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2947 KiB

Open AccessFeature PaperArticle

Engineering Support for Handling Controller Conflicts in Energy Storage Systems Applications

by Claudia Zanabria, Ali Tayyebi, Filip Pröstl Andrén, Johannes Kathan and Thomas Strasser

Energies 2017, 10(10), 1595; https://doi.org/10.3390/en10101595 - 13 Oct 2017

Cited by 8 | Viewed by 4956

Abstract

Energy storage systems will play a major role in the decarbonization of future sustainable electric power systems, allowing a high penetration of distributed renewable energy sources and contributing to the distribution network stability and reliability. To accomplish this, a storage system is required [...] Read more.

Energy storage systems will play a major role in the decarbonization of future sustainable electric power systems, allowing a high penetration of distributed renewable energy sources and contributing to the distribution network stability and reliability. To accomplish this, a storage system is required to provide multiple services such as self-consumption, grid support, peak-shaving, etc. The simultaneous activation of controllers operation may lead to conflicts, as a consequence the execution of committed services is not guaranteed. This paper presents and discusses a solution to the exposed issue by developing an engineering support approach to semi-automatically detect and handle conflicts for multi-usage storage systems applications. To accomplish that an ontology is developed and exploited by model-driven engineering mechanisms. The proposed approach is evaluated by implementing a use case example, where detection of conflicts is automatically done at an early design stage. Besides this, exploitable source code for conflicts resolution is generated and used during the design and prototype stages of controllers development. Thus, the proposed engineering support enhances the design and development of storage system controllers, especially for multi-usage applications. Full article

(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)

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16059 KiB

Open AccessArticle

PV Hosting Capacity Analysis and Enhancement Using High Resolution Stochastic Modeling

by Emilio J. Palacios-Garcia, Antonio Moreno-Muñoz, Isabel Santiago, Isabel M. Moreno-Garcia and María I. Milanés-Montero

Energies 2017, 10(10), 1488; https://doi.org/10.3390/en10101488 - 26 Sep 2017

Cited by 28 | Viewed by 5978

Abstract

Reduction of CO₂ emissions is a main target in the future smart grid. This goal is boosting the installation of renewable energy resources (RES), as well as a major consumer engagement that seeks for a more efficient utilization of these resources toward [...] Read more.

Reduction of CO₂ emissions is a main target in the future smart grid. This goal is boosting the installation of renewable energy resources (RES), as well as a major consumer engagement that seeks for a more efficient utilization of these resources toward the figure of ‘prosumers’. Nevertheless, these resources present an intermittent nature, which requires the presence of an energy storage system and an energy management system (EMS) to ensure an uninterrupted power supply. Moreover, network-related issues might arise due to the increasing power of renewable resources installed in the grid, the storage systems also being capable of contributing to the network stability. However, to assess these future scenarios and test the control strategies, a simulation system is needed. The aim of this paper is to analyze the interaction between residential consumers with high penetration of PV generation and distributed storage and the grid by means of a high temporal resolution simulation scenario based on a stochastic residential load model and PV production records. Results of the model are presented for different PV power rates and storage capacities, as well as a two-level charging strategy as a mechanism for increasing the hosting capacity (HC) of the network. Full article

(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)

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714 KiB

Open AccessArticle

Automated Energy Scheduling Algorithms for Residential Demand Response Systems

by Laihyuk Park, Yongwoon Jang, Hyoungchel Bae, Juho Lee, Chang Yun Park and Sungrae Cho

Energies 2017, 10(9), 1326; https://doi.org/10.3390/en10091326 - 2 Sep 2017

Cited by 22 | Viewed by 6480

Abstract

Demand response technology is a key technology for distributing electricity tasks in response to electricity prices in a smart grid system. In the current demand response research, there has been much demand for an automated energy scheduling scheme that uses smart devices for [...] Read more.

