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Special Issue "Sustainable Electric Power Systems Research"

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

Deadline for manuscript submissions: closed (30 September 2017)

Special Issue Editor

Guest Editor
Prof. Dr. Tomonobu Senjyu

Department of Electrical and Electronic Engineering, University of the Ryukyus, Nishihara, Okinawa 903-0213, Japan
Website | E-Mail
Phone: +81-98-895-8686
Fax: +81 895 8686
Interests: Renewable energy; Power systems; Power electronics; System control; Optimization; Smart grid; Smart house; Motor drives; Artificial intelligence; Electric vehicles

Special Issue Information

Dear Colleagues,

Renewable energy systems, such as photovoltaic and wind power system, are being introduced into power systems. The systems do not emit CO2 for generation and system costs have been going down rapidly in recent years. Generated power depends on weather conditions, such as solar insolation and wind speed. The fluctuated generated power influences power systems; the voltage and frequency of power system can be changed suddenly; therefore, the power quality in power systems is strongly deteriorated. The control strategies and operation methods for power systems should be optimized in power systems with a high penetration of renewable systems. Moreover, high-power switching devices are now being developed, which can provide high-power electronic equipment for power systems. The power quality will increase with the use of power converters and inverters. This is another hot research topic in power engineer communities. This Special Issue of Sustainability will present the novel challenges for power system analysis, control, and optimization, including renewable energy and distributed generators in power systems.

Prof. Dr. Tomonobu Senjyu
Guest Editor

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Keywords

  • Renewable energy
  • Photovoltaic systems
  • Wind energy conversion systems
  • Power system analysis, control, and optimization
  • Distribution systems
  • Voltage and frequency control in power systems
  • Reliability for power supply
  • Demand side management and demand response
  • High voltage direct current (HVDC) systems
  • Remote-area power systems
  • Distributed generators

Published Papers (28 papers)

