecasting the variable power (solar and wind) generation as the forecasting requirement is one of several key aspects of making RE grid integration cheaper and more scalable.
Sometime state-level prediction of variable power generation can be useful to see the overall generation, but for the smooth operation of the transmission network, the grid management requires the forecast at each node of the generation. Hence, for proper grid management, the temporal and spatial granularity of the forecast methodology are the crucial issues in managing the grid.
According to CERC and FOR model regulations, the granularity of the temporal space is considered as 15 minutes defining it as 1 time-block. To define the spatial granularity the concept of ‘Available Capacity’ is introduced while defining the %error in deviation where the error is defined as, %Error = (Actual Generation – Schedule Generation) x 100 / AvC. Where AvC means for wind or solar generators cumulative capacity rating of the wind turbines or solar inverters that are capable of generating power in a given time-block. Here the AvC considers the minimum spatial granularity of forecasting as it is generation-centric and remains same in all regulations. The act is very clear and specific, AvC of the wind or solar generator shall be considered for % error calculation; not the whole portfolio of an aggregator or QCA as a whole, but all the plants’ capacity shall be considered individually and independently.
Since ‘Deviation’ means in a time block, for a seller his total actual injection of energy minus his total scheduled generation and for a buyer means his total actual drawal of energy minus his total scheduled drawal; and Available Capacity is solar or wind generation-centric as per the Act, so a QCA or Aggregator’s ‘Deviation’ cannot be calculated under the current Act or methodology as Aggregator or QCA does not have any PPA. For calculating Deviation under the Act only AvC at plant level or pooling station level, i.e. generator’s level AvC needs to be considered. Otherwise Act is silent about Deviation calculation of QCA or Aggregator’s level or Deviation by Aggregator or QCA. So, if we consider the whole portfolio of an Aggregator or QCA to decide his AvC, then it will be a wrong interpretation of the Act. This definition also clearly states that this Act is applicable only for wind & solar generators not Aggregator or QCA. So, Aggregator or QCA can aggregate and coordinate, but all deviation has to be calculated at the generators level or pooling station level. There is nothing called Aggregator or QCA Deviation under the Act.
Though the existence of QCA and the aggregator is as per regulation, the definition of AvC and ‘deviation’ remains unchanged and logical as the forecast is not only to predict the overall generation but to predict the generation at each grid-node to facilitate the transmission. For proper grid management the system operators depend not only the overall generation, but on the predicted generation of the grid-node as the transmission capacity is not infinite and the grid cannot be considered as infinite source or sink of energy.
But knowingly or unknowingly encouraging the forceful adoption of ‘aggregation of forecast’ as ‘aggregated’ forecast creates the instability in the generation-transmission system, violates different clauses of the regulations and starts the ‘Gaming’ in forecast methodology. Defining the ‘AvC’ as the summation of different pooling stations or cumulative sum of portfolio not only violates the regulations, it also paralyses the grid system and can bring a huge financial impact on power producers, transmission company and overall the grid in very near future. And interestingly, it is not a forecast at all, dividing the wrongly defined ‘deviation’ with high value of wrongly defined ‘AvC’ one can minimize the error in the overall generation (which is actually not required for the grid) but is it as per regulations or is it facilitate the transmission and overall the stability of the grid? Because the ‘Gaming’ in relation to the Regulation means, an intentional wrong/mis-declaration of available capacity or schedule by any seller in order to make an undue commercial gain through charge for deviations. Interestingly, as per the definition of ‘Gaming’ the QCA or aggregator are not responsible, but through their act the power producers become responsible for the consequences and this ‘Gaming’ policy can bring a massive transmission failure due to the spatial dispersion of power generation of different grid nodes.
Abhik Kumar Das
(This article was originally published in Climate Samurai, January-2018 issue)