model, the generation technologies with the lowest cost, including fixed and variable costs, will be built; and 3. A **static transmission system load flow** model that takes the dispatch for a specific load condition (e.g., annual peak) and calculates the flows along the lines and voltages at each (high voltage) node/substation of the transmission network. The objective of the load flow analysis is mainly to ensure that the generation investment plan and dispatch produced in the preceding two steps can be accommodated in the transmission system, i.e., power flows on all lines remain within limit, voltage at all sub‐stations remain within limits, including contingency events when one of the large generator or line is on outage.

Investment optimization in the first step takes into account fixed costs including annualized capital cost of new entrant projects as well as variable fuel and variable O&M costs. In addition, the cost of power import and any cost of unserved energy are also considered. The model takes into account depleting domestic gas availability in Bangladesh, which in turn means the option of either importing expensive LNG and using the available infrastructure needs to be compared with building new coal plants and using imported coal, and/or renewables.

Dispatch modeling takes into account plant flexibility to meet additional power requirements for a system where output from renewables can change unexpectedly and substantially. In general coal plants have lower ramp‐up and ramp‐down rates due to higher technical constraints. Gas and oil‐fired plants are more flexible and are better suited to provide back‐up power to renewables. The model constrained the changes in power output from each plant from one hour to the next to account for these differences in flexibility.

The transmission analysis takes into account existing and planned substations, transmission lines and the current and projected loads at each 132kV substation. The inputs consist of 132kV, 230kV and 400kV substations and the transmission lines connecting them. Each transmission line’s capacity mirrors the existing grid and the projects for increasing capacity. The system will need to balance supply and demand with nearly uniform voltage levels in order to maintain voltage stability and reduce losses. For this analysis, we targeted substation voltage levels to be within stipulated voltage level (e.g., ±5%). Voltage levels could be narrowed further with the addition of shunts in the system, though fine‐tuning the grid to set voltage levels within a narrower band adds little value to long‐term analysis. Substation load is scaled by the overall growth rate in demand. For the grid analysis, we used Siemens’ PSS/E system analysis tool.

The modeling framework is the first application of a full suite of capacity, dispatch and load flow models to address VRE policy in the country. As discussed above, comprehensive analyses that fully considers all three levels of analysis on a consistent basis, with due consideration of spinning reserve and transmission, is also of recent origin. The need for spinning reserve to manage variability, for instance, is often ignored in analysis of VRE although it can prove to be a critical consideration.

For the optimization, we use Electricity Planning Model (EPM) developed at the World Bank (Chattopadhyay et al, 2018) using the <mark>General Algebraic Modeling System</mark> (GAMS, 2017) language.<sup>8</sup> The

> 8 GAMS is a popular mathematical programming language that consists of a compiler and a range of integrated high‐performance solvers including CPLEX from IBM that we have used for this analysis. GAMS, originally developed by the World Bank, permits the modeling of complex, large‐scale problems. Excel provides the framework for data input to modeling and analysis of outputs. Full details of the model is available:

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