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Open AccessArticle Optimal Capacitor Placement in Wind Farms by Considering Harmonics Using Discrete Lightning Search Algorithm
Sustainability 2017, 9(9), 1669; doi:10.3390/su9091669
Received: 7 August 2017 / Revised: 7 September 2017 / Accepted: 18 September 2017 / Published: 20 September 2017
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Abstract
Currently, many wind farms exist throughout the world and, in some cases, supply a significant portion of energy to networks. However, numerous uncertainties remain with respect to the amount of energy generated by wind turbines and other sophisticated operational aspects, such as voltage
[...] Read more.
Currently, many wind farms exist throughout the world and, in some cases, supply a significant portion of energy to networks. However, numerous uncertainties remain with respect to the amount of energy generated by wind turbines and other sophisticated operational aspects, such as voltage and reactive power management, which requires further development and consideration. To fix the problem of poor reactive power compensation in wind farms, optimal capacitor placement has been proposed in existing wind farms as a simple and relatively inexpensive method. However, the use of induction generators, transformers, and additional capacitors represent potential problems for the harmonics of a system and therefore must be taken into account at wind farms. The optimal location and size of capacitors at buses of an 80-MW wind farm were determined according to modelled wind speed, system equivalent circuits, and harmonics in order to minimize energy losses, optimize reactive power and reduce the management costs. The discrete version of the lightning search algorithm (DLSA) is a powerful and flexible nature-inspired optimization technique that was developed and implemented herein for optimal capacitor placement in wind farms. The obtained results are compared with the results of the genetic algorithm (GA) and the discrete harmony search algorithm (DHSA). Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle A Combined Voltage Control Strategy for Fuel Cell
Sustainability 2017, 9(9), 1517; doi:10.3390/su9091517
Received: 18 July 2017 / Revised: 17 August 2017 / Accepted: 22 August 2017 / Published: 28 August 2017
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Abstract
Control of output voltage is critical for the power quality of solid oxide fuel cells (SOFCs), which is, however, challenging due to electrochemical nonlinearity, load disturbances, modelling uncertainties, and actuator constraints. Moreover, the fuel utilization rate should be limited within a safety range
[...] Read more.
Control of output voltage is critical for the power quality of solid oxide fuel cells (SOFCs), which is, however, challenging due to electrochemical nonlinearity, load disturbances, modelling uncertainties, and actuator constraints. Moreover, the fuel utilization rate should be limited within a safety range during the voltage regulation transient. The current research is usually appealing to model predictive control (MPC) by formulating the difficulties into a constrained optimization problem, but its huge computational complexity makes it formidable for real-time implementation in practice. To this end, this paper aims to develop a combined control structure, with basic function blocks, to fulfill the objectives with minor computation. Firstly, the disturbance, nonlinearity and uncertainties are lumped as a total disturbance, which is estimated and mitigated by active disturbance rejection controller (ADRC). Secondly, a feed-forward controller is introduced to improve the load disturbance rejection response. Finally, the constraints are satisfied by designing a cautious switching strategy. The simulation results show that the nominal performance of the proposed strategy is comparable to MPC. In the presence of parameter perturbation, the proposed strategy shows a better performance than MPC. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Multi-Criteria Analysis of Electric Vans for City Logistics
Sustainability 2017, 9(8), 1453; doi:10.3390/su9081453
Received: 5 June 2017 / Revised: 8 August 2017 / Accepted: 14 August 2017 / Published: 17 August 2017
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Abstract
Atmospheric emissions of anthropogenic origin are one of the most important problems in cities. A particularly discrete ecological footprint in urban environment is made by urban freight transport. This problem has become the key challenge for all stakeholder groups involved in freight transport
[...] Read more.
Atmospheric emissions of anthropogenic origin are one of the most important problems in cities. A particularly discrete ecological footprint in urban environment is made by urban freight transport. This problem has become the key challenge for all stakeholder groups involved in freight transport in urban areas. Over the recent years, there has been a growing interest in using alternative fuel vehicles in urban logistics, including those equipped with electric drive systems. This paper presents a multi-criteria analysis (MCA) of selected electric vehicles (EVs) in the context of their application for the purposes of deliveries in cities. In methodological terms, we present a unique MCA-based approach for evaluation of Electric Freight Vehicles (EFVs). A successful attempt is made to build a multistep MCA procedure based on two carefully selected MCDA methods (PROMETHEE II and fuzzy TOPSIS) to handle both certain and uncertain data sets in a single decision process. In practical terms, we successfully demonstrate the usefulness of the proposed approach by creating a set of decision maker’s preference models (based on certain and uncertain data) of carefully selected EFVs and provide sensitivity and robustness analyses of the obtained solutions. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Determinants of Consumers’ Purchasing Intentions for the Hydrogen-Electric Motorcycle
Sustainability 2017, 9(8), 1447; doi:10.3390/su9081447
Received: 15 July 2017 / Revised: 3 August 2017 / Accepted: 14 August 2017 / Published: 16 August 2017
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Abstract
In recent years, increasing concerns regarding the energy costs and environmental effects of urban motorcycle use have spurred the development of hydrogen-electric motorcycles in Taiwan. Although gasoline-powered motorcycles produce substantial amounts of exhaust and noise pollution, hydrogen-electric motorcycles are highly energy-efficient, relatively quiet,
[...] Read more.
In recent years, increasing concerns regarding the energy costs and environmental effects of urban motorcycle use have spurred the development of hydrogen-electric motorcycles in Taiwan. Although gasoline-powered motorcycles produce substantial amounts of exhaust and noise pollution, hydrogen-electric motorcycles are highly energy-efficient, relatively quiet, and produce zero emissions, features that suggest their great potential to reduce the problems currently associated with the use of motorcycles in city environments. This study identified the significant external variables that affect consumers’ purchase intentions toward using hydrogen-electric motorcycles. A questionnaire method was employed with a total of 300 questionnaires distributed and 233 usable questionnaires returned, yielding a 78% overall response rate. Structural equation modeling (SEM) was applied to test the research hypothesis. The research concluded that (1) product knowledge positively influenced purchase intentions but negatively affected the perceived risk; (2) perceived quality via hydrogen-electric motorcycles positively influenced the perceived value but negatively affected the perceived risk; (3) perceived risk negatively affected the perceived value; and (4) the perceived value positively affected purchase intentions. This study can be used as a reference for motorcycle manufacturers when planning their marketing strategies. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Sustainability from the Occurrence of Critical Dynamic Power System Blackout Determined by Using the Stochastic Event Tree Technique
Sustainability 2017, 9(6), 941; doi:10.3390/su9060941
Received: 26 March 2017 / Revised: 28 May 2017 / Accepted: 31 May 2017 / Published: 3 June 2017
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Abstract
With the advent of advanced technology in smart grid, the implementation of renewable energy in a stressed and complicated power system operation, aggravated by a competitive electricity market and critical system contingencies, this will inflict higher probabilities of the occurrence of a severe
[...] Read more.
With the advent of advanced technology in smart grid, the implementation of renewable energy in a stressed and complicated power system operation, aggravated by a competitive electricity market and critical system contingencies, this will inflict higher probabilities of the occurrence of a severe dynamic power system blackout. This paper presents the proposed stochastic event tree technique used to assess the sustainability against the occurrence of dynamic power system blackout emanating from implication of critical system contingencies such as the rapid increase in total loading condition and sensitive initial transmission line tripping. An extensive analysis of dynamic power system blackout has been carried out in a case study of the following power systems: IEEE RTS-79 and IEEE RTS-96. The findings have shown that the total loading conditions and sensitive transmission lines need to be given full attention by the utility to prevent the occurrence of dynamic power system blackout. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Assessment Method for Substation Capacity Credit of Generalized Power Source Considering Grid Structure
