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Special Issue "Innovative Methods for Smart Grids Planning and Management"

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: 31 August 2017

Special Issue Editors

Guest Editor
Prof. Dr. Pierluigi Siano

Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, Fisciano (SA) 84084, Italy
Website | E-Mail
Interests: smart grids; demand response; electricity markets; power systems; renewable energy sources
Guest Editor
Dr. Miadreza Shafie-khah

Department of Industrial Engineering, University of Salerno, Via Giovanni Paolo II, 132, Fisciano (SA) 84084, Italy
E-Mail
Interests: smart grid; demand response; electric vehicle; power system; electricity market

Special Issue Information

Dear Colleagues,

We would like to invite submissions to a Special Issue of Energies on the subject of “Innovative Methods for Smart Grids Planning and Management”. In order to meet social requirements and economic improvements, current power systems have to be modernized; thus, providing a cost-efficient, eco-friendly, and sustainable energy is one of the main issues in modern societies. In response to this demand, new features of smart grid technology have provided enormous potential to have a more reliable, flexible, efficient, and resilient grid. The purpose of this Special Issue is to encourage researchers to address many of the challenges faced by the transition to a smart grid.

Prof. Dr. Pierluigi Siano

Dr. Miadreza Shafie-khah
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • electrical power and energy systems

  • smart cities

  • smart grids

  • planning

  • management

Published Papers (15 papers)

