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Conventional load flow algorithms are very commonly used in the system planning. In the conventional load flow methods, system electrical parameters at specific weather conditions will be considered. These methods gives results for given loading condition and have no provision to incorporate weather condition of a specific geographical location. If the load flow has the provision to incorporate the dynamic electrical characteristics of the conductors based on the operating weather condition, the results of the methods are going to be more accurate or in other words the results are close to the real values. In view of the above, in this paper a modified load flow algorithm incorporating the thermal modeling of the conductors with ambient temperature, wind velocity, conductor surface absorptivity, global solar radiation, Wind direction factor etc. is proposed. To verify the effectiveness of the proposed algorithm, the thermal mathematical model of transmission lines available in IEEE Std. 738™ -2006, IEEE Std. 738™ -2012 and CIGRE WG 22.12 are considered. In the proposed algorithm, new variables corresponding to Conductor Temperature are incorporated. The proposed algorithm is tested with the real time weather data of India and demonstrated on IEEE 30 and 118 bus systems. • An algorithm for power flow including thermal models of the transmission lines. • Variable weather and ZIP load models are incorporated in the proposed algorithm. • It estimates the transmission line temperature using the field measurements. • Seasonal variations of the critical bus voltages are estimated using proposed method. • Impact of renewable generation on system performance is evaluated. [ABSTRACT FROM AUTHOR]

• Bringing the asset management of transformer under the purview of building manager from utility. • Derived mathematical model of demand response from transformer thermal model. • Method to estimate transformer temperature time constant from measurements and algorithm for improving the life of transformer by regulating HVAC and AHUs. • Smart grid architecture for demand responsive HVAC. • Real time simulation of impact of demand response using the actual building consumption data from an academic campus. Overloading and ageing effects contribute to 12-15% of distribution transformer failures in India. This research is motivated in extending life of transformer by using demand response as an operational strategy where the demand response events are issued by predicting overheating of transformer before it occurs. In this paper heating ventilation and air conditioning is considered as a flexible load for responding to demand response events. A demo site is created at 11 KV/440 V substation with 1.6 MVA transformer at Indian Institute of Technology Hyderabad (IITH) campus and the proposed architecture and algorithm is implemented. This substation supplies power to chiller plant and three academic buildings with heating ventilation and air conditioning (HVAC). Analysis for improving the transformer lifetime is carried out for 5 consecutive days during the period (25–29)th Feb 2020 using real time field data. It is observed that during this period 11 demand response events occurred with a total demand response of 919 kWH. From the obtained results it is observed that there is a saving of 15 hoursof transformer life within a period of 5 days (120 hours) of transformer operation. The key contribution in this paper is to bring together three concepts transformer lifetime estimation, HVAC flexibility and demand response for improving the transformer lifetime. [ABSTRACT FROM AUTHOR]