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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: closed (30 June 2017) | Viewed by 62801

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Dr. Shuhui Li

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Department of Center for Advanced Vehicle Technologies, College of Electrical and Computer Engineering, University of Alabama, Tuscaloosa, AL 35487, USA
Interests: smart grid and smart microgrid; renewable energy; systems power; electronics; electric machines and drives; power systems; artificial intelligence and neural networks modeling; analysis and simulation of dynamic systems; massively parallel processing applications software; engineering measurements and instrumentations
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Special Issue Information

Dear Colleagues,

The electric power grid of today is experiencing a significant change because of the rapid development of renewable energy technologies. Smart electricity grid is the key to enhance the penetration of renewable energy into electric power systems. However, due to the intermittent and distributed nature of renewable energy sources, multidisciplinary characteristics of renewable energy systems, and extensive applications of advanced technologies in a smart grid, design and management of a smart and renewable energy system is a great challenge to both power and computing industry. Furthermore, it is anticipated that future energy systems will increasingly be “two-way streets”, allowing every energy user to be not only a customer, but an energy provider as well. This, in essence, will represent a shift toward an “Internet for energy”, transforming the energy industry in a way similar to the Internet transforming the computer industry from the mainframe computer paradigm to today’s distributed and parallel computing environment. This transition inevitably demands significant research for many rapidly rising issues while the operation, stability, and reliability of the existing power grid not be affected.

This Special Issue focuses on recent advances in smart electric power grid that can accommodate more renewable energy into electric utility systems. From sustainable source (including wind, solar, wave, etc.) perspective, the Special Issue is interested in sustainable energy generation characteristics, prediction of sustainable energy production, control of sustainable energy in supporting grid frequency and voltage, impact of sustainable energy generation to net load variability, issues in determining capacity credit relevant to sustainable energy generation, etc. From the grid perspective, the Special Issue is interested but not limited to the following issues relevant to increased renewable energy penetration: 1) To what extent are dispatchable generation reserves required and under what circumstances? 2) Will system reliability be compromised with increased sustainable energy penetration? 3) What are the system operating cost impacts of renewable’s variability? 4) How do impacts vary with renewable penetration? 5) How will sustainable energy generation affect system operating strategies? 6) How does the level of renewable penetration affect the placement of PMUs (phasor measurement units) for effective monitoring and evaluation of electric power system operation? Energy storage, Demand response, micorgrids, etc.

Dr. Shuhui Li
Guest Editor

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 submissions that pass pre-check are 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.

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Keywords

Solar photovoltaics
wind power
wave energy
power generation control
prediction and forecast
energy storage
power system control
automatic generation control
grid reliability and stability
power system planning and operation
economic dispatch
grid operators
voltage regulation
demand response
microgrid
grid monitoring and measurement

Published Papers (11 papers)

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Research

1026 KiB

Open AccessArticle

Auction Mechanism of Micro-Grid Project Transfer

by Yong Long, Yu Wang and Chengrong Pan

Sustainability 2017, 9(10), 1895; https://doi.org/10.3390/su9101895 - 20 Oct 2017

Cited by 4 | Viewed by 3796

Abstract

Micro-grid project transfer is the primary issue of micro-grid development. The efficiency and quality of the micro-grid project transfer directly affect the quality of micro-grid project construction and development, which is very important for the sustainable development of micro-grid. This paper constructs a multi-attribute auction model of micro-grid project transfer, which reflects the characteristics of micro-grid system and the interests of stakeholders, calculates the optimal bidding strategy and analyzes the influence of relevant factors on auction equilibrium by multi-stage dynamic game with complete information, and makes a numerical simulation analysis. Results indicate that the optimal strategy of auction mechanism is positively related to power quality, energy storage quality, and carbon emissions. Different from the previous lowest price winning mechanism, the auction mechanism formed in this paper emphasizes that the energy suppliers which provide the comprehensive optimization of power quality, energy storage quality, carbon emissions, and price will win the auction, when both the project owners and energy suppliers maximize their benefits under this auction mechanism. The auction mechanism is effective because it is in line with the principle of individual rationality and incentive compatibility. In addition, the number of energy suppliers participating in the auction and the cost of the previous auction are positively related to the auction equilibrium, both of which are adjusting the equilibrium results of the auction. At the same time, the utilization rate of renewable energy and the comprehensive utilization of energy also have a positive impact on the auction equilibrium. In the end, this paper puts forward a series of policy suggestions about micro-grid project auction. The research in this paper is of great significance to improve the auction quality of micro-grid projects and promote the sustainable development of micro-grid. Full article

(This article belongs to the Special Issue Smart Grid)

