Sharif Digital Repository

Cooperation and competition between pathogens can alter the amount of individuals affected by a coinfection. Nonetheless, the evolution of the pathogens' behavior has been overlooked. Here, we consider a coevolutionary model where the simultaneous spreading is described by a two-pathogen susceptible-infected-recovered model in an either synergistic or competitive manner. At the end of each epidemic season, the pathogens species reproduce according to their fitness that, in turn, depends on the payoff accumulated during the spreading season in a hawk-and-dove game. This coevolutionary model displays a rich set of features. Specifically, the evolution of the pathogens' strategy induces abrupt... 

In deregulated power systems, distribution network operators (DNO) are responsible for maintaining the proper operation and efficiency of distribution networks. This is achieved traditionally through specific investments in network components. The event of distributed generation (DG) has introduced new challenges to these distribution networks. The role of DG units must be correctly assessed to optimise the overall operating and investment cost for the whole system. However, the distributed generation owners (DGOs) have different objective functions which might be contrary to the objectives of DNO. This study presents a long-term dynamic multi-objective model for planning of distribution... 

This paper presents a long-term dynamic multi-objective planning model for distribution network expansion along with distributed energy options. The proposed model optimizes two objectives, namely costs and emissions and determines the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on distributed generation units and network reinforcements over the planning period. An efficient two-stage heuristic method is proposed to solve the formulated planning problem. The effectiveness of the proposed model is demonstrated by applying it to a distribution network and comparing the simulation results with other methods and models  

This paper presents a long-term dynamic multi-objective model for distributed generation investment. The proposed model optimizes three objectives, namely active losses, costs and environmental emissions and determines the optimal schemes of sizing, sitting of DG units and specially the dynamics of investment over the planning period. The Pareto optimal solutions of the problem are found using a GA algorithm and finally a fuzzy satisfying method is applied to select the optimal solution considering the desires of the planner. The solutions of Pareto optimal front are analyzed to extract general useful information for planners about the appropriate DG technologies and placement schemes. The...