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Research

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Open AccessArticle Secure Plug-in Electric Vehicle PEV Charging in a Smart Grid Network
Energies 2017, 10(7), 1024; doi:10.3390/en10071024
Received: 26 June 2017 / Revised: 12 July 2017 / Accepted: 13 July 2017 / Published: 19 July 2017
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Abstract
Charging of plug-in electric vehicles (PEVs) exposes smart grid systems and their users to different kinds of security and privacy attacks. Hence, a secure charging protocol is required for PEV charging. Existing PEV charging protocols are usually based on insufficiently represented and simplified
[...] Read more.
Charging of plug-in electric vehicles (PEVs) exposes smart grid systems and their users to different kinds of security and privacy attacks. Hence, a secure charging protocol is required for PEV charging. Existing PEV charging protocols are usually based on insufficiently represented and simplified charging models that do not consider the user’s charging modes (charging at a private location, charging as a guest user, roaming within one’s own supplier network or roaming within other suppliers’ networks). However, the requirement for charging protocols depends greatly on the user’s charging mode. Consequently, available solutions do not provide complete protocol specifications. Moreover, existing protocols do not support anonymous user authentication and payment simultaneously. In this paper, we propose a comprehensive end-to-end charging protocol that addresses the security and privacy issues in PEV charging. The proposed protocol uses nested signatures to protect users’ privacy from external suppliers, their own suppliers and third parties. Our approach supports anonymous user authentication, anonymous payment, as well as anonymous message exchange between suppliers within a hierarchical smart grid architecture. We have verified our protocol using the AVISPA software verification tool and the results showed that our protocol is secure and works as desired. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessArticle Electric Power Grids Distribution Generation System for Optimal Location and Sizing—A Case Study Investigation by Various Optimization Algorithms
Energies 2017, 10(7), 960; doi:10.3390/en10070960
Received: 6 May 2017 / Revised: 1 July 2017 / Accepted: 5 July 2017 / Published: 10 July 2017
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Abstract
In this paper, the approach focused on the variables involved in assessing the quality of a distributed generation system are reviewed in detail, for its investigation and research contribution. The aim to minimize the electric power losses (unused power consumption) and optimize the
[...] Read more.
In this paper, the approach focused on the variables involved in assessing the quality of a distributed generation system are reviewed in detail, for its investigation and research contribution. The aim to minimize the electric power losses (unused power consumption) and optimize the voltage profile for the power system under investigation. To provide this assessment, several experiments have been made to the IEEE 34-bus test case and various actual test cases with the respect of multiple Distribution Generation DG units. The possibility and effectiveness of the proposed algorithm for optimal placement and sizing of DG in distribution systems have been verified. Finally, four algorithms were trailed: simulated annealing (SA), hybrid genetic algorithm (HGA), genetic algorithm (GA), and variable neighbourhood search. The HGA algorithm was found to produce the best solution at a cost of a longer processing time. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessArticle A Behavioral Economics Approach to Residential Electricity Consumption
Energies 2017, 10(6), 768; doi:10.3390/en10060768
Received: 20 April 2017 / Revised: 27 May 2017 / Accepted: 29 May 2017 / Published: 1 June 2017
PDF Full-text (2311 KB) | HTML Full-text | XML Full-text
Abstract
Consumer behavior is complex and is difficult to represent in traditional economic theories of decision-making. This paper focuses on the development of an agent-based approach to analyze people’s behavior in consuming electricity using a behavioral economics framework, where the consumer is the main
[...] Read more.
Consumer behavior is complex and is difficult to represent in traditional economic theories of decision-making. This paper focuses on the development of an agent-based approach to analyze people’s behavior in consuming electricity using a behavioral economics framework, where the consumer is the main agent of power systems. This approach may bring useful insights for distribution companies and regulatory agencies, helping to shift thinking to a more user-centric approach. The emergent properties of electricity consumption are modeled by the means of consumer’s heuristics, taking into account the electricity price, consumer’s satisfaction level, willingness to invest in new technologies, social interactions, and marketing strategies by the power utility. Analysis on the emergent behavior of this approach through simulation studies showed that it is indeed valuable, as does not require in-depth data of all details on human behavior. However, it contributes to the understanding of relations among various objects involved in electricity consumption. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessArticle A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations
Energies 2017, 10(5), 675; doi:10.3390/en10050675
Received: 22 March 2017 / Revised: 25 April 2017 / Accepted: 8 May 2017 / Published: 11 May 2017
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Abstract
Charging station location decisions are a critical element in mainstream adoption of electric vehicles (EVs). The consumer confidence in EVs can be boosted with the deployment of carefully-planned charging infrastructure that can fuel a fair number of trips. The charging station (CS) location
[...] Read more.
Charging station location decisions are a critical element in mainstream adoption of electric vehicles (EVs). The consumer confidence in EVs can be boosted with the deployment of carefully-planned charging infrastructure that can fuel a fair number of trips. The charging station (CS) location problem is complex and differs considerably from the classical facility location literature, as the decision parameters are additionally linked to a relatively longer charging period, battery parameters, and available grid resources. In this study, we propose a three-layered system model of fast charging stations (FCSs). In the first layer, we solve the flow capturing location problem to identify the locations of the charging stations. In the second layer, we use a queuing model and introduce a resource allocation framework to optimally provision the limited grid resources. In the third layer, we consider the battery charging dynamics and develop a station policy to maximize the profit by setting maximum charging levels. The model is evaluated on the Arizona state highway system and North Dakota state network with a gravity data model, and on the City of Raleigh, North Carolina, using real traffic data. The results show that the proposed hierarchical model improves the system performance, as well as the quality of service (QoS), provided to the customers. The proposed model can efficiently assist city planners for CS location selection and system design. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessArticle Research and Application of Hybrid Forecasting Model Based on an Optimal Feature Selection System—A Case Study on Electrical Load Forecasting
Energies 2017, 10(4), 490; doi:10.3390/en10040490
Received: 30 January 2017 / Revised: 10 March 2017 / Accepted: 27 March 2017 / Published: 5 April 2017
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Abstract
The process of modernizing smart grid prominently increases the complexity and uncertainty in scheduling and operation of power systems, and, in order to develop a more reliable, flexible, efficient and resilient grid, electrical load forecasting is not only an important key but is
[...] Read more.