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2590 KiB

Open AccessArticle

Operating Strategy for Local-Area Energy Systems Integration Considering Uncertainty of Supply-Side and Demand-Side under Conditional Value-At-Risk Assessment

by Jiaqi Shi, Yingrui Wang, Ruibin Fu and Jianhua Zhang

Sustainability 2017, 9(9), 1655; https://doi.org/10.3390/su9091655 - 18 Sep 2017

Cited by 7 | Viewed by 4367

Abstract

To alleviate environmental pollution and improve the energy usage efficiency of terminals, energy systems integration (ESI) has become an important paradigm in the energy structure evolution. Power, gas and heat systems are becoming tightly interlinked with each other in ESI. The dispatching strategy of local-area ESI has significant impact on its operation. In this paper, a local-area ESI operational scheduling model based on conditional value-at-risk (CVaR) is proposed to minimize expected operational cost, which considers the uncertainty of energy supply-side and demand-side as well as multi-energy network constraints, including electrical network, thermal network and gas network. The risk cost is analyzed comprehensively under the condition of under- or overestimated cost. On this basis, a hybrid method combining particle swarm optimization with interior point algorithm is executed to compute the optimal solutions of two-stage multi-period mixed-integer convex model. Finally, a case study is performed on ESI to demonstrate the effectiveness of the proposed method. Full article

(This article belongs to the Special Issue Smart Grid)

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1467 KiB

Open AccessArticle

An Integrative DR Study for Optimal Home Energy Management Based on Approximate Dynamic Programming

by Hepeng Li, Peng Zeng, Chuanzhi Zang, Haibin Yu and Shuhui Li

Sustainability 2017, 9(7), 1248; https://doi.org/10.3390/su9071248 - 17 Jul 2017

Cited by 10 | Viewed by 4414

Abstract

This paper presents an integrative demand response (DR) mechanism for energy management of appliances, an energy storage system and an electric vehicle (EV) within a home. The paper considers vehicle-to-home (V2H) and vehicle-to-grid (V2G) functions for energy management of EVs and the degradation cost of the EV battery caused by the V2H/V2G operation in developing the proposed DR mechanism. An efficient optimization algorithm is developed based on approximate dynamic programming, which overcomes the challenges of solving high dimensional optimization problems for the integrative home energy system. To investigate how the participation of different home appliances affects the DR efficiency, several DR scenarios are designed. Then, a detailed simulation study is conducted to investigate and compare home energy management efficiency under different scenarios. Full article

(This article belongs to the Special Issue Smart Grid)

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1660 KiB

Open AccessArticle

Distributed Optimisation Algorithm for Demand Side Management in a Grid-Connected Smart Microgrid

by Omowunmi Mary Longe, Khmaies Ouahada, Suvendi Rimer, Hendrik C. Ferreira and A. J. Han Vinck

Sustainability 2017, 9(7), 1088; https://doi.org/10.3390/su9071088 - 22 Jun 2017

Cited by 23 | Viewed by 4163

Abstract

The contributions of Distributed Energy Generation (DEG) and Distributed Energy Storage (DES) for Demand Side Management (DSM) purposes in a smart macrogrid or microgrid cannot be over-emphasised. However, standalone DEG and DES can lead to under-utilisation of energy generation by consumers and financial investments; in grid-connection mode, though, DEG and DES can offer arbitrage opportunities for consumers and utility provider(s). A grid-connected smart microgrid comprising heterogeneous (active and passive) smart consumers, electric vehicles and a large-scale centralised energy storage is considered in this paper. Efficient energy management by each smart entity is carried out by the proposed Microgrid Energy Management Distributed Optimisation Algorithm (MEM-DOA) installed distributively within the network according to consumer type. Each smart consumer optimises its energy consumption and trading for comfort (demand satisfaction) and profit. The proposed model was observed to yield better consumer satisfaction, higher financial savings, and reduced Peak-to-Average-Ratio (PAR) demand on the utility grid. Other associated benefits of the model include reduced investment on peaker plants, grid reliability and environmental benefits. The MEM-DOA also offered participating smart consumers energy and tariff incentives so that passive smart consumers do not benefit more than active smart consumers, as was the case with some previous energy management algorithms. Full article

(This article belongs to the Special Issue Smart Grid)

