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

Deadline for manuscript submissions: closed (15 September 2017) | Viewed by 40130

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Special Issue Editors

Dr. Hongyu Wu

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Guest Editor

Faculty of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506, USA
Interests: power systems control and operation; modeling, optimization and simulation of power systems; renewable energy integration; demand side management; electricity market analysis and energy management systems
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Dr. Amin Khodaei

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Guest Editor

2155 E Wesley, #263, University of Denver, Denver, CO 80208, USA
Interests: smart electricity grids; microgrid design and operation; renewable energy integration; power system operation and planning; and power system economics

Special Issue Information

Dear Colleagues,

Battery energy storage is becoming a crucial component to advance renewable energy and energy efficiency technologies and to improve electric power systems economy and reliability. However, battery energy storage systems feature specific technology-driven characteristics when connected to the power grid. The high capital cost of this technology is an additional factor impacting its applications. The Special Issue on “Battery Energy Storage Applications in Smart Grid” investigates the applications of this timely and important technology for improving sustainability, reliability, and efficiency of next-generation power grids. This Special Issue is a continuation of the previous and successful Special Issues pertaining to energy storage.

Assist. Prof. Dr. Hongyu Wu
Assoc. Prof. Dr. Amin Khodaei
Guest Editors

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Keywords

Battery energy storage for supporting grid services
Community/microgrid applications of the battery energy storage
Grid integration and renewable coordination
Battery storage for accounting for high PV penetration in distribution networks
Electric vehicles as battery energy storage
System analysis on effective integration of storage options
Demonstration or field deployment experiences
Performance of battery energy storage application
Operational, planning, market, and policy issues related to battery energy storage application

Published Papers (7 papers)

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Research

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4835 KiB

Open AccessArticle

Transactive-Market-Based Operation of Distributed Electrical Energy Storage with Grid Constraints

by M. Nazif Faqiry, Lawryn Edmonds, Haifeng Zhang, Amin Khodaei and Hongyu Wu

Energies 2017, 10(11), 1891; https://doi.org/10.3390/en10111891 - 17 Nov 2017

Cited by 30 | Viewed by 4721

Abstract

In a transactive energy market, distributed energy resources (DERs) such as dispatchable distributed generators (DGs), electrical energy storages (EESs), distribution-scale load aggregators (LAs), and renewable energy sources (RESs) have to earn their share of supply or demand through a bidding process. In such a market, the distribution system operator (DSO) may optimally schedule these resources, first in a forward market, i.e., day-ahead, and in a real-time market later on, while maintaining a reliable and economic distribution grid. In this paper, an efficient day-ahead scheduling of these resources, in the presence of interaction with wholesale market at the locational marginal price (LMP), is studied. Due to inclusion of EES units with integer constraints, a detailed mixed integer linear programming (MILP) formulation that incorporates simplified DistFlow equations to account for grid constraints is proposed. Convex quadratic line and transformer apparent power flow constraints have been linearized using an outer approximation. The proposed model schedules DERs based on distribution locational marginal price (DLMP), which is obtained as the Lagrange multiplier of the real power balance constraint at each distribution bus while maintaining physical grid constraints such as line limits, transformer limits, and bus voltage magnitudes. Case studies are performed on a modified IEEE 13-bus system with high DER penetration. Simulation results show the validity and efficiency of the proposed model. Full article

(This article belongs to the Special Issue Battery Energy Storage Applications in Smart Grid)

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2724 KiB

Open AccessArticle

A Mobile Battery Swapping Service for Electric Vehicles Based on a Battery Swapping Van

by Sujie Shao, Shaoyong Guo and Xuesong Qiu

Energies 2017, 10(10), 1667; https://doi.org/10.3390/en10101667 - 20 Oct 2017

Cited by 49 | Viewed by 10335

Abstract

This paper presents a novel approach for providing a mobile battery swapping service for electric vehicles (EVs) that is provided by a mobile battery swapping van. This battery swapping van can carry many fully charged batteries and drive up to an EV to swap a battery within a few minutes. First, a reasonable EV battery swapping architecture based on a battery swapping van is established in this paper. The function and role of each participant and the relationships between each participant are determined, especially their changes compared with the battery charging service. Second, the battery swapping service is described, including the service request priority and service request queuing model. To provide the battery swapping service efficiently and effectively, the battery swapping service request scheduling is analyzed well, and a minimum waiting time based on priority and satisfaction scheduling strategy (MWT-PS) is proposed. Finally, the battery swapping service is simulated, and the performance of MWT-PS is evaluated in simulation scenarios. The simulation results show that this novel approach can be used as a reference for a future system that provides reasonable and satisfying battery swapping service for EVs. Full article

