Abstract
Smart local energy networks provide an opportunity for more penetration of distributed energy resources. However, these resources cause an extra dependency in both time and carrier domains that should be considered through a comprehensive model. Hence, this paper introduces a new concept for internal and external dependencies in Smart Multi-Energy Systems (SMES). Internal dependencies are caused by converters and storages existing in operation centers and modeled by coupling matrix. On the other hand, external dependencies are defined as the behavior of multi-energy demand in shifting among carriers or time periods. In this paper, system dependency is modeled based on energy hub approach through adding virtual ports and making new coupling matrix. Being achieved by SMESs, the dependencies release demand-side flexibility and subsequently enhance system efficiency. Moreover, a test SMES that includes several elements and multi-energy demand in output is applied to show the effectiveness of the model.

Abstract
Smart local energy networks represent a key option for more penetration of sustainably developed facilities. These facilities can cause an extended dependency in both time and carrier domains which should be considered through a comprehensive model. This paper introduces a new concept of internal and external dependencies. The concept is related to penetration of energy converters on demand side and the effects they bring to the system. Being achieved by implementation of smart grid, dependencies release operational flexibility and subsequently enhance the system efficiency. The model contains, carrier based demand response which preserves consumers satisfaction by utilizing the flexibility in exchanging the input energy carrier instead of changing end-usage pattern. The paper develops the coupling matrix model for smart multi-energy systems considering the external dependency as an added module to the overall model.

Abstract
New technologies such as Plug-in Electric Vehicles or PEVs bring new trends in areas where multi entities interact. One of these areas is the facilities in cities for better manipulation of technologies. Encouraging the utilization of PEVs necessitates the provision of charging stations. In this regard, PEV Parking Lots (PLs) can be a great help as they can solve both urban and electrical problem of PEVs. On the other hand, gathering numerous PEVs in one point like PLs provides the system operator with the opportunity of PEVs batteries that can be used as potential storages. Therefore, in this paper, the optimum behavior of PEV PLs is modeled while they contribute their batteries' capacity in both energy and reserve market. The charging schedule of PLs with various numbers of stations has been reported as well as their share in the market as an energy source during peak hours.

Abstract
In this paper, a mixed-integer linear programing ( MILP) model for the traffic behavior of plug-in electric vehicles ( PEVs) in an urban environment is proposed. It is assumed that any environment can be categorized into different zones based on their urban functions ( e. g. industrial, residential, and commercial). Therefore, the interaction of PEVs that travel between these zones has to be modeled. Besides, it is assumed that in each zone a parking lot ( PL) and individual charging stations exist to provide the required state of charge ( SOC) for PEVs during their daily travel. As a result, the amount of power that these PEVs consume ( rather in PL or charging stations) and the amount of SOC that PEVs carry with them should be precisely computed. The proposed MILP model is applied on two zones urban area with residential and industrial districts and the numerical results prove the proficiency of the model.

Abstract
The increasing penetration of plug-in electric vehicles (PEVs) has encouraged solutions for facilitating their utilization. In this regard, PEV parking lots (PLs) have proved to be essential for future systems with high amounts of PEVs. However, operating a PL in order to maximize its profit while enforcing its own constraints generates conflicts between the PL and the distribution system operator (DSO). As a result, this paper proposes a model to solve the PL equilibria behavior. A bi-level problem including the operation of DSO and PL is solved using mathematical programming with equilibrium constraints (MPEC). The PL's behavior is defined by its hourly energy and reserve interaction with the market through the DSO. As the total amount of PL's interaction with the grid will affect the DSO's operational decision making, the proposed model finds the equilibrium point to maximize the benefit for PL and DSO.

Abstract
In a multienergy system, there are different types of dependencies among the energy carriers. Internal dependencies refer to possible changes in the energy source in the presence of energy converters and storage, and are managed by the system operator through the control strategies applied to the equipment. External dependencies (EDs) are due to the choice of the energy supply according to customer preferences when alternative solutions are available. This paper introduces a new model of EDs within a multigeneration representation based on energy hubs. EDs are addressed through a stochastic model in order to take into account the possible uncertainty in the customers' decisions. This model is then used to introduce carrier-based demand response (DR) in which the user participates in DR programs aimed at promoting the shifting among different energy sources by preserving the service provided to the end users. The results obtained from the new model in deterministic and stochastic cases indicate the appropriateness and usefulness of the proposed approach.