Chapter 1 Introduction
7.2 Conclusion Related to Methodological Application
The operational model portrays system operational insights at higher spatial and temporal resolution. Due to applied constraints, it ensures that the dispatch profiles of the generators are within their technical limits and more realistic power flow between the nodes. This leads to calculation of different activity profiles of the technologies compared to the planning model. Due to a considerable number of nodes, generators, and transmission lines, volume of the operational model is large. It is computationally challenging to solve the model for multiple milestone years of the planning model and perform multiple scenario analysis within reasonable time frame. Reformulation of model and refinement of model solving methods needs to be targeted. Incorporation of specific operational constraints in the planning model itself can lead may lead to more accurate dispatch decisions of generators, regional power exchange and help streamlining data exchange between the two types of models. There is a need to identify specific constraints to incorporate in the planning model based on trade-off between additional computational complexity and result accuracy. These are further elaborated in Section 7.3.
Bi-directional method illustrates how output of an operational model working at finer spatial and temporal level can be utilized in a planning model with coarse modeling definitions.
It also outlines how additional user constraints can be constructed from operational model results to update technology wise, time slice wise and region wise capacity factor in the planning model for each model iteration for attempting new solution.
7.2 Conclusion Related to Methodological Application 131 to geographical coverage, spatial and temporal definitions, time horizon, system definition, level of details of RE granularity and other several assumptions. Specifically, there is no earlier work on long-term system development of North-Indian power sector. Therefore, direct comparison of results is a challenging task.
Overall, the results presented in this thesis are an important contribution to national energy system planning, as they indicate optimistic transition towards a high renewable penetrated system. As the present study has not modeled any specific policy inputs, results impart light on future system development for various policy formulations. Due to the primary focus of India on solar and wind for clean power generation, their variability modeling is the main focus of this modeling application.
India aims to meet sustainable development goals, such as 100% electricity access to people and to move towards low carbon economy. It is a challenging task considering India’s current fast track approach towards economic progress. Drastic policy change regarding electricity supply can jeopardize existing political consensus. Managing affordable electricity supply price is therefore crucial. As solar and coal are main generating options affecting future supply price, following paragraphs provide a short discussion on their inter-dependencies, along with total CO2emission.
Result shows that in spite of increasing RE penetration, coal will continue to be a major player unless extreme exogenous carbon taxetc. related policies are imposed. Government initiatives towards implementing these taxes in power sector, and their rate are uncertain and volatile. Therefore, future domestic coal production rates should be improved. Present rates are clearly not going to be sufficient to meet future coal demand. This requires new explorations, modernizing existing mines, and streamlining environmental clearances.
Though steps towards implementing these has been started, setting up realistic targets, political will as well regulatory clearances are the key challenges
Figure 7.1 outlines solar and coal-based generation in different electricity supply prices for CO2 price and solar cost scenario groups respectively in 2050; coal price and wind cost are set to ref scenario. In Figure 7.1 A, evident diversification of three groups is seen according to CO2price scenario. The lowest group indicates no CO2price cases with low solar-based generation. The highest solar power production in this group is around 950 TWh when solar cost is at SL and storage cost is at TL scenario. On the other hand, solar generation is lowest (469 TWh) when storage and solar cost are high. In this CO2 price scenario group, electricity price ranges from 2.5-3.37 INR/ kWh. In the middle group or CL scenario group, electricity price ranges from 2.9-4.05 INR/ kWh whereas, total solar generation ranges from 1343-791 TWh. In high CO2price cases (red dots), 1093 TWh solar generation is seen at an electricity price of 4.48 INR/ kWh, when storage and solar costs
are at high level. On the other hand, in low solar and storage cost cases, maximum solar generation of 1561 TWh is seen at a much lower electricity price of 2.88 INR/ kWh.
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Figure 7.1Solar and coal based power generation vs electricity price in CO2 price and solar cost scenarios in 2050
Similar observations can be made in Figure 7.1 B, where coal-based generation is plotted with respect to electricity price for three solar cost scenario groups. Three clear clusters of model cases, due to three CO2price scenarios, can be seen. In each CO2price group, it can be observed that higher solar and storage cost leads to higher coal-based generation at higher electricity price. In the upper group of points (ref CO2price), low solar cost leads to coal generation as low as 673 TWh at a rate less than 2.51 INR/ kWh; while at high solar cost coal-based generation as high as 1039 TWh is seen at electricity supply price of 3.37 INR/
kWh. Within each scenario group in three point cluster, coal-based generation moves up according to the inverse variation of storage cost (as low storage favors higher solar energy generation). Coal-based generation is very low for high CO2price cases.
Investigation of such cases is important as various cases can be found to generate lower CO2 emission at lower electricity price. Large number of model cases in this study con- structed from three sensitivities of five parameters gives ample opportunity to analyze the system development under diverse conditions. Future studies in this direction in India will benefit from the scenario selection, model case construction and result analysis.
Energy storage technologies appear to be a key enabler of variable RE sources, especially solar PV. Though there are several policy-related instruments in India to attract investment into RE capacity, there is no clear policy towards integrating storage systems actively for RE integration. Current RE expansion plans in India are primarily involved with a substantial