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3837 KiB

Open AccessArticle

Coordinated Optimal Operation Method of the Regional Energy Internet

by Rishang Long, Jian Liu, Chunliang Lu, Jiaqi Shi and Jianhua Zhang

Sustainability 2017, 9(5), 848; https://doi.org/10.3390/su9050848 - 19 May 2017

Cited by 9 | Viewed by 4931

Abstract

The development of the energy internet has become one of the key ways to solve the energy crisis. This paper studies the system architecture, energy flow characteristics and coordinated optimization method of the regional energy internet. Considering the heat-to-electric ratio of a combined cooling, heating and power unit, energy storage life and real-time electricity price, a double-layer optimal scheduling model is proposed, which includes economic and environmental benefit in the upper layer and energy efficiency in the lower layer. A particle swarm optimizer–individual variation ant colony optimization algorithm is used to solve the computational efficiency and accuracy. Through the calculation and simulation of the simulated system, the energy savings, level of environmental protection and economic optimal dispatching scheme are realized. Full article

(This article belongs to the Special Issue Smart Grid)

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5545 KiB

Open AccessArticle

Virtual Inertia Control-Based Model Predictive Control for Microgrid Frequency Stabilization Considering High Renewable Energy Integration

by Thongchart Kerdphol, Fathin S. Rahman, Yasunori Mitani, Komsan Hongesombut and Sinan Küfeoğlu

Sustainability 2017, 9(5), 773; https://doi.org/10.3390/su9050773 - 08 May 2017

Cited by 117 | Viewed by 11950

Abstract

Renewable energy sources (RESs), such as wind and solar generations, equip inverters to connect to the microgrids. These inverters do not have any rotating mass, thus lowering the overall system inertia. This low system inertia issue could affect the microgrid stability and resiliency in the situation of uncertainties. Today’s microgrids will become unstable if the capacity of RESs become larger and larger, leading to the weakening of microgrid stability and resilience. This paper addresses a new concept of a microgrid control incorporating a virtual inertia system based on the model predictive control (MPC) to emulate virtual inertia into the microgrid control loop, thus stabilizing microgrid frequency during high penetration of RESs. The additional controller of virtual inertia is applied to the microgrid, employing MPC with virtual inertia response. System modeling and simulations are carried out using MATLAB/Simulink^® software. The simulation results confirm the superior robustness and frequency stabilization effect of the proposed MPC-based virtual inertia control in comparison to the fuzzy logic system and conventional virtual inertia control in a system with high integration of RESs. The proposed MPC-based virtual inertia control is able to improve the robustness and frequency stabilization of the microgrid effectively. Full article

(This article belongs to the Special Issue Smart Grid)

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11556 KiB

Open AccessArticle

An Optimal Dispatch Model of Wind-Integrated Power System Considering Demand Response and Reliability

by Qingshan Xu, Yifan Ding and Aixia Zheng

Sustainability 2017, 9(5), 758; https://doi.org/10.3390/su9050758 - 05 May 2017

Cited by 20 | Viewed by 4072

Abstract

Demand response (DR) has become an impressive option in the deregulated power system due to its features of availability, quickness and applicability. In this paper, a novel economic dispatch model integrated with wind power is proposed, where incentive-based DR and reliability measures are taken into account. Compared with the conventional models, the proposed model considers customers’ power consumption response to the incentive price. The load profile is optimized with DR to depress the influence on the dispatch caused by the anti-peak-shaving and intermittence of wind generation. Furthermore, a probabilistic formulation is established to calculate the expected energy not supplied (EENS). This approach combines the probability distribution of the forecast errors of load and wind power, as well as the outage replacement rates of units into consideration. The cost of EENS is added into the objective to achieve an optimal equilibrium point between economy and reliability of power system operation. The proposed model is solved by mixed integer linear programming (MILP). The applicability and effectiveness of this model is illustrated by numerical simulations tested on the IEEE 24-bus Reliability Test System. Full article

(This article belongs to the Special Issue Smart Grid)

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4915 KiB

Open AccessArticle

New Configuration and Novel Reclosing Procedure of Distribution System for Utilization of BESS as UPS in Smart Grid

by Hun-Chul Seo

Sustainability 2017, 9(4), 507; https://doi.org/10.3390/su9040507 - 27 Mar 2017

Cited by 8 | Viewed by 3966

Abstract

This paper proposes a new configuration and novel reclosing procedure of a distribution system with a battery energy storage system (BESS) used as an uninterruptible power supply (UPS) in a smart grid. The proposed new configurations of the distribution systems are the installation of a circuit breaker (CB) on both sides of the distribution line, the replacement of the recloser with a CB and protective relay, and the requirement of a communication method. The proposed reclosing procedure performs the reclosing of the CB at the load side and then judges the fault clearance using the load current. If the fault is cleared, the synchronism checking between the main source and the BESS is performed. After completing this, the CB at the main source side is reclosed. The smart grid environment, including a new distribution system, BESS, and reclosing method are modeled with the Electromagnetic Transients Program (EMTP)/ATPDraw. To verify the proposed method, the various simulations according to the fault clearance time are performed and analyzed. The simulation results show that the BESS can be operated as a UPS and successful reclosing is possible. Full article

