The Role of Demand Profile in Optimizing Operational Planning

Heat demand is increasing every day due to urbanization, population growth, and rising living standards. This rising heat demand continually escalates operational costs day by day. The reduction in the expenses of heat production units is crucial because it directly affects energy affordability and profitability. The heat production units operate generally according to the end-user demand. The main goal is here to see how the variation in demand could have an impact on the operational cost and to determine what aspects of the demand variations need to be addressed to achieve cost-effective performance. Four categories for demand profiles are introduced: high demand, average demand, low demand, and extremely low demand. In this paper, the impact of the demand profile on the operational cost is discussed. An annual demand profile is taken into account. From these profiles, which are related to all days of the year, repeated samples are categorized, and samples are selected. For each of the selected patterns, the operational cost of the desired period is calculated and compared. For the calculation of the best scenario, a genetic algorithm-based algorithm is represented as a function of the consumed power and hourly electricity price. The results of the paper show that the extremely low demand profile outlined a better condition for saving in operational costs (44.6%) while the high demand profile represents the lowest potential for saving (26.5%). Investigation of the results shows that for more than 70% of the situations, the daily demand profile falls into the low demand profile, and this provides a great opportunity for more savings throughout the yearly operation of the unit.