(This article belongs to the Special Issue Battery Energy Storage Applications in Smart Grid)

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5244 KiB

Open AccessArticle

Application of a Simplified Thermal-Electric Model of a Sodium-Nickel Chloride Battery Energy Storage System to a Real Case Residential Prosumer

by Fabio Bignucolo, Massimiliano Coppo, Giorgio Crugnola and Andrea Savio

Energies 2017, 10(10), 1497; https://doi.org/10.3390/en10101497 - 26 Sep 2017

Cited by 14 | Viewed by 4071

Abstract

Recently, power system customers have changed the way they interact with public networks, playing a more and more active role. End-users first installed local small-size generating units, and now they are being equipped with storage devices to increase the selfconsumption rate. By suitably managing local resources, the provision of ancillary services and aggregations among several end-users are expected evolutions in the near future. In the upcoming market of household-sized storage devices, sodium-nickel chloride technology seems to be an interesting alternative to lead-acid and lithium-ion batteries. To accurately investigate the operation of the NaNiCl₂ battery system at the residential level, a suitable thermoelectric model has been developed by the authors, starting from the results of laboratory tests. The behavior of the battery internal temperature has been characterized. Then, the designed model has been used to evaluate the economic profitability in installing a storage system in the case that end-users are already equipped with a photovoltaic unit. To obtain realistic results, real field measurements of customer consumption and solar radiation have been considered. A concrete interest in adopting the sodiumnickel chloride technology at the residential level is confirmed, taking into account the achievable benefits in terms of economic income, back-up supply, and increased indifference to the evolution of the electricity market. Full article

(This article belongs to the Special Issue Battery Energy Storage Applications in Smart Grid)

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890 KiB

Open AccessArticle

Demand Side Management in Nearly Zero Energy Buildings Using Heuristic Optimizations

by Nadeem Javaid, Sardar Mehboob Hussain, Ibrar Ullah, Muhammad Asim Noor, Wadood Abdul, Ahmad Almogren and Atif Alamri

Energies 2017, 10(8), 1131; https://doi.org/10.3390/en10081131 - 02 Aug 2017

Cited by 49 | Viewed by 5701

Abstract

Today’s buildings are responsible for about 40% of total energy consumption and 30–40% of carbon emissions, which are key concerns for the sustainable development of any society. The excessive usage of grid energy raises sustainability issues in the face of global changes, such as climate change, population, economic growths, etc. Traditionally, the power systems that deliver this commodity are fuel operated and lead towards high carbon emissions and global warming. To overcome these issues, the recent concept of the nearly zero energy building (nZEB) has attracted numerous researchers and industry for the construction and management of the new generation buildings. In this regard, this paper proposes various demand side management (DSM) programs using the genetic algorithm (GA), teaching learning-based optimization (TLBO), the enhanced differential evolution (EDE) algorithm and the proposed enhanced differential teaching learning algorithm (EDTLA) to manage energy and comfort, while taking the human preferences into consideration. Power consumption patterns of shiftable home appliances are modified in response to the real-time price signal in order to get monetary benefits. To further improve the cost and user discomfort objectives along with reduced carbon emission, renewable energy sources (RESs) are also integrated into the microgrid (MG). The proposed model is implemented in a smart residential complex of multiple homes under a real-time pricing environment. We figure out two feasible regions: one for electricity cost and the other for user discomfort. The proposed model aims to deal with the stochastic nature of RESs while introducing the battery storage system (BSS). The main objectives of this paper include: (1) integration of RESs; (2) minimization of the electricity bill (cost) and discomfort; and (3) minimizing the peak to average ratio (PAR) and carbon emission. Additionally, we also analyze the tradeoff between two conflicting objectives, like electricity cost and user discomfort. Simulation results validate both the implemented and proposed techniques. Full article

(This article belongs to the Special Issue Battery Energy Storage Applications in Smart Grid)