The process of modernizing smart grid prominently increases the complexity and uncertainty in scheduling and operation of power systems, and, in order to develop a more reliable, flexible, efficient and resilient grid, electrical load forecasting is not only an important key but is still a difficult and challenging task as well. In this paper, a short-term electrical load forecasting model, with a unit for feature learning named Pyramid System and recurrent neural networks, has been developed and it can effectively promote the stability and security of the power grid. Nine types of methods for feature learning are compared in this work to select the best one for learning target, and two criteria have been employed to evaluate the accuracy of the prediction intervals. Furthermore, an electrical load forecasting method based on recurrent neural networks has been formed to achieve the relational diagram of historical data, and, to be specific, the proposed techniques are applied to electrical load forecasting using the data collected from New South Wales, Australia. The simulation results show that the proposed hybrid models can not only satisfactorily approximate the actual value but they are also able to be effective tools in the planning of smart grids. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessFeature PaperArticle Experimental Results on a Wireless Wattmeter Device for the Integration in Home Energy Management Systems
Energies 2017, 10(3), 398; doi:10.3390/en10030398
Received: 4 December 2016 / Revised: 23 February 2017 / Accepted: 13 March 2017 / Published: 20 March 2017
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Abstract
This paper presents a home area network (HAN)-based domestic load energy consumption monitoring prototype device as part of an advanced metering system (AMS). This device can be placed on individual loads or configured to measure several loads as a whole. The wireless communication
[...] Read more.
This paper presents a home area network (HAN)-based domestic load energy consumption monitoring prototype device as part of an advanced metering system (AMS). This device can be placed on individual loads or configured to measure several loads as a whole. The wireless communication infrastructure is supported on IEEE 805.12.04 radios that run a ZigBee stack. Data acquisition concerning load energy transit is processed in real time and the main electrical parameters are then transmitted through a RF link to a wireless terminal unit, which works as a data logger and as a human-machine interface. Voltage and current sensing are implemented using Hall effect principle-based transducers, while C code is developed on two 16/32-bit microcontroller units (MCUs). The main features and design options are then thoroughly discussed. The main contribution of this paper is that the proposed metering system measures the reactive energy component through the Hilbert transform for low cost measuring device systems. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessFeature PaperArticle Real-Time Forecasting of EV Charging Station Scheduling for Smart Energy Systems
Energies 2017, 10(3), 377; doi:10.3390/en10030377
Received: 7 November 2016 / Revised: 11 March 2017 / Accepted: 13 March 2017 / Published: 16 March 2017
Cited by 1 | PDF Full-text (5790 KB) | HTML Full-text | XML Full-text
Abstract
The enormous growth in the penetration of electric vehicles (EVs), has laid the path to advancements in the charging infrastructure. Connectivity between charging stations is an essential prerequisite for future EV adoption to alleviate user’s “range anxiety”. The existing charging stations fail to
[...] Read more.
The enormous growth in the penetration of electric vehicles (EVs), has laid the path to advancements in the charging infrastructure. Connectivity between charging stations is an essential prerequisite for future EV adoption to alleviate user’s “range anxiety”. The existing charging stations fail to adopt power provision, allocation and scheduling management. To improve the existing charging infrastructure, data based on real-time information and availability of reserves at charging stations could be uploaded to the users to help them locate the nearest charging station for an EV. This research article focuses on an a interactive user application developed through SQL and PHP platform to allocate the charging slots based on estimated battery parameters, which uses data communication with charging stations to receive the slot availability information. The proposed server-based real-time forecast charging infrastructure avoids waiting times and its scheduling management efficiently prevents the EV from halting on the road due to battery drain out. The proposed model is implemented using a low-cost microcontroller and the system etiquette tested. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessArticle Engineering Smart Grids: Applying Model-Driven Development from Use Case Design to Deployment
Energies 2017, 10(3), 374; doi:10.3390/en10030374
Received: 20 December 2016 / Revised: 28 February 2017 / Accepted: 9 March 2017 / Published: 16 March 2017
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Abstract
The rollout of smart grid solutions has already started and new methods are deployed to the power systems of today. However, complexity is still increasing as focus is moving from a single system, to a system of systems perspective. The results are increasing
[...] Read more.
The rollout of smart grid solutions has already started and new methods are deployed to the power systems of today. However, complexity is still increasing as focus is moving from a single system, to a system of systems perspective. The results are increasing engineering efforts and escalating costs. For this reason, new and automated engineering methods are necessary. This paper addresses these needs with a rapid engineering methodology that covers the overall engineering process for smart grid applications—from use case design to deployment. Based on a model-driven development approach, the methodology consists of three main parts: use case modeling, code generation, and deployment. A domain-specific language is introduced supporting the use case design according to the Smart Grid Architecture Model. It is combined with the IEC 61499 distributed control model to improve the function layer design. After a completed use case design, executable code and communication configurations (e.g., IEC 61850) are generated and deployed onto compatible field devices. This paper covers the proposed rapid engineering methodology and a corresponding prototypical implementation which is validated in a laboratory experiment. Compared to other methods the proposed methodology decreases the number of engineering steps and reduces the use case design and implementation complexity. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessArticle Strategic Maintenance Scheduling of an Offshore Wind Farm in a Deregulated Power System
Energies 2017, 10(3), 313; doi:10.3390/en10030313
Received: 21 December 2016 / Accepted: 1 March 2017 / Published: 6 March 2017
Cited by 2 | PDF Full-text (1322 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a model for strategic maintenance scheduling of offshore wind farms (SMSOWF) in a deregulated power system. The objective of the model is to plan the maintenance schedules in a way to maximize the profit of the offshore wind farm. In
[...] Read more.
This paper proposes a model for strategic maintenance scheduling of offshore wind farms (SMSOWF) in a deregulated power system. The objective of the model is to plan the maintenance schedules in a way to maximize the profit of the offshore wind farm. In addition, some network constraints, such as transmission lines capacity, and wind farm constraints, such as labor working shift, wave height limit and wake effect, as well as unexpected outages, are included in deterministic and stochastic studies. Moreover, the proposedmodel provides theability to incorporate information from condition monitoring systems. SMSOWF is formulated through a bi-level formulation and then transformed into a single-level through Karush–Kuhn–Tucker conditions. The model is validated through a test system, and the results demonstrate applicability, advantages and challenges of harnessing the full potential of the model. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessArticle Improvement of Wind Energy Production through HVDC Systems
Energies 2017, 10(2), 157; doi:10.3390/en10020157
Received: 26 October 2016 / Revised: 19 December 2016 / Accepted: 10 January 2017 / Published: 27 January 2017
Cited by 1 | PDF Full-text (5793 KB) | HTML Full-text | XML Full-text
Abstract
Variable and non-programmable resources, such as solar and wind, have undergone a stunning growth in recent years and are likely to gain even more importance in the future. Their strong presence in the national electricity mix has created issues in many countries regarding
[...] Read more.