Demand response technology is a key technology for distributing electricity tasks in response to electricity prices in a smart grid system. In the current demand response research, there has been much demand for an automated energy scheduling scheme that uses smart devices for residential customers in the smart grid. In this paper, two automated energy scheduling schemes are proposed for residential smart grid demand response systems: semi-automated scheduling and fully-automated scheduling. If it is possible to set the appliance preference, semi-automated scheduling will be conducted, and if it is impossible, fully-automated scheduling will be operated. The formulated optimization problems consider the electricity bill along with the user convenience. For the fully-automated scheduling, the appliance preference can automatically be found according to appliance type from the electricity consumption statistics. A performance evaluation validates that the proposed scheme shifts operation to avoid peak load, that the electricity bill is significantly reduced, and that user convenience is satisfied. Full article

(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)

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2091 KiB

Open AccessArticle

Economic Dispatch with Demand Response in Smart Grid: Bargaining Model and Solutions

by Kai Ma, Congshan Wang, Jie Yang, Qiuxia Yang and Yazhou Yuan

Energies 2017, 10(8), 1193; https://doi.org/10.3390/en10081193 - 12 Aug 2017

Cited by 16 | Viewed by 4830

Abstract

This paper proposes an economic dispatch strategy for the electricity system with one generation company, multiple utility companies and multiple consumers, which participate in demand response to keep the electricity real-time balance. In the wholesale markets, multiple utility companies will commonly select a [...] Read more.

This paper proposes an economic dispatch strategy for the electricity system with one generation company, multiple utility companies and multiple consumers, which participate in demand response to keep the electricity real-time balance. In the wholesale markets, multiple utility companies will commonly select a reliable agent to negotiate with the generation company on the wholesale price. It is challengeable to find a wholesale price to run the electricity market fairly and effectively. In this study, we use the multiple utility companies’ profits to denote the utility function of the agent and formulate the interaction between the agent and the generation company as a bargaining problem, where the wholesale price was enforced in the bargaining outcome. Then, the Raiffa–Kalai–Smorodinsky bargaining solution (RBS) was utilized to achieve the fair and optimal outcome. In the retail markets, the unfavorable disturbances exist in the power management and price when the consumers participate in the demand response to keep the electricity real-time balance, which motivates us to further consider the dynamic power management algorithm with the additive disturbances, and then obtain the optimal power consumption and optimal retail price. Based on the consumers’ utility maximization, we establish a price regulation model with price feedback in the electricity retail markets, and then use the iterative algorithm to solve the optimal retail price and the consumer’s optimal power consumption. Hence, the input-to-state stability condition with additive electricity measurement disturbance and price disturbance is given. Numerical results demonstrate the effectiveness of the economic dispatch strategy. Full article

(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)

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2224 KiB

Open AccessArticle

Assessment of Credible Capacity for Intermittent Distributed Energy Resources in Active Distribution Network

by Chen Sun, Dong Liu, Yun Wang and Yi You

Energies 2017, 10(8), 1104; https://doi.org/10.3390/en10081104 - 27 Jul 2017

Cited by 2 | Viewed by 4120

Abstract

The irregularity and randomness of distributed energy sources’ (DERs) output power characteristic usually brings difficulties for grid analysis. In order to reliably and deterministically evaluate intermittent distributed generation’s active power output, a credible capacity index for active distribution network (ADN) is proposed. According [...] Read more.

The irregularity and randomness of distributed energy sources’ (DERs) output power characteristic usually brings difficulties for grid analysis. In order to reliably and deterministically evaluate intermittent distributed generation’s active power output, a credible capacity index for active distribution network (ADN) is proposed. According to the definition, it is a certain interval that the stochastic active power output of DERs may fall in with larger probability in all kinds of possible dynamic and time varying operation scenarios. Based on the description and analysis on the time varying scenarios, multiple scenarios considered dynamic power flow method for and are proposed. The method to calculate and evaluate credible capacity based on dynamic power flow (DPF) result is illustrated. A study case of an active distribution network with DERs integrated and containing 32 nodes is selected; multiple operation scenarios with various fractal dimension are established and used. Results of calculated credible capacity based on several groups of scenarios have been analyzed, giving the variance analysis of groups of credible capacity values. A deterministic value with the maximum occurrence probability representing credible capacity is given. Based on the same network case, an application of credible capacity to grid extension planning is given, which contributes to expenditure and cost reduction. The effectiveness and significance of the proposed credible capacity and solution method have been demonstrated and verified. Full article

