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Effective utilization of renewable energy sources and efficient management of electric energy are essential for any developing countries like India. This can be envisioned through the implementation of concepts of smart grid (SG). One of the key requisites for SG implementation is that the grid should be completely observable. Renovation of conventional Indian power grid to a SG necessitates incorporation of the phasor measurement units (PMUs) in the present power grid measurement and monitoring system. Since the cost of PMU is high and any bus containing a PMU makes the neighboring connected buses observable, optimal placement of PMUs is very important for complete observability of the grid. This paper proposes optimal redundant geographical locations in the northern, eastern and north-eastern regions of Indian power grid for PMU placement. The PMUs installed in these geographical locations will make the grid completely observable and maintain the observability under the conditions of failure of some PMUs or branch outages. Integer linear programming has been used for finding the optimal PMU locations. The results proposed in this paper can be a stepping stone for revamping the Indian power grid to a SG ensuring complete observability during different contingency conditions.

We present the study on the Indian power transmission network using the framework of a complex network and quantify its structural properties. For this, we build the network structure underlying the Indian power grid, using two of its most prevalent power lines. We construct an equivalent model of an exponential network and study its structural changes with changes in two parameters related to redundancy and dead-ends. Then we analyze its stability against cascading failures by varying these two parameters using the link failure model. This helps to gain insight into the relation of network topology to its stability, and indicates how the optimum choice of these parameters can result in a power grid structure with minimum failed links. We apply the same model to study the robustness of the Indian power grid against such failures. In this case, we find that when a link connected to a generator fails, it results in a cascade that spreads in the grid until it is split into two separate stable clusters of generators and consumers, with over one-third of its nodes nonfunctional.

Efficient utilization of energy resources is essential for a developing country like India. The concept of smart grid （SG） can provide a highly reliable power system with optimized utilization of available resources. The present Indian power grid requires revolutionary changes to meet the growing demands and to make the grid smarter and reliable. One of the important requirements for SG is the instantaneous monitoring of the voltage, current and power flows at all buses in the grid. The traditional monitoring system cannot satisfy this requirement since they are based on nonlinear power flow equations. Synchro-phasor-measurement devices like phasor mea- surement units （PMUs） can measure the phasor values of voltages at installed buses. Consequently, the currents passing through all branches connected to that bus can be computed. Since the voltage phasor values at the neighboring buses of a bus containing the PMU can be estimated using Ohm＇s law, it is redundant to install PMUs at all the buses in a power grid for its complete observability. This paper proposes the optimal geographi- cal locations for the PMUs in southern region Indian power grid for the implementation of SG, using Integer Linear Programming. The proposed optimal geographical locations for PMU placement can be a stepping stone for the implementation of SG in India.

Conventional power grids across the globe are reforming to smart power grids with cutting edge technologies in real time monitoring and control methods. Advanced real time monitoring is facilitated by incorporating synchrophasor measurement units such as phasor measurement units (PMUs) to the power grid monitoring system. Several physical and economic constraints limit the deployment of PMUs in smart power grids. This paper proposes a pragmatic multi-stage simulated annealing (PMSSA) methodology for finding the optimal locations in the smart power grid for installing PMUs in conjunction with existing conventional measurement units (CMUs) to achieve a complete observability of the grid. The proposed PMSSA is much faster than the conventional simulated annealing (SA) approach as it utilizes controlled uphill and downhill movements during various stages of optimization. Moreover, the method of integrating practical phasor measurement unit (PMU) placement conditions like PMU channel limits and redundant placement can be easily handled. The efficacy of the proposed methodology has been validated through simulation studies in IEEE standard bus systems and practical regional Indian power grids.

The aim of this paper is to review and compare present European and Indian grid code requirements imposed to hybrid power plants (HPPs) combining wind, solar and storage technologies. Since there are no grid codes specifically for HPPs, the paper will review grid codes for the power plant based on individual renewable technology in the HPP. European grid codes specifies ranges for parameters inside which each national transmission system operators (TSO) has to specify the set of national parameters (Danish specifications in this paper). The comparisons are performed with respect to fault-ride-through capability, frequency and voltage operation ranges, active power control/frequency support as well as reactive power control/voltage support.

Energy plays a crucial role in driving economic growth, and India’s energy consumption has increased notably due to its growing population and development. At present, fossil fuels such as coal, petroleum, and natural gas fulfill the majority of India’s energy requirements, but their swift depletion and negative environmental effects present significant challenges. India’s abundant solar energy potential—estimated at approximately 5000 trillion kWh annually—positions the nation to harness clean and sustainable power. With steady growth, solar energy has become a key component of India’s power grid. However, integrating renewable energy into the grid presents challenges, such as maintaining frequency and voltage stability. This report analyzes India’s substantial advancements in solar energy, emphasizing the enabling government policies and the problems associated with integrating renewable energy into the grid. The study underscores the crucial need for effective load frequency control (LFC) solutions to mitigate grid stability issues, intensified by the fluctuating and intermittent characteristics of solar energy. It also evaluates policy-driven approaches and technological advancements, providing practical recommendations to overcome integration challenges. This research aims to contribute to the effective deployment of solar energy in India’s energy mix, ensuring long-term grid stability and sustainability, and it underscores that India’s creative strategies can serve as a model for other nations facing analogous issues in renewable energy integration. It emphasizes the necessity of recognizing optimal practices that integrate energy security, economic development, and environmental objectives, thus contributing to global dialogs on energy transitions.