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3129 KiB

Open AccessArticle

Multi-Objective Scheduling Optimization Based on a Modified Non-Dominated Sorting Genetic Algorithm-II in Voltage Source Converter−Multi-Terminal High Voltage DC Grid-Connected Offshore Wind Farms with Battery Energy Storage Systems

by Ho-Young Kim, Mun-Kyeom Kim and San Kim

Energies 2017, 10(7), 986; https://doi.org/10.3390/en10070986 - 12 Jul 2017

Cited by 12 | Viewed by 4212

Abstract

Improving the performance of power systems has become a challenging task for system operators in an open access environment. This paper presents an optimization approach for solving the multi-objective scheduling problem using a modified non-dominated sorting genetic algorithm in a hybrid network of meshed alternating current (AC)/wind farm grids. This approach considers voltage and power control modes based on multi-terminal voltage source converter high-voltage direct current (MTDC) and battery energy storage systems (BESS). To enhance the hybrid network station performance, we implement an optimal process based on the battery energy storage system operational strategy for multi-objective scheduling over a 24 h demand profile. Furthermore, the proposed approach is formulated as a master problem and a set of sub-problems associated with the hybrid network station to improve the overall computational efficiency using Benders’ decomposition. Based on the results of the simulations conducted on modified institute of electrical and electronics engineers (IEEE-14) bus and IEEE-118 bus test systems, we demonstrate and confirm the applicability, effectiveness and validity of the proposed approach. Full article

(This article belongs to the Special Issue Battery Energy Storage Applications in Smart Grid)

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2015 KiB

Open AccessArticle

Impact Analysis of Demand Response Intensity and Energy Storage Size on Operation of Networked Microgrids

by Akhtar Hussain, Van-Hai Bui and Hak-Man Kim

Energies 2017, 10(7), 882; https://doi.org/10.3390/en10070882 - 30 Jun 2017

Cited by 19 | Viewed by 4431

Abstract

Integration of demand response (DR) programs and battery energy storage system (BESS) in microgrids are beneficial for both microgrid owners and consumers. The intensity of DR programs and BESS size can alter the operation of microgrids. Meanwhile, the optimal size for BESS units is linked with the uncertainties associated with renewable energy sources and load variations. Similarly, the participation of enrolled customers in DR programs is also uncertain and, among various other factors, uncertainty in market prices is a major cause. Therefore, in this paper, the impact of DR program intensity and BESS size on the operation of networked microgrids is analyzed while considering the prevailing uncertainties. The uncertainties associated with forecast load values, output of renewable generators, and market price are realized via the robust optimization method. Robust optimization has the capability to provide immunity against the worst-case scenario, provided the uncertainties lie within the specified bounds. The worst-case scenario of the prevailing uncertainties is considered for evaluating the feasibility of the proposed method. The two representative categories of DR programs, i.e., price-based and incentive-based DR programs are considered. The impact of change in DR intensity and BESS size on operation cost of the microgrid network, external power trading, internal power transfer, load profile of the network, and state-of-charge (SOC) of battery energy storage system (BESS) units is analyzed. Simulation results are analyzed to determine the integration of favorable DR program and/or BESS units for different microgrid networks with diverse objectives. Full article

(This article belongs to the Special Issue Battery Energy Storage Applications in Smart Grid)

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Review

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1981 KiB

Open AccessReview

State-Of-The-Art in Microgrid-Integrated Distributed Energy Storage Sizing

by Ibrahim Alsaidan, Abdulaziz Alanazi, Wenzhong Gao, Hongyu Wu and Amin Khodaei

Energies 2017, 10(9), 1421; https://doi.org/10.3390/en10091421 - 16 Sep 2017

Cited by 41 | Viewed by 5728

Abstract

Distributed energy storage (DES) plays an important role in microgrid operation and control, as it can potentially improve local reliability and resilience, reduce operation cost, and mitigate challenges caused by high penetration renewable generation. However, to ensure an acceptable economic and technical performance, DES must be optimally sized and placed. This paper reviews the existing DES sizing methods for microgrid applications and presents a generic sizing method that enables microgrid planners to efficiently determine the optimal DES size, technology, and location. The proposed method takes into consideration the impact of DES operation on its lifetime to enhance the obtained results accuracy and practicality. The presented model can be used for both grid-tied (considering both grid-connected and islanded modes) and isolated microgrids. Full article

(This article belongs to the Special Issue Battery Energy Storage Applications in Smart Grid)

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