Sayyad Nojavan

Recently, electricity utilization is increasing as a result of population growth. Hence, total fuel consumption of thermal units increases with their inefficient and uneconomical load dispatch. Moreover, uncertainty associated with electricity market prices changes daily profit of market operator. For this purpose, information gap decision theory (IGDT) is implemented on a multi-period unit commitment (UC) problem aiming to maximize total profit obtained from selling electricity to consumers. In this chapter, total revenue achieved from selling energy to customers minus total operational cost of thermal power plants is maximized considering ramp-up and ramp-down rates, minimum up- and downtimes, and production capacity of thermal generation stations in UC problem. Moreover, uncertainty of electricity prices is modeled using IGDT to assess how market operator can make a risk-averse decision at low market prices and obtain higher profit in comparison with base problem, which is solved with same prices. In other words, robustness mode of IGDT enables operator to find a good solution for hour-ahead scheduling of thermal units for underestimated energy rates in a way that total profit will not only be larger than a predefined critical profit but also is more than profit of UC problem, which is solved with same market prices and without application of IGDT strategy. Similarly, opportunistic mode of IGDT makes it possible to maximize profit for overestimated electricity prices so that it will not only be more than a target profit but also is larger than profit of UC problem, which is solved with same prices and without implementation of IGDT. To prove IGDT’s robustness and capability in modeling uncertainties, a ten-unit standard system is discussed in two case studies: case 1, without application of IGDT method, and case 2, with implementation of robustness and opportunistic modes of IGDT. It is found that risk-averse and risk-seeker decisions affect total cost, revenue,