Model-based Evaluation of Multiple Solutions to Grid Integration Challenges of Large-scale Renewable Power

Abstract

Worldwide renewable installations are growing exponentially in the electricity mix. In a renewable-rich electricity grid, the demand, as well as the generation, varies in different time scales. It is highly complicated to meet continuously changing demand with weather-dependent intermittent renewable generation. From minute-wise variation to seasonal changes, grid stability must be maintained throughout the gradual decarbonization of electricity supply systems or grids. This is a major challenge for net zero transition in the energy sector worldwide. Further, detailed planning is essential to manage low-probability high-impact events like “renewable Energy droughts” in a renewable-rich grid. There are several techniques that can help in addressing the challenges of large-scale grid integration of renewable wind-solar plants. In this thesis, we explore some of the promising solutions like strategic siting of new wind plants to have smoothing in the aggregate generation, selective wind-solar hybridization to avoid extreme energy drought events, and strategic wind-solar-storage portfolio design to achieve high reliability within limited cost.

Smoothing of generation variability, i.e., reduction of variance in the aggregate generation, is crucial for grid integration of large-scale wind power plants. Prior studies of smoothing have focused on geographical smoothing based on distance. In contrast, we propose a novel concept, “diurnal smoothing,” that depends on spatial variations in the timing of seasonal-mean diurnal cycle peak. Considering the case of India, which experiences a strong diurnal cycle of wind speed, we show how spatial heterogeneity in the wind diurnal cycle can be exploited to smooth wind power variability over and above geographical smoothing. For any given separation distance between sites, the hourly wind speed correlation is highly variable. The difference in the timing of the diurnal cycle peak is a crucial factor for explaining this variability, and we define smoothing from the differently timed seasonal-mean diurnal cycle as “diurnal smoothing.” We show that apart from separation distance, the diurnal cycle is crucial for correlation among sites separated by 200 km or more with strong diurnal cycles (amplitude more than approximately 0.5 m/s). Thus, diurnal smoothing is a vital factor in the aggregation of large wind power plants, and grid integration is benefited by considering (in addition to distance) new wind plant sites with largely separated diurnal cycles, especially those differing by roughly 12 hours. Such diurnal smoothing is relevant for regions across the world with strong wind-speed diurnal cycles. Ultimately grid integration depends on variations in total wind and solar generation and demand. Hence, their combined effects must be studied.

Wind power growth makes it essential to simulate weather variability and its impacts on the electricity grid. Low-probability, high-impact weather events like wind drought are important but difficult to identify based on limited historical datasets. A stochastic weather generator, Imperial College Weather Generator (IMAGE), is applied to identify extreme events through long-period simulations. IMAGE captures mean, spatial correlation, and seasonality in wind speed and estimates return periods of extreme wind events over India. Simulations show that when Rajasthan experiences wind drought, Southern India continues to have wind and vice versa. Regional grid-scale wind droughts can be avoided if grids are strongly interconnected across India.

Increasing the share of weather-dependent renewables in the electricity grid is essential to deeply decarbonize the electricity system. Therefore, the investigation of solar drought is also crucial. Wind and solar “droughts” or low-generation days can severely impact grid stability in a renewable-rich grid. This thesis analyses for the first time wind, solar, and hybrid energy droughts in India using a stochastic weather generator. Available literature analyze the observational data that is of limited duration (30 to 40 years). Therefore, the discussion of low-probability high-impact renewable energy droughts that have long return periods (in the range of 30 years) is limited in the literature. The present study seeks to address this research gap by exploring the risk of wind, solar, and wind-solar powered energy droughts based on simulated long time series (5000 years). It is found that the weather generator captures mean, seasonality, and correlation between wind speed and solar irradiance and is therefore used to estimate return periods of extreme wind and solar droughts. Our analysis shows that wind droughts are more intense than solar droughts in India. We examine the role that wind-solar hybridization can play in offsetting low wind energy episodes. The benefits of hybridization are regionally dependent. In South India, hybrid plants have advantages over either wind or solar plants alone. In comparison, for Rajasthan, the benefits of hybridization are limited. Moreover, when one of the regions (South India or Rajasthan) has a renewable drought, the other region has only a 10% probability of having a similar drought. Our findings highlight the need for robust inter-regional grid connections to mitigate regional-level renewable droughts.

Next part of the thesis focus on the bulk storage requirement. In a steadily decarbonizing electricity system, exploring cost-effective wind-solar-storage combinations to replace conventional fossil-fuelled power generation without compromising grid reliability becomes increasingly important. For a renewable energy-rich state in Southern India (Karnataka), we systematically assess the economics of various wind-solar-storage energy mixes for different future scenarios using Pareto frontiers describing economically efficient combinations. The simulated scenarios consider assumed growth in electricity demand, different levels of baseload generation, and flexibility from fossil fuels and hydropower. Our approach considers hourly load data, simulates generation based on hourly weather reanalysis data and models the effects of battery charging and discharging on battery lifetime. Given declining baseload generation and available flexibility in the state electricity grid, its reliability is limited by the amount of generation curtailment that is permitted. Furthermore, we show that adding battery storage capacity without concomitant expansion of renewable generation capacity is inefficient. Keeping the wind-solar installation within the officially assessed renewable potential, a fully decarbonized grid with a certain flexibility can have approximately 63% reliability at the most. Achieving 99% grid reliability would be costly, requiring large wind-solar installations that exceed officially assessed potential, constrained by land allocation. A completely decarbonized grid (in the absence of any base generation) with 6 GW of flexible generation and allowing for 30% annual curtailment of renewables would result in grid reliability of around 93%. The findings highlight the importance of a fresh examination of curtailment thresholds, renewable potential assessment, and possibilities of demand-side management based on consumers’ willingness to modify hourly load patterns.

Other than the solutions discussed here, there are several other probable methods to help in the smooth grid integration of large renewable plants. Some of them are increasing the accuracy of generation and demand forecasting, introducing demand-side management or demand response, and designing a new deviation settlement mechanism to encourage better generation forecasting from renewable generators. Several policy interventions and the formulation of new grid codes are essential for the implementation of these solutions.

The thesis discusses challenges and possible solutions for grid integration of large wind-solar plants from a broad perspective, assuming copper plate grid connectivity. Detailed electricity grid simulation and discussion on merit order dispatch are outside the scope of this work. We also highlight that this thesis focuses on the grid integration challenges from technical and economic perspectives and evaluates the possible solutions accordingly. The social impact of the solutions discussed here is beyond the scope of the study. The land acquisition challenges, grid connection issues, just energy transition, and the impact of wind-solar on biodiversity remain unexplored in the thesis.