| Work Detail |
The discussion paper addresses the evolving energy landscape in India, emphasizing the shift from coal-based power to renewable energy sources such as solar and wind. Since 2014, significant progress has been made in expanding renewable energy capacity, particularly through initiatives like the National Solar Mission. Solar capacity alone has grown substantially, from 2.63 GW in 2014 to over 81 GW by 2023. As part of its commitment under the Nationally Determined Contributions (NDC), India aims to achieve 50% of its installed energy capacity from non-fossil sources by 2030.
However, this transition to renewable energy presents challenges, particularly in integrating variable renewable energy (VRE) sources like solar and wind into the grid. The variability and intermittency of these sources create difficulties in ensuring grid reliability. One crucial concept to address this is capacity credit, which refers to the dependable contribution of renewable energy to the grid. Unlike conventional power plants, whose output can be controlled, renewable energy is subject to fluctuations based on weather conditions and the time of day. Hence, system planners must adopt scientific approaches to estimate capacity credit for VRE sources.
To facilitate this, the Central Electricity Authority (CEA) has been tasked with calculating the capacity credit of various power sources, including renewable energy, and providing this information to state utilities. Furthermore, under the Resource Adequacy Guidelines, distribution utilities must also calculate the capacity credit for their resources. This ensures a more reliable and accurate understanding of the firm power available from renewable sources, which is crucial for meeting future energy demand.
The paper also introduces the concept of coincident peak, which refers to the demand of different states or utilities during the national peak demand. Since peak demand varies across time and location, the coincident peak may not align with the peak demand of individual utilities. Therefore, states must ensure that they have sufficient capacity to meet the coincident peak contribution at the national level, taking into account a Planning Reserve Margin (PRM).
The methodologies proposed in the paper for calculating capacity credit and coincident peak are designed to enhance grid stability and ensure a reliable power supply. For instance, the paper explores different methods for determining the coincident peak demand, including the “Top 5% Demand Hours” methodology. This approach involves analyzing the demand profile of each state, projecting future demand, and preparing a load duration curve to determine the top 5% of demand hours. The coincident peak for each state is then calculated based on the state’s demand during these top-demand hours.
The challenges of integrating renewable energy into the grid are further compounded by the inherent variability of solar and wind power. For instance, solar power generation is available only during the day, while wind power is subject to seasonal and geographic variations. The paper discusses how to calculate capacity credit for VRE sources, taking into account factors such as location-specific profiles, temperature, and year-on-year variations in generation.
The methodologies proposed for capacity credit calculation focus on ensuring that utilities have adequate capacity during peak demand hours. For conventional sources like coal, gas, and hydro, the capacity credit is more straightforward and based on factors such as availability and past generation data. For VRE sources, however, the paper suggests using a combination of statistical methods, including the “Top 10% Methodology,” which involves analyzing the generation profile during the top 10% of demand hours.
Ultimately, incorporating capacity credit into energy planning will help utilities optimize their resource portfolios, ensure a reliable power supply, and accelerate the transition to a low-carbon energy system. The paper concludes that while renewable energy is essential for reducing carbon emissions and promoting sustainability, careful planning, and accurate capacity credit assessments are necessary to mitigate the challenges of variability and intermittency. |
