This paper presents a generic framework for the modeling of energy systems comprising multiple-energy carriers, such as electricity, heat, gas, biomass, etc. The modeling framework is based on the so-called energy hub approach. The core idea of the energy hub is the definition of a conversion matrix capable of describing the interactions of production, delivery, and consumption in multiple-energy carrier systems. Based on the energy hub concept a broad spectrum of modeling extensions and applications is presented, such as a multiple-energy carrier optimal power flow, risk management and investment analysis tools, agent-based control schemes for decentralized generation units as well as the possibility to analyze the influence of plug-in hybrid electric vehicles (PHEVs) on future energy systems. The paper is concluded with a section presenting the key benefits of the energy hub modeling framework, followed by a discussion on the main design principles generality, scalability, and modularity as well as a discussion on the possibility to follow top-down or bottom-up modeling strategies.

Power flow studies are typically used to determine the steady state or operating conditions of power systems for specified sets of load and generation values, and is one of the most intensely used tools in power engineering. When the input conditions are uncertain, numerous scenarios need to be analyzed to cover the required range of uncertainty. Under such conditions, reliable solution algorithms that incorporate the effect of data uncertainty into the power flow analysis are required. To address this problem, this paper proposes a new solution methodology based on the use of affine arithmetic, which is an enhanced model for self-validated numerical analysis in which the quantities of interest are represented as affine combinations of certain primitive variables representing the sources of uncertainty in the data or approximations made during the computation. The application of this technique to the power flow problem is explained in detail, and several numerical results are presented and discussed, demonstrating the effectiveness of the proposed methodology, especially in comparison to previously proposed interval arithmetic's techniques.

In this paper, we propose a decentralized and self-organizing solution framework aimed at addressing economic dispatch (ED) analysis in a distributed scenario. In particular we will demonstrate that, under some hypotheses, the solution of the ED analysis can be obtained by computing proper weighted averages of the variable of interests. To compute these global quantities we propose the deployment of a network of cooperative dynamic agents solving distributed average consensus problems. Thanks to this decentralized/nonhierarchical paradigm, all the basic operations needed to solve the economic dispatch problem could be easily processed by the agents. Simulation results obtained on the 118 and 300 bus IEEE test networks are presented and discussed in order to prove the effectiveness of the proposed framework.

Optimal voltage regulation is one of the main issues to address in a Smart Grid context. In this domain, the application of traditional hierarchical control paradigms has some disadvantages that could hinder their application in Smart Grids where the constant growth of grid complexity and the need for massive pervasion of distribution generation systems require more scalable and more flexible control and regulation paradigms. To try and overcome these challenges, this paper proposes the concept of a decentralized nonhierarchal voltage regulation architecture based on intelligent and cooperative smart entities. This paper intends to bring two main contributions to the existing literature. The first is the definition of a decentralized architecture aimed at computing the actual value of the cost function and its gradient without the need of a central fusion center acquiring and processing all the sensor acquisitions. The second is the proposal of a distributed and cooperative optimization strategy aimed at identifying the optimal asset of the voltage controllers.

The microgrid (MG) paradigm is a new concept which is considered as a solution for addressing technical, economical, and environmental issues of modern power systems. The application of MG is the subject of extensive studies and experimental tests. It is recognized that there are a number of technical challenges concerning the operation, monitoring, control, and protection of MGs systems. In this respect, the rapid development of the information and communication technologies (ICTs) has opened the door for feasible and cost-effective solutions allowing more extensive intra- and interutility information exchange, diffusion, and open access to a wide range of real-time information. Consequently, the ICTs could represent a strategic tool in supporting effective MG operation. According to this statement, the paper proposes an advanced framework based on the service-oriented architectures for integrated MG modeling, monitoring, and control. The proposed framework is platform, language, and vendor independent, and thus it is an ideal candidate for an effective integration in existing energy management systems and distribution management systems (EMSs/DMSs).