Sustainability 2017, 9(6), 928; doi:10.3390/su9060928
Received: 13 April 2017 / Revised: 20 May 2017 / Accepted: 25 May 2017 / Published: 2 June 2017
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Abstract
This paper presents the concept of the generalized power source in an active distribution network. After the energy storage system (ESS), distributed generators (DG), and demand-side controllable load are connected to the active distribution network, part of the system load can be undertaken
[...] Read more.
This paper presents the concept of the generalized power source in an active distribution network. After the energy storage system (ESS), distributed generators (DG), and demand-side controllable load are connected to the active distribution network, part of the system load can be undertaken by these ESS, DG, and controllable load instead of relying on the capacity of the substation, which greatly improves the reliability of the system. The above-mentioned distributed energy resources in the active distribution network are collectively referred to as the generalized power source (GPS). Substation credible capacity refers to the capacity of the GPS to supply the distribution network that is equivalent at the high voltage distribution network level when considering the faults of the main transformer, 110 kV lines, and circuit breakers. Considering the uncertainties and control strategies of GPS, this paper takes a specific distribution area as the background to study its substituted substation capacity. Based on a sequential Monte Carlo evaluation framework and the principle of constant reliability, an evaluation method of the GPS credible capacity is proposed. In order to verify the effectiveness of the method proposed in this paper, the credible capacity of various typical connection modes of a high voltage distribution network is quantitatively analyzed in the case study, which can provide a reference for the capacity planning of an active distribution network substation and grid structure selection. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Learning of Power Technologies in China: Staged Dynamic Two-Factor Modeling and Empirical Evidence
Sustainability 2017, 9(5), 861; doi:10.3390/su9050861
Received: 18 April 2017 / Revised: 8 May 2017 / Accepted: 17 May 2017 / Published: 19 May 2017
PDF Full-text (475 KB) | HTML Full-text | XML Full-text
Abstract
Cost evolution has an important influence on the commercialization and large-scale application of power technology. Many researchers have analyzed the quantitative relationship between the cost of power technology and its influencing factors while establishing various forms of technical learning curve models. In this
[...] Read more.
Cost evolution has an important influence on the commercialization and large-scale application of power technology. Many researchers have analyzed the quantitative relationship between the cost of power technology and its influencing factors while establishing various forms of technical learning curve models. In this paper, we focus on the positive effects of the policy on research and development (R&D) learning by summarizing and comparing four energy technology cost models based on learning curves. We explore the influencing factors and dynamic change paths of power technology costs. The paper establishes a multi-stage dynamic two-factor learning curve model based on cumulative R&D investment and the installed capacity. This work presents the structural changes of the influencing factors at various stages. Causality analysis and econometric estimation of learning curves are performed on wind power and other power technologies. The conclusion demonstrates that a “learn by researching” approach had led to cost reduction of wind power to date, but, in the long term, the effect of “learn by doing” is greater than that of “learn by researching” when R&D learning is saturated. Finally, the paper forecasts the learning rates and the cost trends of the main power technologies in China. The work presented in this study has implications on power technology development and energy policy in China. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Integrated Natural Gas, Heat, and Power Dispatch Considering Wind Power and Power-to-Gas
Sustainability 2017, 9(4), 602; doi:10.3390/su9040602
Received: 9 March 2017 / Revised: 9 April 2017 / Accepted: 10 April 2017 / Published: 13 April 2017
Cited by 3 | PDF Full-text (3234 KB) | HTML Full-text | XML Full-text
Abstract
A large amount of wind power has to be curtailed due to the inflexibility of the combined heat and power (CHP) system in the heating season in northern China. The power-to-gas (P2G) technology, which uses electricity to produce hydrogen or synthetic natural gas,
[...] Read more.
A large amount of wind power has to be curtailed due to the inflexibility of the combined heat and power (CHP) system in the heating season in northern China. The power-to-gas (P2G) technology, which uses electricity to produce hydrogen or synthetic natural gas, has become a promising energy conversion option for the utilization of surplus power energy. In this paper, an integrated natural gas, heat, and power dispatch (INGHPD) model which balances natural gas, heat, and power demand considering wind power and a P2G unit, is proposed. A natural gas network and P2G are modeled and integrated into the dispatch model. To demonstrate the effectiveness of the proposed model, an integrated energy system consisting of a six-bus power system, a six-node natural gas system, and a district heating system is simulated. The benefits of P2G are investigated in terms of reducing wind power curtailment, as well as system operation cost and CO2 emissions. The results in the deterministic model show that with the introduction of 40 MW P2G, the wind power curtailment rate decreases from 24.0% to 9.7%. The daily wind power energy consumed by P2G reaches 256 MWh and the daily CO2 emissions reduction reaches 46,080 kg. Additionally, the impact of the power and heat demand on the gas production of P2G and of the P2G capacity on the wind power curtailment are also investigated. P2G tends to generate more natural gas when the power demand is low and the heat demand is high. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Tailor-Made Feedback to Reduce Residential Electricity Consumption: The Effect of Information on Household Lifestyle in Japan
Sustainability 2017, 9(4), 528; doi:10.3390/su9040528
Received: 8 December 2016 / Revised: 29 March 2017 / Accepted: 29 March 2017 / Published: 30 March 2017
Cited by 2 | PDF Full-text (8757 KB) | HTML Full-text | XML Full-text
Abstract
Residential smart metering and energy feedback have attracted worldwide attention toward reducing energy consumption and building a sustainable society. Many theoretical studies have suggested the importance of personalized information; however, few feedback demonstrations have focused on household lifestyle. This paper presents a pilot
[...] Read more.
Residential smart metering and energy feedback have attracted worldwide attention toward reducing energy consumption and building a sustainable society. Many theoretical studies have suggested the importance of personalized information; however, few feedback demonstrations have focused on household lifestyle. This paper presents a pilot program of energy feedback reports based on analytical methods to show the relationship between electricity consumption and household lifestyle in Japan. One type of report was for households with a night-oriented lifestyle, which were classified by means of frequency analysis; it was evident that such households should shift to a healthy, environmentally friendly, morning-oriented lifestyle. Another type of report was based on cluster analysis: it pinpointed the dates and times when the household consumed much more electricity than with its regular routine. Through panel data regression analysis, it was found that the reports contributed to reducing daily household electricity consumption—as long as a boomerang effect could be avoided. It was also found that the feedback effect was enhanced by activation of consciousness, norms, and motives. It was observed that activation required a good understanding of the characteristics of electricity consumption and lifestyles of each household. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle A Low Cost, Edge Computing, All-Sky Imager for Cloud Tracking and Intra-Hour Irradiance Forecasting
Sustainability 2017, 9(4), 482; doi:10.3390/su9040482
Received: 31 December 2016 / Revised: 15 March 2017 / Accepted: 17 March 2017 / Published: 23 March 2017
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Abstract
With increasing use of photovoltaic (PV) power generation by utilities and their residential customers, the need for accurate intra-hour and day-ahead solar irradiance forecasting has become critical. This paper details the development of a low cost all-sky imaging system and an intra-hour cloud
[...] Read more.