For the suggested site in the Maldives, this research paper analyzes the possibility of a hybrid renewable microgrid that is dispatch strategy-governed in both off-grid and on-grid scenarios. The planned microgrid’s techno-environmental-economic-power-system responses have been assessed. Both the power system response study and the techno-environmental-economic study of the modelled microgrid were carried out using the software platforms DIgSILENT PowerFactory and HOMER Pro respectively. Cycle charging (CC) dispatch technique had the lowest performance for both on and off-grid modes, according to the research, with cost of energy (COE) of 0.135 and 0.213 dollars per kWh, and net present costs (NPC) of 132,906 and 147,058 dollars respectively. With an NPC of 113,137 dollars and a COE of 0.166 dollars/kWh, the generator order strategy operates optimally while in on-grid mode. On the other hand, load following operates at its finest in off-grid mode, with a COE of 0.024 dollars/kWh and a NPC of 141,448 dollars. The microgrid’s reactive power, different bus voltages and frequency responses demonstrate how the proposed system, which employs the dispatch approach, voltage Q droop, and input mode PQ controller, operates steadily. For the purpose of illustrating the importance of the research effort, a comparison section between the planned HOMER optimizer and other optimization approaches is also included. The research was done with the Maldives in mind, but it offers a general notion for setting up a microgrid anyplace in the world with comparable weather and load circumstances. The research was done with the Maldives in mind, but it offers a general notion for setting up a microgrid anyplace in the world with comparable weather and load circumstances.

PurposeIndian electricity production mix, technology level, and local production conditions vary across the states and union territories. This variability is obscured in existing national-level life cycle inventories of Indian power producing technologies and power systems, which potentially leads to inaccurate results from LCA studies that include Indian activities. This study aims to create a consistent regionalized inventory model of Indian power system parameters and to evaluate how that influences life cycle impact assessment (LCIA) calculations.MethodsData collection covers state-specific key parameters of domestic power production and distribution, and inter-exchanges among the regional grids and with other countries in 2012–2013. However, such regionalization work faces some data availability challenges. Power plant parameter data (e.g., efficiency, fuel quality, exact technology used) are mostly unavailable on plant level for India; if at all, relevant data are available on a state level. Moreover, local emission data are also mostly unavailable except emissions of CO2. Quantities of other important emissions (NOx, SOx, CH4, CO, PM) are, therefore, calculated based on emission factors from literature.Results and discussionVariation in electricity production volumes among the states and regional grids are found notably high. Six states contribute 55% of the national power supply, whereas ten states contribute only 2.1% to the total. Moreover, the five regional electricity grids—Eastern, Western, Southern, Northern, and North-eastern grids—show high variation in production mixes. These differences have a considerable impact on LCIA results. For instance, the contribution to the global warming potential per 1 kWh of electricity supplied to the grid is nearly twice as high in the Eastern grid as in the North-eastern grid. Furthermore, transformation and transmission losses are found to be high in the Indian electricity grids with an average of 17% technical losses along the transmission chain from high voltage to the low voltage.ConclusionsHence, we conclude that the inventory data produced in this study on Indian electricity production and distribution at grid level, taking local variations in technology mix and key parameters into account, enables higher accuracy in life cycle assessment studies compared to using average national-level data.

State estimation is one of the most important functions in an energy control centre. An computationally efficient state estimator which is free from numerical instability/ill-conditioning is essential for security assessment of electric power grid. Whereas approaches to successfully overcome the numerical ill-conditioning issues have been proposed, an efficient algorithm for addressing the convergence issues in the presence of topological errors is yet to be evolved. Trust region (TR) methods have been successfully employed to overcome the divergence problem to certain extent. In this study, case studies are presented where the conventional algorithms including the existing TR methods would fail to converge. A linearised model-based TR method for successfully overcoming the convergence issues is proposed. On the computational front, unlike the existing TR methods for state estimation which employ quadratic models, the proposed linear model-based estimator is computationally efficient because the model minimiser can be computed in a single step. The model minimiser at each step is computed by minimising the linearised model in the presence of TR and measurement mismatch constraints. The infinity norm is used to define the geometry of the TR. Measurement mismatch constraints are employed to improve the accuracy. The proposed algorithm is compared with the quadratic model-based TR algorithm with case studies on the IEEE 30-bus system, 205-bus and 514-bus equivalent systems of part of Indian grid.

In the current scenario of the deregulated Indian electricity market where the power demand and its availability vary remarkably, the factors playing a significant role in demand variations are often associated with the impact of unprecedented weather conditions and technological evolutions. To maintain grid security and discipline that yield to financial implications, there lies a great need to formulate an equilibrium between electricity supply and demand. Devising a model to anticipate the variations which are highly adaptive to such changes is the need of the hour. For this purpose, an algorithm has been proposed in this study, which is best suited for the day-ahead load forecast. The variables selected for the forecast are one-day-lagged demand statistics, seasonality trend, weather, and calendar variables. The proposed algorithm outperforms the existing benchmark model, which is evaluated through various statistical performance metrics such as mean absolute percentage error, mean absolute error, root-mean-square error, and coefficient of variation. The performance of the proposed methodology at the seasonal level is analysed and validated through uncertainty analysis with one post-sample year for the state of Delhi, India. This model presents its compatibility to prevalent grid regulations as well as shall hold good in the weather and demand variations possibly expected in the future.