Energies 2015,8 11001 However,these software have some limitations for simulating occupant energy-use behavior.The main limitation is that they assume the same energy use pattern for all occupants in a building,and this pattern is constant over time [18,24,28,71-73].In fact,they are not able to account for dynamic aspects of occupancy.Due to these limitation,the energy use estimated by these software normally deviates from the real levels by up to 30 percent [5,28,74].Furthermore,in addition to traditional software,traditional building management systems also have limitations with real-time inputs of occupancy-related dynamic factors,such as the number of occupants and their preferences,actions,and decisions [63].This limitation is problematic since the inputs of real-time occupancy information can reduce HVAC and lighting energy consumption by up to 20 and 30 percent,respectively [56,66,67,75].In response to these limitations in modeling occupants'energy-use behaviors,a number of studies have recently worked on various simulation techniques to attempt to overcome these particular limitations. It is noteworthy that the developed energy-modeling and simulation tools for modeling occupants' energy-related characteristics and behaviors(discussed below)are mainly used during the early phase (i.e.,design phase)of buildings [73,76-78].Such tools could help users to choose the correct size and most energy-efficient building systems and the appliances that are proportionate to the number of occupants.These tools,therefore,help to improve overall building simulation capabilities.However, to achieve the best results,the application of these tools should be very sensitive to occupants'input parameters to accurately represent occupants'actions [73,79].In fact,these tools could be used to analyze the specific dynamics for all individual occupants,and could be calibrated to ensure that they can be used for all sizes of commercial buildings with different numbers of occupants.Researchers might also set the simulations to consider the decreased occupancy of after-hours and non-working days. To maximize the benefits of such software,the systems should be flexible enough to consider all possible occupant actions as well as all of the common practices of occupants. In addition to simulating the design phase of the buildings,simulation tools could also be used during other phases such as the construction and operation phases [28,63,75,80-83].For instance,within the renovation phase of buildings,such tools could help decision makers choose the most efficient appliances/systems when making a purchase.In addition,the use of such simulation techniques would help avoid the real resource-intensive process of testing which appliances and systems work well for a building.Time of a run,accuracy,and versatility(i.e.,solving different occupancy problems in any commercial building)are the main criteria that must be evaluated for occupancy simulation tools [50]. Many effective options are discussed below. 3.1.Agent-Based Modeling Simulation research has indicated that occupants'dynamic energy use patterns can result in significant variations in energy consumption in the commercial sector [28].In particular,a significant number of simulations employed Agent-Based Modeling (ABM)techniques to overcome software limitations in order to simulate actions and interactions between occupants and their built environment.These simulations sought to better predict building operational energy performance during the design phase.ABM is a kind of computational model that simulates the actions and interactions of agents with each other and their environments [84];in ABM,building occupants are agents in the built environment.Unlike most mathematical models,ABM agents have heterogeneous features and abilities [85].Energies 2015, 8 11001 However, these software have some limitations for simulating occupant energy-use behavior. The main limitation is that they assume the same energy use pattern for all occupants in a building, and this pattern is constant over time [18,24,28,71–73]. In fact, they are not able to account for dynamic aspects of occupancy. Due to these limitation, the energy use estimated by these software normally deviates from the real levels by up to 30 percent [5,28,74]. Furthermore, in addition to traditional software, traditional building management systems also have limitations with real-time inputs of occupancy-related dynamic factors, such as the number of occupants and their preferences, actions, and decisions [63]. This limitation is problematic since the inputs of real-time occupancy information can reduce HVAC and lighting energy consumption by up to 20 and 30 percent, respectively [56,66,67,75]. In response to these limitations in modeling occupants’ energy-use behaviors, a number of studies have recently worked on various simulation techniques to attempt to overcome these particular limitations. It is noteworthy that the developed energy-modeling and simulation tools for modeling occupants’ energy-related characteristics and behaviors (discussed below) are mainly used during the early phase (i.e., design phase) of buildings [73,76–78]. Such tools could help users to choose the correct size and most energy-efficient building systems and the appliances that are proportionate to the number of occupants. These tools, therefore, help to improve overall building simulation capabilities. However, to achieve the best results, the application of these tools should be very sensitive to occupants’ input parameters to accurately represent occupants’ actions [73,79]. In fact, these tools could be used to analyze the specific dynamics for all individual occupants, and could be calibrated to ensure that they can be used for all sizes of commercial buildings with different numbers of occupants. Researchers might also set the simulations to consider the decreased occupancy of after-hours and non-working days. To maximize the benefits of such software, the systems should be flexible enough to consider all possible occupant actions as well as all of the common practices of occupants. In addition to simulating the design phase of the buildings, simulation tools could also be used during other phases such as the construction and operation phases [28,63,75,80–83]. For instance, within the renovation phase of buildings, such tools could help decision makers choose the most efficient appliances/systems when making a purchase. In addition, the use of such simulation techniques would help avoid the real resource-intensive process of testing which appliances and systems work well for a building. Time of a run, accuracy, and versatility (i.e., solving different occupancy problems in any commercial building) are the main criteria that must be evaluated for occupancy simulation tools [50]. Many effective options are discussed below. 3.1. Agent-Based Modeling Simulation research has indicated that occupants’ dynamic energy use patterns can result in significant variations in energy consumption in the commercial sector [28]. In particular, a significant number of simulations employed Agent-Based Modeling (ABM) techniques to overcome software limitations in order to simulate actions and interactions between occupants and their built environment. These simulations sought to better predict building operational energy performance during the design phase. ABM is a kind of computational model that simulates the actions and interactions of agents with each other and their environments [84]; in ABM, building occupants are agents in the built environment. Unlike most mathematical models, ABM agents have heterogeneous features and abilities [85]