With increasing use of photovoltaic (PV) power generation by utilities and their residential customers, the need for accurate intra-hour and day-ahead solar irradiance forecasting has become critical. This paper details the development of a low cost all-sky imaging system and an intra-hour cloud motion prediction methodology that produces minutes-ahead irradiance forecasts. The SkyImager is designed around a Raspberry Pi single board computer (SBC) with a fully programmable, high resolution Pi Camera, housed in a durable all-weather enclosure. Our software is written in Python 2.7 and utilizes the open source computer vision package OpenCV. The SkyImager can be configured for different operational environments and network designs, from a standalone edge computing model to a fully integrated node in a distributed, cloud-computing based micro-grid. Preliminary results are presented using the imager on site at the National Renewable Energy Laboratory (NREL) in Golden, CO, USA during the fall of 2015 under a variety of cloud conditions. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Energy Storage System Sizing Based on a Reliability Assessment of Power Systems Integrated with Wind Power
Sustainability 2017, 9(3), 395; doi:10.3390/su9030395
Received: 18 January 2017 / Accepted: 3 March 2017 / Published: 7 March 2017
Cited by 5 | PDF Full-text (2326 KB) | HTML Full-text | XML Full-text
Abstract
The available capacity is a major factor that influences the reliability contribution of energy storage in power systems integrated with wind power. This paper presents the capacity value of the energy storage metrics to quantitatively estimate the contribution of energy storage to the
[...] Read more.
The available capacity is a major factor that influences the reliability contribution of energy storage in power systems integrated with wind power. This paper presents the capacity value of the energy storage metrics to quantitatively estimate the contribution of energy storage to the generation adequacy. A method in accordance with EFC approach has been introduced to model the capacity value of energy storage. The adequacy-oriented model of the energy storage available capacity is proposed for the energy storage system, regarding the roles of the key parameters for the CVES analysis. The case study results indicate that the capacity value of energy storage quantitatively weigh the contribution of the energy storage to system reliability. The sensitivity analysis of the impact factors for the CVES is conducted. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Study on the Evolution Mechanism and Development Forecasting of China’s Power Supply Structure Clean Development
Sustainability 2017, 9(2), 213; doi:10.3390/su9020213
Received: 31 October 2016 / Revised: 26 January 2017 / Accepted: 26 January 2017 / Published: 5 February 2017
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Abstract
The clean development of China’s power supply structure has become a crucial strategic problem for the low-carbon, green development of Chinese society. Considering the subsistent developments of optimized allocation of energy resources and efficient utilization, the urgent need to solve environmental pollution, and
[...] Read more.
The clean development of China’s power supply structure has become a crucial strategic problem for the low-carbon, green development of Chinese society. Considering the subsistent developments of optimized allocation of energy resources and efficient utilization, the urgent need to solve environmental pollution, and the continuously promoted power market-oriented reform, further study of China’s power structure clean development has certain theoretical value. Based on the data analysis, this paper analyzes the key factors that influence the evolution process of the structure with the help of system dynamics theory and carries out comprehensive assessments after the construction of the structure evaluation system. Additionally, a forecasting model of the power supply structure development based on the Vector Autoregressive Model (VAR) has been put forward to forecast the future structure. Through the research of policy review and scenario analysis, the paths and directions of structure optimization are proposed. In this paper, the system dynamics, vector autoregressive model (VAR), policy mining, and scenario analysis methods are combined to systematically demonstrate the evolution of China’s power structure, and predict the future direction of development. This research may provide a methodological and practical reference for the analysis of China’s power supply structure optimization development and for theoretical studies. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Evaluating the Potential of Variable Renewable Energy for a Balanced Isolated Grid: A Japanese Case Study
Sustainability 2017, 9(1), 119; doi:10.3390/su9010119
Received: 30 November 2016 / Revised: 3 January 2017 / Accepted: 9 January 2017 / Published: 14 January 2017
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Abstract
There is a global push to develop renewable energy to further a low-carbon society. However, the nature of variable renewable energy (VRE) sources such as wind power and solar photovoltaic (PV) systems may create problems because electricity grids require a stable power supply
[...] Read more.
There is a global push to develop renewable energy to further a low-carbon society. However, the nature of variable renewable energy (VRE) sources such as wind power and solar photovoltaic (PV) systems may create problems because electricity grids require a stable power supply to match demand. To evaluate the potential capacity of VREs that may be installed, we develop an optimized model that balances power supply and demand and also considers grid balancing by battery storage and load frequency control. The model was applied to a case study of an isolated grid on a remote Japanese island. When set to optimize the grid in terms of lowest cost, the model suggested that, compared with the base case, the capacity of wind power should be increased by a factor of 1.7 and 15.8 for situations without and with battery storage, respectively. Since it was always considered to be more expensive than wind power, no change in solar PV capacity was observed. These approaches resulted in a decrease in the total power generation cost of 2% and 24%, respectively, while total CO2 emissions fell by 3% and 52%, primarily driven by decreased used of the existing fossil-fueled thermal plant. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Multi-Objective Optimization for Equipment Capacity in Off-Grid Smart House
Sustainability 2017, 9(1), 117; doi:10.3390/su9010117
Received: 16 August 2016 / Revised: 7 January 2017 / Accepted: 9 January 2017 / Published: 13 January 2017
Cited by 1 | PDF Full-text (440 KB) | HTML Full-text | XML Full-text
Abstract
Recently, the off-grid smart house has been attracting attention in Japan for considering global warming. Moreover, the selling price of surplus power from the renewable energy system by Feed-In Tariff (FIT) has declined. Therefore, this paper proposes an off-grid smart house with the
[...] Read more.
Recently, the off-grid smart house has been attracting attention in Japan for considering global warming. Moreover, the selling price of surplus power from the renewable energy system by Feed-In Tariff (FIT) has declined. Therefore, this paper proposes an off-grid smart house with the introduced Photovoltaic (PV) system, Solar Collector (SC) system, Hot Water Heat Pump (HWHP), fixed battery and Electric Vehicle (EV). In this research, a multi-objective optimization problem is considered to minimize the introduced capacity and shortage of the power supply in the smart house. It can perform the electric power procurement from the EV charging station for the compensation of a shortage of power supply. From the simulation results, it is shown that the shortage of the power supply can be reduced by the compensation of the EV power. Furthermore, considering the uncertainty for PV output power, reliable simulation results can be obtained. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Control of the Air Supply Subsystem in a PEMFC with Balance of Plant Simulation
Sustainability 2017, 9(1), 73; doi:10.3390/su9010073
Received: 14 November 2016 / Revised: 2 January 2017 / Accepted: 3 January 2017 / Published: 7 January 2017
Cited by 2 | PDF Full-text (1575 KB) | HTML Full-text | XML Full-text
Abstract
This paper deals with the design of a control scheme for improving the air supply subsystem of a Proton Exchange Membrane Fuel Cell (PEMFC) with maximum power of 65 kW. The control scheme is evaluated in a plant simulator which incorporates the balance
[...] Read more.
This paper deals with the design of a control scheme for improving the air supply subsystem of a Proton Exchange Membrane Fuel Cell (PEMFC) with maximum power of 65 kW. The control scheme is evaluated in a plant simulator which incorporates the balance of plant (BOP) components and is built in the aspenONE® platform. The aspenONE® libraries and tools allows introducing the compressor map and sizing the heat exchangers used to conduct the reactants temperature to the operating value. The PEMFC model and an adaptive controller were programmed to create customized libraries used in the simulator. The structure of the plant control is as follows: the stoichiometric oxygen excess ratio is regulated by manipulating the compressor power, the equilibrium of the anode-cathode pressures is achieved by tracking the anode pressure with hydrogen flow manipulation; the oxygen and hydrogen temperatures are regulated in the heat exchangers, and the gas humidity control is obtained with a simplified model of the humidifier. The control scheme performance is evaluated for load changes, perturbations and parametric variations, introducing a growing current profile covering a large span of power, and a current profile derived from a standard driving speed cycle. The impact of the control scheme is advantageous, since the control objectives are accomplished and the PEMFC tolerates reasonably membrane damage that can produce active surface reduction. The simulation analysis aids to identify the safe Voltage-Current region, where the compressor works with mechanical stability. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Comprehensive Benefit Evaluation of the Wind-PV-ES and Transmission Hybrid Power System Consideration of System Functionality and Proportionality