(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)

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7156 KiB

Open AccessEditor’s ChoiceArticle

Investigation on the Development of a Sliding Mode Controller for Constant Power Loads in Microgrids

by Eklas Hossain, Ron Perez, Sanjeevikumar Padmanaban and Pierluigi Siano

Energies 2017, 10(8), 1086; https://doi.org/10.3390/en10081086 - 26 Jul 2017

Cited by 37 | Viewed by 6426

Abstract

To implement renewable energy resources, microgrid systems have been adopted and developed into the technology of choice to assure mass electrification in the next decade. Microgrid systems have a number of advantages over conventional utility grid systems, however, they face severe instability issues [...] Read more.

To implement renewable energy resources, microgrid systems have been adopted and developed into the technology of choice to assure mass electrification in the next decade. Microgrid systems have a number of advantages over conventional utility grid systems, however, they face severe instability issues due to the continually increasing constant power loads. To improve the stability of the entire system, the load side compensation technique is chosen because of its robustness and cost effectiveness. In this particular occasion, a sliding mode controller is developed for a microgrid system in the presence of constant power loads to assure a certain control objective of keeping the output voltage constant at 480 V. After that, a robustness analysis of the sliding mode controller against parametric uncertainties was performed and the sliding mode controller’s robustness against parametric uncertainties, frequency variations, and additive white Gaussian noise (AWGN) are presented. Later, the performance of the proportional integral derivative (PID) and sliding mode controller are compared in the case of nonlinearity, parameter uncertainties, and noise rejection to justify the selection of the sliding mode controller over the PID controller. All the necessary calculations are reckoned mathematically and results are verified in a virtual platform such as MATLAB/Simulink with a positive outcome. Full article

(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)

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3633 KiB

Open AccessArticle

Secure Plug-in Electric Vehicle (PEV) Charging in a Smart Grid Network

by Khaled Shuaib, Ezedin Barka, Juhar Ahmed Abdella, Farag Sallabi, Mohammed Abdel-Hafez and Ala Al-Fuqaha

Energies 2017, 10(7), 1024; https://doi.org/10.3390/en10071024 - 19 Jul 2017

Cited by 9 | Viewed by 5975

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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1463 KiB

Open AccessArticle

Electric Power Grids Distribution Generation System for Optimal Location and Sizing—A Case Study Investigation by Various Optimization Algorithms

by Ahmed Ali, Sanjeevikumar Padmanaban, Bhekisipho Twala and Tshilidzi Marwala

Energies 2017, 10(7), 960; https://doi.org/10.3390/en10070960 - 10 Jul 2017

Cited by 30 | Viewed by 4654

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

by Luciano C. Siebert, Adriana Sbicca, Alexandre Rasi Aoki and Germano Lambert-Torres

Energies 2017, 10(6), 768; https://doi.org/10.3390/en10060768 - 1 Jun 2017

Cited by 19 | Viewed by 9185

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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2678 KiB

Open AccessArticle

A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations

by Cuiyu Kong, Raka Jovanovic, Islam Safak Bayram and Michael Devetsikiotis

Energies 2017, 10(5), 675; https://doi.org/10.3390/en10050675 - 11 May 2017

Cited by 51 | Viewed by 8020

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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3834 KiB

Open AccessArticle

Research and Application of Hybrid Forecasting Model Based on an Optimal Feature Selection System—A Case Study on Electrical Load Forecasting

by Yunxuan Dong, Jianzhou Wang, Chen Wang and Zhenhai Guo

Energies 2017, 10(4), 490; https://doi.org/10.3390/en10040490 - 5 Apr 2017

Cited by 12 | Viewed by 4492

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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4381 KiB

Open AccessFeature PaperArticle

Experimental Results on a Wireless Wattmeter Device for the Integration in Home Energy Management Systems

by Eduardo M. G. Rodrigues, Radu Godina, Miadreza Shafie-khah and João P. S. Catalão

Energies 2017, 10(3), 398; https://doi.org/10.3390/en10030398 - 20 Mar 2017

Cited by 13 | Viewed by 6951

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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5790 KiB

