Concept of energy management for advanced smart-grid power distribution system in aeronautical application

Author(s):  
L. Rubino ◽  
D. Iannuzzi ◽  
G. Rubino ◽  
M. Coppola ◽  
P. Marino

The concept of smart grid to transform the old power grid into a smart and intelligent electric power distribution system is, currently, a hot research topic. Smart grid offers the merging of electrical power engineering technologies with network communications. Game theory has featured as an interesting technique, adopted by many researchers, to establish effective smart grid communications. The use of game theory has offered solutions to various decision-making problems, ranging from distributed load management to micro storage management in smart grid. Interestingly, different researchers have different objectives or problem scopes for adopting game theory in smart grid. This chapter explores the game-based approach.


Author(s):  
Reza Tajik

Nowadays, the utilization of renewable energy resources in distribution systems (DSs) has been rapidly increased. Since distribution generation (DG) use renewable resources (i.e., biomass, wind and solar) are emerging as proper solutions for electricity generation. Regarding the tremendous deployment of DG, common distribution networks are undergoing a transition to DSs, and the common planning methods have become traditional in the high penetration level. Indeed, in conformity with the voltage violation challenge of these resources, this problem must be dealt with too. So, due to the high penetration of DG resources and nonlinear nature of most industrial loads, the planning of DG installation has become an important issue in power systems. The goal of this paper is to determine the planning of DG in distribution systems through smart grid to minimize losses and control grid factors. In this regard, the present work intending to propose a suitable method for the planning of DSs, the key properties of DS planning problem are evaluated from the various aspects, such as the allocation of DGs, and planning, and high-level uncertainties. Also depending on these analyses, this universal literature review addressed the updated study associated with DS planning. In this work, an operational design has been prepared for a higher performance of the power distribution system in the presence of DG. Artificial neural network (ANN) has been used as a method for voltage monitoring and generation output optimization. The findings of the study show that the proposed method can be utilized as a technique to improve the process of the distribution system under various penetration levels and in the presence of DG. Also, the findings revealed that the optimal use of ANN method leads to more controllable and apparent DS.


Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2470 ◽  
Author(s):  
Alamaniotis ◽  
Gatsis

Utilization of digital connectivity tools is the driving force behind the transformation of the power distribution system into a smart grid. This paper places itself in the smart grid domain where consumers exploit digital connectivity to form partitions within the grid. Every partition, which is independent but connected to the grid, has a set of goals associated with the consumption of electric energy. In this work, we consider that each partition aims at morphing the initial anticipated partition consumption in order to concurrently minimize the cost of consumption and ensure the privacy of its consumers. These goals are formulated as two objectives functions, i.e., a single objective for each goal, and subsequently determining a multi-objective problem. The solution to the problem is sought via an evolutionary algorithm, and more specifically, the non-dominated sorting genetic algorithm-II (NSGA-II). NSGA-II is able to locate an optimal solution by utilizing the Pareto optimality theory. The proposed load morphing methodology is tested on a set of real-world smart meter data put together to comprise partitions of various numbers of consumers. Results demonstrate the efficiency of the proposed morphing methodology as a mechanism to attain low cost and privacy for the overall grid partition.


Energies ◽  
2018 ◽  
Vol 11 (3) ◽  
pp. 568 ◽  
Author(s):  
Muhammad Babar ◽  
Jakub Grela ◽  
Andrzej Ożadowicz ◽  
Phuong Nguyen ◽  
Zbigniew Hanzelka ◽  
...  

Effective Energy Management with an active Demand Response (DR) is crucial for future smart energy system. Increasing number of Distributed Energy Resources (DER), local microgrids and prosumers have an essential and real influence on present power distribution system and generate new challenges in power, energy and demand management. A relatively new paradigm in this field is transactive energy (TE), with its value and market-based economic and technical mechanisms to control energy flows. Due to a distributed structure of present and future power system, the Internet of Things (IoT) environment is needed to fully explore flexibility potential from the end-users and prosumers, to offer a bid to involved actors of the smart energy system. In this paper, new approach to connect the market-driven (bottom-up) DR program with current demand-driven (top-down) energy management system (EMS) is presented. Authors consider multi-agent system (MAS) to realize the approach and introduce a concept and standardize the design of new Energy Flexometer. It is proposed as a fundamental agent in the method. Three different functional blocks have been designed and presented as an IoT platform logical interface according to the LonWorks technology. An evaluation study has been performed as well. Results presented in the paper prove the proposed concept and design.


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