Sustainability 2017, 9(1), 65; doi:10.3390/su9010065
Received: 8 November 2016 / Revised: 31 December 2016 / Accepted: 3 January 2017 / Published: 5 January 2017
Cited by 1 | PDF Full-text (1680 KB) | HTML Full-text | XML Full-text
Abstract
In the background of decreasing fossil fuels and increasing environmental pollution, the wind-photovoltaic energy storage and transmission hybrid power system (or called the wind-PV-ES and transmission hybrid system) has become a strategic choice to achieve energy sustainability. However, the comprehensive benefit evaluation of
[...] Read more.
In the background of decreasing fossil fuels and increasing environmental pollution, the wind-photovoltaic energy storage and transmission hybrid power system (or called the wind-PV-ES and transmission hybrid system) has become a strategic choice to achieve energy sustainability. However, the comprehensive benefit evaluation of such a combined power system is in a relatively blank state in China, which will hinder the reasonable and orderly development of this station. Four parts, the technical performance, economic benefit, ecological impact and social benefit, are considered in this paper, and a multi-angle evaluation index system of the wind-PV-ES and transmission system is designed. The projection pursuit model is used to evaluated system functionality conventionally; relative entropy theory is used to evaluate the system functionality simultaneously; and a comprehensive benefit evaluation model of the technique for order preference by similar to ideal solution (TOPSIS) considering both system functionality and proportionality is constructed. Finally, the national demonstration station of the wind-PV-ES-transmission system is taken as an example to testify to the practicability and validity of the evaluation index system and model. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Assessment of the Carbon Footprint, Social Benefit of Carbon Reduction, and Energy Payback Time of a High-Concentration Photovoltaic System
Sustainability 2017, 9(1), 27; doi:10.3390/su9010027
Received: 23 November 2016 / Revised: 19 December 2016 / Accepted: 21 December 2016 / Published: 25 December 2016
Cited by 1 | PDF Full-text (1597 KB) | HTML Full-text | XML Full-text
Abstract
Depleting fossil fuel sources and worsening global warming are two of the most serious world problems. Many renewable energy technologies are continuously being developed to overcome these challenges. Among these technologies, high-concentration photovoltaics (HCPV) is a promising technology that reduces the use of
[...] Read more.
Depleting fossil fuel sources and worsening global warming are two of the most serious world problems. Many renewable energy technologies are continuously being developed to overcome these challenges. Among these technologies, high-concentration photovoltaics (HCPV) is a promising technology that reduces the use of expensive photovoltaic materials to achieve highly efficient energy conversion. This reduction process is achieved by adopting concentrating and tracking technologies. This study intends to understand and assess the carbon footprint and energy payback time (EPBT) of HCPV modules during their entire life cycles. The social benefit of carbon reduction is also evaluated as another indicator to assess the energy alternatives. An HCPV module and a tracker from the Institute of Nuclear Energy Research (INER) were applied, and SimaPro 8.0.2 was used for the assessment. The functional unit used in this study was 1 kWh, which is produced by HCPV, and inventory data was sourced from Ecoinvent 3.0 and the Taiwan carbon footprint calculation database. The carbon footprint, EPBT, and social benefit of carbon reduction were evaluated as 107.69 g CO2eq/kWh, 2.61 years, and 0.022 USD/kWh, respectively. Direct normal irradiation (DNI), life expectancy, and the degradation rate of HCPV system were subjected to sensitivity analysis. Results show that the influence of lifetime assumption under a low DNI value is greater than those under high DNI values. Degradation rate is also another important factor when assessing the carbon footprint of HCPV under a low DNI value and a long lifetime assumption. The findings of this study can provide several insights for the development of the Taiwanese solar industry. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Macroeconomic Assessment of Voltage Sags
Sustainability 2016, 8(12), 1304; doi:10.3390/su8121304
Received: 10 November 2016 / Revised: 5 December 2016 / Accepted: 5 December 2016 / Published: 12 December 2016
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Abstract
The electric power sector has changed dramatically since the 1980s. Electricity customers are now demanding uninterrupted and high quality service from both utilities and authorities. By becoming more and more dependent on the voltage sensitive electronic equipment, the industry sector is the one
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The electric power sector has changed dramatically since the 1980s. Electricity customers are now demanding uninterrupted and high quality service from both utilities and authorities. By becoming more and more dependent on the voltage sensitive electronic equipment, the industry sector is the one which is affected the most by voltage disturbances. Voltage sags are one of the most crucial problems for these customers. The utilities, on the other hand, conduct cost-benefit analyses before going through new investment projects. At this point, understanding the costs of voltage sags become imperative for planning purposes. The characteristics of electric power consumption and hence the susceptibility against voltage sags differ considerably among different industry subsectors. Therefore, a model that will address the estimation of worth of electric power reliability for a large number of customer groups is necessary. This paper introduces a macroeconomic model to calculate Customer Voltage Sag Costs (CVSCs) for the industry sector customers. The proposed model makes use of analytical data such as value added, annual energy consumption, working hours, and average outage durations and provides a straightforward, credible, and easy to follow methodology for the estimation of CVSCs. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Factors Influencing the Spatial Difference in Household Energy Consumption in China
Sustainability 2016, 8(12), 1285; doi:10.3390/su8121285
Received: 10 October 2016 / Revised: 15 November 2016 / Accepted: 1 December 2016 / Published: 9 December 2016
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Abstract
What factors determine the spatial heterogeneity of household energy consumption (HEC) in China? Can the impacts of these factors be quantified? What are the trends and characteristics of the spatial differences? To date, these issues are still unclear. Based on the STIRPAT model
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What factors determine the spatial heterogeneity of household energy consumption (HEC) in China? Can the impacts of these factors be quantified? What are the trends and characteristics of the spatial differences? To date, these issues are still unclear. Based on the STIRPAT model and panel dataset for 30 provinces in China over the period 1997–2013, this paper investigated influences of the income per capita, urbanization level and annual average temperature on HEC, and revealed the spatial effects of these influencing factors. The results show that the income level is the main influencing factor, followed by the annual average temperature. There exists a diminishing marginal contribution with increasing income. The influence of urbanization level varies according to income level. In addition, from the eastern region to western region of China, variances largely depend upon economic level at the provincial level. From the northern region to southern region, change is mainly caused by temperature. The urbanization level has more significant impact on the structure and efficiency of household energy consumption than on its quantity. These results could provide reference for policy making and energy planning. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Optimal Operation and Management of Smart Grid System with LPC and BESS in Fault Conditions
Sustainability 2016, 8(12), 1282; doi:10.3390/su8121282
Received: 12 August 2016 / Revised: 31 October 2016 / Accepted: 2 December 2016 / Published: 8 December 2016
Cited by 1 | PDF Full-text (915 KB) | HTML Full-text | XML Full-text
Abstract
Distributed generators (DG) using renewable energy sources (RESs) have been attracting special attention within distribution systems. However, a large amount of DG penetration causes voltage deviation and reverse power flow in the smart grid. Therefore, the smart grid needs a solution for voltage