(This article belongs to the Special Issue Smart Grid)

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3558 KiB

Open AccessArticle

Multi-Objective Scheduling of Electric Vehicles in Smart Distribution Network

by Changhong Deng, Ning Liang, Jin Tan and Gongchen Wang

Sustainability 2016, 8(12), 1234; https://doi.org/10.3390/su8121234 - 28 Nov 2016

Cited by 16 | Viewed by 5545

Abstract

Due to the energy savings and environmental protection they provide, plug-in electric vehicles (PEVs) are increasing in number quickly. Rapid development of PEVs brings new opportunities and challenges to the electricity distribution network’s dispatching. A high number of uncoordinated charging PEVs has significant negative impacts on the secure and economic operation of a distribution network. In this paper, a bi-level programming approach that coordinates PEVs’ charging with the network load and electricity price of the open market is presented. The major objective of the upper level model is to minimize the total network costs and the deviation of electric vehicle aggregators’ charging power and the equivalent power. The subsequent objective of the lower level model after the upper level decision is to minimize the dispatching deviation of the sum of PEVs’ charging power and their optimization charging power under the upper level model. An improved particle swarm optimization algorithm is used to solve the bi-level programming. Numerical studies using a modified IEEE 69-bus distribution test system including six electric vehicle aggregators verify the efficiency of the proposed model. Full article

(This article belongs to the Special Issue Smart Grid)

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2485 KiB

Open AccessArticle

Design and Implementation of a Microgrid Energy Management System

by Eun-Kyu Lee, Wenbo Shi, Rajit Gadh and Wooseong Kim

Sustainability 2016, 8(11), 1143; https://doi.org/10.3390/su8111143 - 07 Nov 2016

Cited by 50 | Viewed by 8445

Abstract

A microgrid is characterized by the integration of distributed energy resources and controllable loads in a power distribution network. Such integration introduces new, unique challenges to microgrid management that have never been exposed to traditional power systems. To accommodate these challenges, it is necessary to redesign a conventional Energy Management System (EMS) so that it can cope with intrinsic characteristics of microgrids. While many projects have shown excellent research outcomes, they have either tackled portions of the characteristics or validated their EMSs only via simulations. This paper proposes a Microgrid Platform (MP), an advanced EMS for efficient microgrid operations. We design the MP by taking into consideration (i) all the functional requirements of a microgrid EMS (i.e., optimization, forecast, human–machine interface, and data analysis) and (ii) engineering challenges (i.e., interoperability, extensibility, and flexibility). Moreover, a prototype system is developed and deployed in two smart grid testbeds: UCLA Smart Grid Energy Research Center and Korea Institute of Energy Research. We then conduct experiments to verify the feasibility of the MP design in real-world settings. Our testbeds and experiments demonstrate that the MP is able to communicate with various energy devices and to perform an energy management task efficiently. Full article

(This article belongs to the Special Issue Smart Grid)

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2813 KiB

Open AccessArticle

Fostering Residential Demand Response through Dynamic Pricing Schemes: A Behavioural Review of Smart Grid Pilots in Europe

by Kris Kessels, Carolien Kraan, Ludwig Karg, Simone Maggiore, Pieter Valkering and Erik Laes

Sustainability 2016, 8(9), 929; https://doi.org/10.3390/su8090929 - 11 Sep 2016

Cited by 43 | Viewed by 6139

Abstract

Many smart grid projects make use of dynamic pricing schemes aimed to motivate consumers to shift and/or decrease energy use. Based upon existing literature and analyses of current smart grid projects, this survey paper presents key lessons on how to encourage households to adjust energy end use by means of dynamic tariffs. The paper identifies four key hypotheses related to fostering demand response through dynamic tariff schemes and examines whether these hypotheses can be accepted or rejected based on a review of published findings from a range of European pilot projects. We conclude that dynamic pricing schemes have the power to adjust energy consumption behavior within households. In order to work effectively, the dynamic tariff should be simple to understand for the end users, with timely notifications of price changes, a considerable effect on their energy bill and, if the tariff is more complex, the burden for the consumer could be eased by introducing automated control. Although sometimes the mere introduction of a dynamic tariff has proven to be effective, often the success of the pricing scheme depends also on other factors influencing the behavior of end users. An important condition to make dynamic tariffs work is that the end users should be engaged with them. Full article

(This article belongs to the Special Issue Smart Grid)

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