Open AccessFeature PaperArticle

Real-Time Forecasting of EV Charging Station Scheduling for Smart Energy Systems

by Bharatiraja Chokkalingam, Sanjeevikumar Padmanaban, Pierluigi Siano, Ramesh Krishnamoorthy and Raghu Selvaraj

Energies 2017, 10(3), 377; https://doi.org/10.3390/en10030377 - 16 Mar 2017

Cited by 55 | Viewed by 11341

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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3121 KiB

Open AccessArticle

Engineering Smart Grids: Applying Model-Driven Development from Use Case Design to Deployment

by Filip Pröstl Andrén, Thomas I. Strasser and Wolfgang Kastner

Energies 2017, 10(3), 374; https://doi.org/10.3390/en10030374 - 16 Mar 2017

Cited by 38 | Viewed by 8773

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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1322 KiB

Open AccessArticle

Strategic Maintenance Scheduling of an Offshore Wind Farm in a Deregulated Power System

by Peyman Mazidi, Yaser Tohidi and Miguel A. Sanz-Bobi

Energies 2017, 10(3), 313; https://doi.org/10.3390/en10030313 - 6 Mar 2017

Cited by 19 | Viewed by 4883

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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5793 KiB

Open AccessArticle

Improvement of Wind Energy Production through HVDC Systems

by Morris Brenna, Federica Foiadelli, Michela Longo and Dario Zaninelli

Energies 2017, 10(2), 157; https://doi.org/10.3390/en10020157 - 27 Jan 2017

Cited by 21 | Viewed by 5554

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

by Yuan Hong, Shengbin Wang and Ziyue Huang

Energies 2017, 10(1), 105; https://doi.org/10.3390/en10010105 - 17 Jan 2017

Cited by 10 | Viewed by 5132

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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4311 KiB

Open AccessArticle

Correlation Feature Selection and Mutual Information Theory Based Quantitative Research on Meteorological Impact Factors of Module Temperature for Solar Photovoltaic Systems

by Yujing Sun, Fei Wang, Bo Wang, Qifang Chen, N.A. Engerer and Zengqiang Mi

Energies 2017, 10(1), 7; https://doi.org/10.3390/en10010007 - 22 Dec 2016

Cited by 56 | Viewed by 6953

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

by Kyungsung An, Hao Jan Liu, Hao Zhu, Zhao Yang Dong and Kyeon Hur

Energies 2016, 9(12), 1074; https://doi.org/10.3390/en9121074 - 16 Dec 2016

Cited by 12 | Viewed by 5937

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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4598 KiB

Open AccessArticle

A Three-Stage Optimal Approach for Power System Economic Dispatch Considering Microgrids

by Wei-Tzer Huang, Kai-Chao Yao, Chun-Ching Wu, Yung-Ruei Chang, Yih-Der Lee and Yuan-Hsiang Ho

Energies 2016, 9(11), 976; https://doi.org/10.3390/en9110976 - 22 Nov 2016

Cited by 9 | Viewed by 5561

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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3778 KiB

Open AccessReview

Grid-Tied Photovoltaic and Battery Storage Systems with Malaysian Electricity Tariff—A Review on Maximum Demand Shaving

by Gopinath Subramani, Vigna K. Ramachandaramurthy, Sanjeevikumar Padmanaban, Lucian Mihet-Popa, Frede Blaabjerg and Josep M. Guerrero

Energies 2017, 10(11), 1884; https://doi.org/10.3390/en10111884 - 16 Nov 2017

Cited by 39 | Viewed by 7899

Abstract

Under the current energy sector framework of electricity tariff in Malaysia, commercial and industrial customers are required to pay the maximum demand (MD) charge apart from the net consumption charges every month. The maximum demand charge will contribute up to 20% of the [...] Read more.