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Distributed generators (DG) using renewable energy sources (RESs) have been attracting special attention within distribution systems. However, a large amount of DG penetration causes voltage deviation and reverse power flow in the smart grid. Therefore, the smart grid needs a solution for voltage control, power flow control and power outage prevention. This paper proposes a decision technique of optimal reference scheduling for a battery energy storage system (BESS), inverters interfacing with a DG and voltage control devices for optimal operation. Moreover, the reconfiguration of the distribution system is made possible by the installation of a loop power flow controller (LPC). Two separate simulations are provided to maintain the reliability in the stable power supply and economical aspects. First, the effectiveness of the smart grid with installed BESS or LPC devices is demonstrated in fault situations. Second, the active smart grid using LCPs is proposed. Real-time techniques of the dual scheduling algorithm are applied to the system. The aforementioned control objective is formulated and solved using the particle swarm optimization (PSO) algorithm with an adaptive inertia weight (AIW) function. The effectiveness of the optimal operation in ordinal and fault situations is verified by numerical simulations. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle A Comparison of Electricity Generation System Sustainability among G20 Countries
Sustainability 2016, 8(12), 1276; doi:10.3390/su8121276
Received: 24 August 2016 / Revised: 21 November 2016 / Accepted: 1 December 2016 / Published: 7 December 2016
Cited by 4 | PDF Full-text (2275 KB) | HTML Full-text | XML Full-text
Abstract
Planning for electricity generation systems is a very important task and should take environmental and economic factors into account. This paper reviews the existing metrics and methods in evaluating energy sustainability, and we propose a sustainability assessment index system. The input indexes include
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Planning for electricity generation systems is a very important task and should take environmental and economic factors into account. This paper reviews the existing metrics and methods in evaluating energy sustainability, and we propose a sustainability assessment index system. The input indexes include generation capacity, generation cost, and land use. The output indexes include desirable and undesirable parts. The desirable outputs are total electricity generation and job creation. The undesirable outputs are external supply risk and external costs associated with the environment and health. The super-efficiency data envelopment analysis method is used to calculate the sustainability of electricity generation systems of 23 countries from 2005 to 2014. The three input indexes and three undesirable output indexes are used as the input variables. The two desirable outputs are used as the output variables. The results show that most countries’ electricity generation sustainability values have decreasing trends. In addition, nuclear and hydro generation have positive effects. Solar, wind, and fossil fuel generation have negative effects on sustainability. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Multi-Objective Optimization for Smart House Applied Real Time Pricing Systems
Sustainability 2016, 8(12), 1273; doi:10.3390/su8121273
Received: 16 August 2016 / Revised: 15 November 2016 / Accepted: 29 November 2016 / Published: 7 December 2016
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Abstract
A smart house generally has a Photovoltaic panel (PV), a Heat Pump (HP), a Solar Collector (SC) and a fixed battery. Since the fixed battery can buy and store inexpensive electricity during the night, the electricity bill can be reduced. However, a large
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A smart house generally has a Photovoltaic panel (PV), a Heat Pump (HP), a Solar Collector (SC) and a fixed battery. Since the fixed battery can buy and store inexpensive electricity during the night, the electricity bill can be reduced. However, a large capacity fixed battery is very expensive. Therefore, there is a need to determine the economic capacity of fixed battery. Furthermore, surplus electric power can be sold using a buyback program. By this program, PV can be effectively utilized and contribute to the reduction of the electricity bill. With this in mind, this research proposes a multi-objective optimization, the purpose of which is electric demand control and reduction of the electricity bill in the smart house. In this optimal problem, the Pareto optimal solutions are searched depending on the fixed battery capacity. Additionally, it is shown that consumers can choose what suits them by comparing the Pareto optimal solutions. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Robust Sliding Mode Control of Permanent Magnet Synchronous Generator-Based Wind Energy Conversion Systems
Sustainability 2016, 8(12), 1265; doi:10.3390/su8121265
Received: 17 September 2016 / Revised: 19 November 2016 / Accepted: 30 November 2016 / Published: 5 December 2016
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Abstract
The subject of this paper pertains to sliding mode control and its application in nonlinear electrical power systems as seen in wind energy conversion systems. Due to the robustness in dealing with unmodeled system dynamics, sliding mode control has been widely used in
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The subject of this paper pertains to sliding mode control and its application in nonlinear electrical power systems as seen in wind energy conversion systems. Due to the robustness in dealing with unmodeled system dynamics, sliding mode control has been widely used in electrical power system applications. This paper presents first and high order sliding mode control schemes for permanent magnet synchronous generator-based wind energy conversion systems. The application of these methods for control using dynamic models of the d-axis and q-axis currents, as well as those of the high speed shaft rotational speed show a high level of efficiency in power extraction from a varying wind resource. Computer simulation results have shown the efficacy of the proposed sliding mode control approaches. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Impact of Battery’s Model Accuracy on Size Optimization Process of a Standalone Photovoltaic System
Sustainability 2016, 8(9), 894; doi:10.3390/su8090894
Received: 24 June 2016 / Revised: 14 August 2016 / Accepted: 1 September 2016 / Published: 3 September 2016
Cited by 1 | PDF Full-text (1723 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a comparative study between two proposed size optimization methods based on two battery’s models. Simple and complex battery models are utilized to optimally size a standalone photovoltaic system. Hourly meteorological data are used in this research for a specific site.
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This paper presents a comparative study between two proposed size optimization methods based on two battery’s models. Simple and complex battery models are utilized to optimally size a standalone photovoltaic system. Hourly meteorological data are used in this research for a specific site. Results show that by using the complex model of the battery, the cost of the system is reduced by 31%. In addition, by using the complex battery model, the sizes of the PV array and the battery are reduced by 5.6% and 30%, respectively, as compared to the case which is based on the simple battery model. This shows the importance of utilizing accurate battery models in sizing standalone photovoltaic systems. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessArticle Scenarios of Carbon Emissions from the Power Sector in Guangdong Province
Sustainability 2016, 8(9), 863; doi:10.3390/su8090863
Received: 24 July 2016 / Revised: 21 August 2016 / Accepted: 25 August 2016 / Published: 29 August 2016
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Abstract
The electricity power sector plays an important role in both CO2 emissions as well as the target contribution of non-fossil energy. Although the target for the reduction of CO2 emission intensity in Guangdong (GD) has not been released by the central
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The electricity power sector plays an important role in both CO2 emissions as well as the target contribution of non-fossil energy. Although the target for the reduction of CO2 emission intensity in Guangdong (GD) has not been released by the central government, GD has set a goal for increasing the share of non-fossil energy in total energy consumption to 25% in the provincial 13th Five-Year Plan. In this study, the CO2 emissions from the electric power sector and the corresponding share of non-fossil fuels in total energy consumption between 2005 and 2014 were analyzed. The logarithmic mean Divisia index (LMDI) technique was applied for investigating the factors affecting the changes in CO2 emissions. The main results are as follows: in 2014, the CO2 emissions from the electric power sector were 286.54 Mt, of which the net purchased electricity accounted for 22.4%. Economic growth is the main contributor for the increase in CO2 emissions from the electric power sector. Electricity intensity, thermal generation efficiency, CO2 emission coefficient, and electricity supply mix slowed the growth of CO2 emissions. Several energy scenarios were developed, and results showed that the provincial target for the share of non-fossil fuels by 2020 would be achieved by all of the scenarios. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Review

