Demand Response Benefits for Major Assets of High Voltage Distribution Systems - Capacity Gain and Life Management

Power systems require an adequate capacity and higher utilization efficiency for an economic and reliable supply of electricity. However, their utilization efficiency is ordinary owing to low load factor and reserve capacity needs. Moreover, the growth of electricity demand and aging infrastructure call for massive investments in form of expansions and replacements. Therefore, the power industry is searching for novel solutions to deal with the future needs. Demand response (DR), a load shaping tool in smart grids, can be a potential solution to the future needs. The aim of the dissertation is to assess the DR benefits of capacity utilization gain and better life management for major assets of high voltage grid. The study focuses on subtransmission grids because they have captured least attention in the prior research. Primary substation transformers have given special attention here due to their vital position in the system and high component cost. The aim of the dissertation is further divided into three tasks in order to distinguish the DR benefit among phases of operations and planning and various components. The first task proposes optimization models for utilization gain and life management of transformers by DR during normal and contingency operations. The second task offers tools for optimal capacity planning of transformers in primary distribution substations with and without considering DR. These tools incorporate all transformer related costs, their failure rate increase with age, and their salvage value based on loss-of-life. The third task determines the potential of DR in mitigating the redundancy needs of lines/cables, transformers, and busbars by comparing outage cost due to their contingencies. The simulations are performed using the developed models for typical Finnish systems. The results indicate the following notable deductions. The utilization efficiency of grid components can be substantially improved using DR that depends upon load shape and its DR capability. Also, DR offers significant better life management potential for transformers during both nor- mal and contingency operations. Moreover, the employment of DR along with remote switch- ing of load transfer between substations provides superior savings in transformer capacity planning as compared to that of manual load shifting. Furthermore, the optimal decisions of DR activations are essential in order to gain the intended DR benefits at a minimal expense. The power system utilities can use the models of this dissertation for making decisions of DR deployments. These deployments will be helpful in delaying or eliminating the capacity investments. Moreover, the tools of the second task will help asset managers for taking optimal planning decisions of transformer ratings and their replacement and maintenance schedules.