Under the smart grid environment, demand response resources (DRRs) are introduced as a virtual power plant to enhance power system adequacy. DRRs often fail to reduce their load due to some external factors. In this paper, a reliability model of a DRR is constructed as multi-state conventional generation units, where the probability, frequency of occurrence, and departure rate of each state can...

A major problem in insect pest and weed management is uncertainty. Managers are faced with three main types of uncertainty: uncertainty about biological and environmental processes, and observational uncertainty. Active adaptive management (AAM) is management with a deliberate plan for learning about the managed system, so that management can be improved in the face of uncertainty. We discuss t...

Adaptive management is a systematic approach for improving environmental management by learning from management outcomes. We believe that protected areas management can benefit greatly from this approach which allows management to proceed despite uncertainty, and reduces this uncertainty through a systematic process for learning. We describe this approach as a six-stage process: problem assessm...

Congestion management in electricity markets is traditionally done using deterministic values of power system parameters considering a fixed network configuration. In this paper, a stochastic programming framework is proposed for congestion management considering the power system uncertainties. The uncertainty sources that are modeled in the proposed stochastic framework consist of contingencie...

Among others who point to environmental variability and managerial uncertainty as causes of fishery collapse, Roughgarden and Smith (1996) argue that three sources of uncertainty are important for fisheries management: variability in fish dynamics, inaccurate stock size estimates, and inaccurate implementation of harvest quotas. We develop a bioeconomic model with these three sources of uncerta...