International Journal of Smart Electrical Engineering, Vol.8, No.4,Fall 2019 ISSN: 2251-9246 EISSN: 2345-6221 149 Energy Scheduling in Power Market under Stochastic Dependence Structure Mehdi Farhadkhani 1 Electricity Economics & Energy Research Group, Niroo Research Institute (NRI),Tehran, Iran Abstract Since the emergence of power market, the target of power generating utilities has mainly switched from cost minimization to revenue maximization. They dispatch their power energy generation units in the uncertain environment of power market. As a result, multi-stage stochastic programming has been applied widely by many power generating agents as a suitable tool for dealing with self-scheduling strategies under uncertainty. However, dependence structure between stochastic variables has been almost ignored in the literature. Copula function is a new concept in the probability and statistics field which has the capability to represent the dependence structure among stochastic variables. However, Copula function has recently taken into account in power system studies by some articles. In this article, self-scheduling strategy of a generation utility owning thermal units is investigated while the dependence structure among stochastic load and market price variables is taking into account. We assume that the generation utility is a price-taker agent in a power market, and it also has to meet the load of a specific region as a retailer. The results indicates that as the stochastic dependence structure among load and price variables is considered in modeling load and price scenarios, the output of unit commitment problem changes so that the revenue of generation utility increases. Keywords: Unit Commitment; Stochastic Dependence Structure; Multistage Stochastic Programming; Scenario Tree Construction; Copula Function. © 2019 IAUCTB-IJSEE Science. All rights reserved 1. Introduction Energy scheduling is the main task of power generation companies and system operators to take profit from energy trade in power market, reduce generation costs, and maintain power system security. Energy scheduling is mainly conducted through unit commitment, unit on/off scheduling. Hence, unit commitment decisions are significant to maintain reliability and cost efficiency in the power system as a whole. In general, the goal of unit commitment problem is to find a unit on/off schedule that minimizes the commitment and dispatch costs of meeting the forecasted system load, taking into account various physical, inter-temporal constraints for generating resources, transmission, and system reliability requirements [1]. From a system operator view, in the event that the actual system condition obviously deviates from the expected condition, the system operator needs to take corrective actions such as committing expensive fast-start generators, voltage reduction, or load shedding in emergency situations to maintain system security [1]. In the other hand, a generation utility tries to reduce the cost and maximize the revenues of power energy generation by producing energy in peak energy price hours. Hence, this energy scheduling model is a typically large-scale stochastic optimization decision making model which takes into account stochastic input parameters such as the demand for replacement reserves, wind and solar power energy production forecasts, load and market price forecasts. The model evaluates optimal unit commitment and economic dispatch at hourly time- resolution and minimizes the expected value of production costs of the system that comprises fuel cost, start-up cost, and variable operation and maintenance cost [2]. pp.149:155