Variable and non-programmable resources, such as solar and wind, have undergone a stunning growth in recent years and are likely to gain even more importance in the future. Their strong presence in the national electricity mix has created issues in many countries regarding the secure operation of the power system. In order to guarantee the stability of the system, several TSOs have resorted to wind energy curtailment, which represents a waste of clean energy and an economic loss. In order to analyze this issue, a model of the Italian power system was developed, a program able to simulate the electricity dispatching mechanism. The model was, then, used to evaluate possible solutions to reduce wind curtailment. In particular, a proposal for the construction of an HVDC line linking Southern and Northern Italy was studied. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessArticle Efficient Energy Consumption Scheduling: Towards Effective Load Leveling
Energies 2017, 10(1), 105; doi:10.3390/en10010105
Received: 7 November 2016 / Revised: 29 December 2016 / Accepted: 12 January 2017 / Published: 17 January 2017
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Abstract
Different agents in the smart grid infrastructure (e.g., households, buildings, communities) consume energy with their own appliances, which may have adjustable usage schedules over a day, a month, a season or even a year. One of the major objectives of the smart grid
[...] Read more.
Different agents in the smart grid infrastructure (e.g., households, buildings, communities) consume energy with their own appliances, which may have adjustable usage schedules over a day, a month, a season or even a year. One of the major objectives of the smart grid is to flatten the demand load of numerous agents (viz. consumers), such that the peak load can be avoided and power supply can feed the demand load at anytime on the grid. To this end, we propose two Energy Consumption Scheduling (ECS) problems for the appliances held by different agents at the demand side to effectively facilitate load leveling. Specifically, we mathematically model the ECS problems as Mixed-Integer Programming (MIP) problems using the data collected from different agents (e.g., their appliances’ energy consumption in every time slot and the total number of required in-use time slots, specific preferences of the in-use time slots for their appliances). Furthermore, we propose a novel algorithm to efficiently and effectively solve the ECS problems with large-scale inputs (which are NP-hard). The experimental results demonstrate that our approach is significantly more efficient than standard benchmarks, such as CPLEX, while guaranteeing near-optimal outputs. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessArticle Correlation Feature Selection and Mutual Information Theory Based Quantitative Research on Meteorological Impact Factors of Module Temperature for Solar Photovoltaic Systems
Energies 2017, 10(1), 7; doi:10.3390/en10010007
Received: 2 September 2016 / Revised: 10 December 2016 / Accepted: 15 December 2016 / Published: 22 December 2016
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Abstract
The module temperature is the most important parameter influencing the output power of solar photovoltaic (PV) systems, aside from solar irradiance. In this paper, we focus on the interdisciplinary research that combines the correlation analysis, mutual information (MI) and heat transfer theory, which
[...] Read more.
The module temperature is the most important parameter influencing the output power of solar photovoltaic (PV) systems, aside from solar irradiance. In this paper, we focus on the interdisciplinary research that combines the correlation analysis, mutual information (MI) and heat transfer theory, which aims to figure out the correlative relations between different meteorological impact factors (MIFs) and PV module temperature from both quality and quantitative aspects. The identification and confirmation of primary MIFs of PV module temperature are investigated as the first step of this research from the perspective of physical meaning and mathematical analysis about electrical performance and thermal characteristic of PV modules based on PV effect and heat transfer theory. Furthermore, the quantitative description of the MIFs influence on PV module temperature is mathematically formulated as several indexes using correlation-based feature selection (CFS) and MI theory to explore the specific impact degrees under four different typical weather statuses named general weather classes (GWCs). Case studies for the proposed methods were conducted using actual measurement data of a 500 kW grid-connected solar PV plant in China. The results not only verified the knowledge about the main MIFs of PV module temperatures, more importantly, but also provide the specific ratio of quantitative impact degrees of these three MIFs respectively through CFS and MI based measures under four different GWCs. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessArticle Evaluation of Conservation Voltage Reduction with Analytic Hierarchy Process: A Decision Support Framework in Grid Operations Planning
Energies 2016, 9(12), 1074; doi:10.3390/en9121074
Received: 1 November 2016 / Revised: 3 December 2016 / Accepted: 12 December 2016 / Published: 16 December 2016
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Abstract
This paper presents a systematic framework to evaluate the performance of conservation voltage reduction (CVR) by determining suitable substations for CVR in operations planning. Existing CVR planning practice generally only focuses on the energy saving aspect without taking other underlying attributes into account,
[...] Read more.
This paper presents a systematic framework to evaluate the performance of conservation voltage reduction (CVR) by determining suitable substations for CVR in operations planning. Existing CVR planning practice generally only focuses on the energy saving aspect without taking other underlying attributes into account, i.e., network topology and reduced voltage effects on other substations. To secure the desired operating reserve and avoid any adverse impacts, these attributes should be considered for implementing CVR more effectively. This research develops a practical decision-making framework based on the analytic hierarchy process (AHP) to quantify several of the aforementioned attributes. Candidate substations for CVR deployment are prioritized such that performances are compared in terms of power transfer distribution factor (PTDF), voltage sensitivity factor (VSF), and CVR factor. In addition, to meet a specified reserve requirement, an integer programming approach is adopted to select potential substations for CVR implementations. Case studies for a Korean electric power system under diverse operating conditions are performed to demonstrate the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Open AccessArticle A Three-Stage Optimal Approach for Power System Economic Dispatch Considering Microgrids
Energies 2016, 9(11), 976; doi:10.3390/en9110976
Received: 20 September 2016 / Revised: 14 November 2016 / Accepted: 15 November 2016 / Published: 22 November 2016
PDF Full-text (4598 KB) | HTML Full-text | XML Full-text
Abstract
The inclusion of microgrids (MGs) in power systems, especially distribution-substation-level MGs, significantly affects power systems because of the large volumes of import and export power flows. Consequently, power dispatch has become complicated, and finding an optimal solution is difficult. In this study, a
[...] Read more.
The inclusion of microgrids (MGs) in power systems, especially distribution-substation-level MGs, significantly affects power systems because of the large volumes of import and export power flows. Consequently, power dispatch has become complicated, and finding an optimal solution is difficult. In this study, a three-stage optimal power dispatch model is proposed to solve such dispatch problems. In the proposed model, the entire power system is divided into two parts, namely, the main power grid and MGs. The optimal power dispatch problem is resolved on the basis of multi-area concepts. In stage I, the main power system economic dispatch (ED) problem is solved by sensitive factors. In stage II, the optimal power dispatches of the local MGs are addressed via an improved direct search method. In stage III, the incremental linear models for the entire power system can be established on the basis of the solutions of the previous two stages and can be subjected to linear programming to determine the optimal reschedules from the original dispatch solutions. The proposed method is coded using Matlab and tested by utilizing an IEEE 14-bus test system to verify its feasibility and accuracy. Results demonstrated that the proposed approach can be used for the ED of power systems with MGs as virtual power plants. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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Review