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Open AccessReview Comparing Patent and Scientific Literature in Airborne Wind Energy
Sustainability 2017, 9(6), 915; doi:10.3390/su9060915
Received: 20 February 2017 / Revised: 24 May 2017 / Accepted: 25 May 2017 / Published: 31 May 2017
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Abstract
Airborne Wind Energy (AWE) is a renewable energy technology that uses wind power devices rather than traditional wind turbines that take advantage of the kinetic wind energy, and remain in the air due to aerodynamic forces. This article aims to compare the scientific
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Airborne Wind Energy (AWE) is a renewable energy technology that uses wind power devices rather than traditional wind turbines that take advantage of the kinetic wind energy, and remain in the air due to aerodynamic forces. This article aims to compare the scientific literature with the patents on wind power with tethered airfoils, to obtain better insights into the literature of this area of knowledge. The method used in this study was a comparative bibliometric analysis, using the Web of Science and Derwent Innovations Index databases, and the Network Analysis Interface for Literature Review software and VosViewer. It was possible to verify the main authors, research centers and companies, countries and journals that publish on the subject; the most cited documents; the technological classes; and the networks of collaborations of this work. It was also possible to identify that researches on wind energy with tethered airfoils began their studies in the late 1970s with the first patent apparently dated from 1975 by the inventors Dai and Dai. The first scientific publication was in 1979 by authors Fletcher and Roberts, followed by Loyd in 1980. United States is the country that presented the highest number of patents and scientific papers. Both scientific papers and patents set up networks of collaboration; that is, important authors are interacting with others to establish cooperative partnerships. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Other

