The climate change around the globe driven by Greenhouse Gas emissions (GHG) is fueling the growth of Sustainable Energy Systems (SES) at a faster pace. However, the lack of acceptance of these systems by society has stifled its successful deployment. Societal values play a key role in evaluating the social acceptance and the broader consequences of SES. However, there exists a complexity of change in the values of people. Alternatively known as value change, although SES may embody values permanently during its design, the values that people hold important may change during the lifetime of SES. Value change may often be driven by various exogenous factors as well as due to the complex, emergent, and dynamic characteristics of SES. Consequently, this has led to high uncertainty in the future acceptance of SES. Exploring the uncertain scenarios of value change is crucial for social acceptance of SES as it can facilitate better consideration of values in evaluating social acceptance of SES, ultimately contributing to the future acceptability of SES by society. However, current approaches to explore value change in ethics of technology literature are scarce. Few have proposed to explore value change, but lack in dealing with value change after it has occurred, or they consider values in a static manner. Alternatively, simulation models show better prospects in exploring complex societal dynamics of which a human mind cannot picture. Simulation models such as Agent-Based Models are seen as a suitable solution to capture the underlying mechanisms that drive the value change considering the complex and dynamic characteristics of SES. The objective of this research is to gain an understanding of the mechanisms that drive the value change in SES, by formulating a modelling approach that integrates agent heterogeneity, common pool resource & dynamic behavior, transformative experience & bounded rationality, and social interaction, to explore value change under various policy and uncertainty scenarios of SES. To this end, this study combined Agent-Based Modelling and Exploratory Modelling approaches to explore the change in importance of values in SES.