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• The paper develops a new closed-loop hybrid system dynamics-optimization approach. • The system dynamics model and hybrid model are compared. • Energy production from waste is considered in the paper. • Social, environmental, and economic aspects are studied in the models. System dynamics approach is a tool to study socio-economic systems and make strategic decisions. However, it is not an appropriate planning method. For this purpose, optimization models are more powerful options. This paper represents a new combination of a system dynamics simulation with an optimization model to consider both aspects. For this purpose, a system dynamics model is developed to simulate the system in a feed-forward path. Then, it is connected to an already developed multi-objective optimization model on the feedback path in a real-time manner to constitute a hybrid closed-loop model. The hybrid model is applied to study the waste management system in Tehran. The focus of the hybrid model is on waste-to-energy technologies and how the system decides to install them. Comparing the hybrid model's results with those of the system dynamics model proves that the optimized policies considerably improve the system financially and environmentally. As far as technologies are concerned, the hybrid model suggests more capacities and diversity of technologies rather than the open-loop system dynamics model. Overall, the framework can be applied to all decision-making models that can add an advantage to system dynamics models. Moreover, the system dynamics model obtained through several scenarios shows that raising awareness, increasing Feed-in-Tariff, and investment in waste-to-energy technologies positively affect the waste management system. [ABSTRACT FROM AUTHOR]

Heretofore, oil prices have been continuously predicted by many researchers using various methods. Among so many factors affecting the oil market, this article foresees the future variations in oil price respecting the new emerging competitors in the oil market, namely unconventional oil, that has received less attention in previous works. The dynamics of oil prices in the global market is investigated via a system approach, regarding the strategies of different oil market players, i.e. OECD/non-OECD member countries, including the mutual causal relationships and mechanisms. Three scenarios are defined to run the model: oil market growth, current situation (base run), and oil market downturn. The results indicate that oil price, which has shown a deep decay in recent years, will gradually reach around $70 per barrel ($41 per barrel in 1993 USD) in the next five years. While there exists oversupply in the global oil market due to unconventional oil production, which will be the case in the near-term, the oil price will not increase considerably up to the year 2025. Surely, an unanticipated shock or crisis on either of the supply side or demand side (e.g. a pandemic disease) can significantly affect both spot and future prices. [Display omitted] • An SD model of oil price dynamics in the global market is developed. • Conventional and unconventional oil development is modelled. • Different oil market players are considered (OPEC/Non-OPEC, and OECD/non-OECD). • Oil price under different scenarios is simulated. • Oil price will not increase considerably up to the year 2025. [ABSTRACT FROM AUTHOR]

Renewable electricity development is not a critical concern in fossil-fuel-rich countries in the Middle East and North Africa, where fossil fuels are abundant and accessible. As a result, the growth of fossil-fuel electricity generators reduces renewable electricity competitiveness and slows its development. Since renewable electricity has an insufficient market share (less than 5% of total electricity generation in these countries, according to global statistics), its development should become a priority due to fossil-fuel depletion and demand growth in the future. The present study investigates various scenarios to examine the energy sector's development in countries facing severe competitiveness challenges of renewable electricity. Then, it recommends the most appropriate policies through evaluating the proposed plans' effectiveness. In this regard, a comprehensive framework has been developed by integrating system dynamics modeling, agent-based modeling logic, and game theory concepts. This systemic modeling procedure has several advantages, including formation of a macro policymaking perspective, the analysis of renewable electricity development trends, and the simulation of competitors' and investors' reactions and decisions. In this case, Iran is chosen for the study due to being a representative of these countries, and its data have been used to validate the proposed model. Model validation showed less than 9% error between simulation results and real data. Besides, the simulation results indicated that establishing a competitive market and enacting targeted support policies could stimulate the development of renewable electricity up to the year 2060. A presumed combined policy based on efficient simulated scenarios could increase renewable electricity capacity and market share 5-fold and 6-fold by 2035, respectively. Also, it could improve capacity and market share 8-fold and 10-fold by 2060, respectively. [Display omitted] [ABSTRACT FROM AUTHOR]

Malaysia has abundant potentials of renewable energy resources mainly because of its rich agriculture that makes high potential in bio-power and its tropical climate, which provides sufficient sunlight for utilization of solar systems. Feed in Tariff mechanism has been applied since 2011 in Malaysia to expand utilization of renewable energy for electricity generation. In this study, a broad range of data is gathered to develop a comprehensive system dynamics model to evaluate the impacts of Feed in Tariff mechanism on the generation mix of Malaysia during a 20-year period between 2011 and 2030. Results demonstrate that although the policy may lead to a satisfactory level of target achievement but the Malaysian government may face an increasing shortage in its RE fund budget starting around 2019 unless it increases its income sources by rising the surcharges on electricity bills or decreases its expenditures by optimizing the amount of FiT payments in different periods. The sensitivity analysis illustrates that the more funding will not lead to a more sustainable generation mix unless it is paid in the right time and in the right direction. Using this model, policymakers can carry out analysis to determine the amount of money that must be collected from the electricity consumers through the surcharges on electricity bills as well as the amount of feed in tariff to be paid for different renewable resources in different periods. [ABSTRACT FROM AUTHOR]