Finding a renewable energy policy using agent based modeling

The dwindling supply of current energy resources has forced an increasing interest in renewable resources while spawning legislative action to increase the energy demand met by renewable resources with several states developing renewable portfolio standards (RPS). Long-term investment policies are necessary to meet RPSs but the method of developing strategies varies by state. Further complications arise from the lack of uniformity of renewable energy sources' access across the United States. While individual policies can be developed, the nation may improve performance with federally set RPSs and pooled budgets and resources. Current research focuses on developing portfolios with optimization methods for individual states. Unfortunately, these models fail to find a long-term investment strategy that meets investment constraints and yearly state targets or fail to attack the issue of pooling resources. Agent based modeling has recently become a tool that aids in policy development because the approach allows agents to interact and cooperate while maintaining their own goals. This research focuses on utilizing agent based modeling to improve the knowledge of decision makers by determining investment policies for individual states based on their willingness to cooperate with different states such that the RPS requirements are met.