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Open AccessFeature PaperReview A Review of Smart Cities Based on the Internet of Things Concept
Energies 2017, 10(4), 421; doi:10.3390/en10040421
Received: 8 January 2017 / Revised: 26 February 2017 / Accepted: 20 March 2017 / Published: 23 March 2017
Cited by 1 | PDF Full-text (3319 KB) | HTML Full-text | XML Full-text
Abstract
With the expansion of smart meters, like the Advanced Metering Infrastructure (AMI), and the Internet of Things (IoT), each smart city is equipped with various kinds of electronic devices. Therefore, equipment and technologies enable us to be smarter and make various aspects of
[...] Read more.
With the expansion of smart meters, like the Advanced Metering Infrastructure (AMI), and the Internet of Things (IoT), each smart city is equipped with various kinds of electronic devices. Therefore, equipment and technologies enable us to be smarter and make various aspects of smart cities more accessible and applicable. The goal of the current paper is to provide an inclusive review on the concept of the smart city besides their different applications, benefits, and advantages. In addition, most of the possible IoT technologies are introduced, and their capabilities to merge into and apply to the different parts of smart cities are discussed. The potential application of smart cities with respect to technology development in the future provides another valuable discussion in this paper. Meanwhile, some practical experiences all across the world and the key barriers to its implementation are thoroughly expressed. Full article
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
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