Under the current energy sector framework of electricity tariff in Malaysia, commercial and industrial customers are required to pay the maximum demand (MD) charge apart from the net consumption charges every month. The maximum demand charge will contribute up to 20% of the electricity bill, and will hence result in commercial and industrial customers focussing on alternative energy supply to minimize the billing cost. This paper aims to review the technical assessment methods of a grid-connected solar photovoltaic (PV)—battery storage system—with respect to maximum demand shaving. An effective battery storage system can provide the extra energy needed during the peak energy consumption periods, as well as when renewable energy (RE) sources go offline. Based on the reviews, maximum demand shaving with good Return-of-Investment (ROI) can be achieved by considering the actual load profile, technical, and economic aspects of the solar PV-battery system and the Malaysian electricity tariff for commercial and industrial customers. Full article

(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)

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4473 KiB

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A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches

by Rui Li, Wei Wang, Zhe Chen, Jiuchun Jiang and Weige Zhang

Energies 2017, 10(11), 1715; https://doi.org/10.3390/en10111715 - 26 Oct 2017

Cited by 71 | Viewed by 8399

Abstract

Due to the widespread deployment of distributed energy resources (DERs) and the liberalization of electricity market, traditional distribution networks are undergoing a transition to active distribution systems (ADSs), and the traditional deterministic planning methods have become unsuitable under the high penetration of DERs. [...] Read more.

Due to the widespread deployment of distributed energy resources (DERs) and the liberalization of electricity market, traditional distribution networks are undergoing a transition to active distribution systems (ADSs), and the traditional deterministic planning methods have become unsuitable under the high penetration of DERs. Aiming to develop appropriate models and methodologies for the planning of ADSs, the key features of ADS planning problem are analyzed from the different perspectives, such as the allocation of DGs and ESS, coupling of operation and planning, and high-level uncertainties. Based on these analyses, this comprehensive literature review summarizes the latest research and development associated with ADS planning. The planning models and methods proposed in these research works are analyzed and categorized from different perspectives including objectives, decision variables, constraint conditions, and solving algorithms. The key theoretical issues and challenges of ADS planning are extracted and discussed. Meanwhile, emphasis is also given to the suitable suggestions to deal with these abovementioned issues based on the available literature and comparisons between them. Finally, several important research prospects are recommended for further research in ADS planning field, such as planning with multiple micro-grids (MGs), collaborative planning between ADSs and information communication system (ICS), and planning from different perspectives of multi-stakeholders. Full article

(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)

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6564 KiB

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Constant Power Loads (CPL) with Microgrids: Problem Definition, Stability Analysis and Compensation Techniques

by Mohammed Kh. AL-Nussairi, Ramazan Bayindir, Sanjeevikumar Padmanaban, Lucian Mihet-Popa and Pierluigi Siano

Energies 2017, 10(10), 1656; https://doi.org/10.3390/en10101656 - 19 Oct 2017

Cited by 119 | Viewed by 15608

Abstract

This paper provides a comprehensive review of the major concepts associated with the μgrid, such as constant power load (CPL), incremental negative resistance or impedance (INR/I) and its dynamic behaviours on the μgrid, and power system distribution (PSD). In general, a μgrid is [...] Read more.

This paper provides a comprehensive review of the major concepts associated with the μgrid, such as constant power load (CPL), incremental negative resistance or impedance (INR/I) and its dynamic behaviours on the μgrid, and power system distribution (PSD). In general, a μgrid is defined as a cluster of different types of electrical loads and renewable energy sources (distributed generations) under a unified controller within a certain local area. It is considered a perfect solution to integrate renewable energy sources with loads as well as with a traditional grid. In addition, it can operate with a conventional grid, for example, by energy sourcing or a controllable load, or it can operate alone as an islanding mode to feed required electric energy to a grid. Hence, one of the important issues regarding the μgrid is the constant power load that results from the tightly designed control when it is applied to power electronic converters. The effect of CPL is incremental negative resistance that impacts the power quality of a power system and makes it at negative damping. Also, in this paper, a comprehensive study on major control and compensation techniques for μgrid has been included to face the instability effects of constant power loads. Finally, the merits and limitations of the compensation techniques are discussed. Full article

(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)

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3319 KiB

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A Review of Smart Cities Based on the Internet of Things Concept

by Saber Talari, Miadreza Shafie-khah, Pierluigi Siano, Vincenzo Loia, Aurelio Tommasetti and João P. S. Catalão

Energies 2017, 10(4), 421; https://doi.org/10.3390/en10040421 - 23 Mar 2017

Cited by 456 | Viewed by 36353

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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