Abstract

Abstract
The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.

Abstract
Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.

Abstract
Emerging technologies arising in modern power systems have propelled the presence of new agents to manipulate these facilities. Participation of plug-in electric vehicles (PIEVs) in the electricity market is one of the main issues in this environment. PIEV participation in market place can affect the agent's strategy. Therefore, this paper investigates two states of power system where individual aggregators participate in the power market on behalf of home-charged PIEVs and parking lots (PLs) separately, as well as the coordinated version of the problem. Several scenarios are developed for deriving specific characteristics of PIEVs in home levels and in PLs. An optimization model is built and solved using mixed integer linear programming. The results are produced to suggest the optimum procedure for an aggregator to whether take the authority of home-charging PIEVs and PLs individually or coordinately.

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.