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Open AccessDiscussion Chinese Electric Power Development Coordination Analysis on Resource, Production and Consumption: A Provincial Case Study
Sustainability 2017, 9(2), 209; doi:10.3390/su9020209
Received: 23 November 2016 / Revised: 12 January 2017 / Accepted: 31 January 2017 / Published: 4 February 2017
PDF Full-text (2952 KB) | HTML Full-text | XML Full-text
Abstract
In line with the pressures of energy shortage and economic development, Chinese government has adopted a series of measures and policies to promote the exploitation and utilization efficiency of electric power. China is urgently reconsidering its electric power development level and coordinating between
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In line with the pressures of energy shortage and economic development, Chinese government has adopted a series of measures and policies to promote the exploitation and utilization efficiency of electric power. China is urgently reconsidering its electric power development level and coordinating between power supply and demand sides. Therefore, in this paper, Chinese industrial structure of electric power was constructed according to its production process from resource, production and consumption sides. With the constructed industrial structure, the influencing factors on each side were selected to build a measurable evaluation system. Thirty-one Chinese provinces were chosen to explore their development coordination level based on the projection pursuit model and coupling coordination model. By the projection pursuit model, improved projection directions and best projection vectors of each province were found to describe the development level of each side. The coupling coordination model was adopted to explore the provincial supply and demand relations between electric power industry side via the indexes of coupling degree, coordination degree and relative development degree. By using ArcGIS mapping analysis, the results show the changes in Chinese provincial coupling and coordination development levels from 2011 to 2014. Finally, using the evaluation results, optimal strategies were discussed for improving the coordination of Chinese electric power development from different aspects, such as technical support, project approval and supervision, and demand side management. The findings prove that projection pursuit model and coupling coordination model can evaluate the electric power development level and describe their dynamic changing coordination relations effectively. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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Open AccessCase Report Economic and Environmental Benefits of Optimized Hybrid Renewable Energy Generation Systems at Jeju National University, South Korea
Sustainability 2016, 8(9), 877; doi:10.3390/su8090877
Received: 27 June 2016 / Revised: 16 August 2016 / Accepted: 22 August 2016 / Published: 2 September 2016
Cited by 4 | PDF Full-text (7413 KB) | HTML Full-text | XML Full-text
Abstract
In order to minimize the social and environmental concerns arising from the use of traditional energy resources such as fossil fuels and nuclear energy, the South Korean government has attempted to develop alternative energy resources. In particular, the large educational institutes and islands
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In order to minimize the social and environmental concerns arising from the use of traditional energy resources such as fossil fuels and nuclear energy, the South Korean government has attempted to develop alternative energy resources. In particular, the large educational institutes and islands in South Korea—which have the motivation and potential to provide electrical services—are required to install renewable electricity generation facilities to reduce the burden on the local grid systems. With this trend, the current study investigates potential configurations of renewable electricity generation systems to supply the electrical demand of Jeju National University, located on the largest island in South Korea. The potential configurations suggested by the simulation results are evaluated by renewable fraction, cost of energy (COE), and total net present cost (NPC). The suggested configurations show a renewable fraction of 1.00 with COE of $0.356–$0.402 per kWh and NPC of $54,620,352–$51,795,040. Based on the results, both implications and limitations are examined. Full article
(This article belongs to the Special Issue Sustainable Electric Power Systems Research)
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