Cost optimization and reliability assessment of a microgrid with large-scale plug-in electric vehicles participating in demand response programs

ABSTRACT

In this paper, an effective objective function is proposed to minimize the cost of operation of a microgrid with large-scale plug-in electric vehicles and renewable energy resources. The profit of consumers is taken into account by utilizing the incentives in the demand response programs, and vehicle-to-grid feature of the plug-in-electric vehicles integrated into the grid. The optimization is performed using genetic algorithms. Also, reliability indices of the economically optimized microgrid are computed for various operation configurations in both the grid-tied and islanded modes. Numerical studies are conducted on a microgrid testbed to validate the performance of the proposed strategy.     

Triple-objective optimal sizing based on dynamic strategy for an islanded hybrid energy microgrid

A triple-objective optimal sizing method based on a dynamic strategy is presented for an islanded hybrid energy microgrid, consisting of wind turbine, solar photovoltaic, battery energy storage system and diesel generator. The dynamic strategy is given based on a dynamic complementary coordination between two different master-slave control modes for maximum renewable energy utilization. Combined with the proposed strategy, NSGA-II-based optimization program is applied to the sizing optimization problem with triple different objectives including the minimization of annualized system cost, the minimization of loss of power supply probability and the maximization of utilization ratio of renewable energy generation. The sizing results and the proposed strategy are both compared and analyzed to validate the proposed method in a real case of an islanded hybrid energy microgrid on Dong’ao Island, China.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.     

Multi-criteria PSO-based optimal design of grid-connected hybrid renewable energy systems

ABSTRACT

Human-induced climate change through the over liberation of greenhouse gases, resulting in devastating consequences to the environment, is a concern of considerable global significance which has fuelled the diversification to alternative renewable energy sources. The unpredictable nature of renewable resources is an impediment to developing renewable projects. More reliable, effective, and economically feasible renewable energy systems can be established by consolidating various renewable energy sources such as wind and solar into a hybrid system using batteries or back-up units like conventional energy generators or grids. The precise design of these systems is a critical step toward their effective deployment. An optimal sizing strategy was developed based on a heuristic particle swarm optimization (PSO) technique to determine the optimum number and configuration of PV panels, wind turbines, and battery units by minimizing the total system life-cycle cost while maximizing the reliability of the hybrid renewable energy system (HRES) in matching the electricity supply and demand. In addition, by constraining the amount of conventional electricity purchased from the grid, environmental concerns were also considered in the presented method. Various systems with different reliabilities and potential of reducing consumer’s CO₂ emissions were designed and the behavior of the proposed method was comprehensively investigated. An HRES may reduce the annualized cost of energy and carbon footprint significantly.     

An isolated AC module for photovoltaic energy conversion

In this paper, an isolated ac module with pseudo dc-link and galvanic isolation is proposed for photovoltaic energy conversion. The studied grid-tie ac module can individually extract the maximum solar power from each photovoltaic panel and transfer to ac utility system. It consists of an interleaved active-clamping single-ended primary-inductive circuit (SEPIC) with a secondary voltage doubler, a full-bridge polarity selector operating under line frequency to achieve high efficiency. For the studied topology, key features such as reduced input current ripple, zero-voltage switching (ZVS) of primary switches, low reverse-recovery current of the output diodes, and lower switch voltage stress are obtained. Also, to reduce input current ripple, an interleaved control strategy is adopted. A simple control strategy is proposed to generate a rectified sinusoidal waveform voltage at the pseudo dc-link capacitors and achieve the high maximum power point tracking (MPPT) accuracy. The operation principles and design considerations of the studied ac module are analyzed and discussed. A prototype with 25–60 V dc input, 110 V/60 Hz ac output and 150 W power rating has been constructed for verifying the feasibility of the proposed ac module.     

Performance enhancement of a stand-alone induction generator-based wind energy system using neural network controller

ABSTRACT

The limitation of self-excited induction generator (SEIG) when used in the stand-alone wind energy system (WES) is poor voltage regulation at variable speed. The indirect vector control (IVC) technique is employed for both the generator-side converter (GSC) and load-side converter (LSC) to regulate the variation of SEIG speed, DC link voltage, and electromagnetic torque independently. Further performance of the proposed IVC technique has been analyzed independently with neural network controller (NNC) and fuzzy logic controller (FLC) as its components. The FLC is replaced by an NNC to improve the performance of the proposed system. IVC of SEIG-based WES has been simulated in MATLAB/SIMULINK software, and the prototype model of the proposed WES is developed to experimentally validate the performance using dSPACE DS-1104 R&D controller board.     

Numerical and experimental investigation of state of health of Li-ion battery

ABSTRACT

Estimation of State of Health (SoH) of Lithium-ion (Li-ion) battery is essential to predict the lifespan of batteries of an electric vehicle (EV). The efficient prediction of battery health indicates to the effective and safe operation of EV. However, delivering an effective and accurate method for the estimation of SoH in the real condition is truly a challenging task. The present study proposed a holistic procedure of combining both experimental and numerical investigations to conduct the fundamental study on coupled mechanical-electrochemical behavior of Li-ion battery. The proposed investigation highlighted the effect of stress on the capacity of the battery, considering capacity fade as an equivalent parameter to its health for real-time estimation of SoH. Finally, a simple model of Artificial Neural Network (ANN) is provided, which shows the linear dependency of stress with the SoH. The results obtained from the ANN model are validated with a Linear Regression (LR) model for a better understanding of the inspection. The predicted value of mean Square Error (MSE) and R square error in the ANN training model are found to be 0.000309 and 0.849687, respectively. Whereas for the test model, these predicted values are found to be 0.000438 and 0.819347, respectively.     

Multi-objective-based optimal transmission switching and demand response for managing congestion in hybrid power systems

ABSTRACT

This paper proposes a novel congestion management (CM) approach by using the optimal transmission switching (OTS) and demand response (DR) for a system with conventional thermal generators and renewable energy sources (RESs). In this paper, wind and solar PV units are considered as the RESs. The stochastic behavior of wind and solar PV powers are modeled by using the appropriate probability density functions (PDFs). The proposed CM methodology simultaneously optimizes the generation dispatch, demand response, and also the network topology of the power system. The OTS identifies the branches that should be taken out of service by significantly reducing the operating cost of the system while respecting the system security. Here, the total operating cost minimization/social welfare maximization and system losses minimization are considered as the objectives to be optimized. The proposed CM problem is solved using the multi-objective Jaya algorithm and it is used to determine a set of Pareto-optimal solutions. The Jaya algorithm is simple and it does not have any algorithmic-specific parameters to be tuned. This aspect reduces the designer’s effort in tuning the parameters to arrive at the optimum objective function value. A fuzzy logic-based approach is used to identify the best compromise solution. The effectiveness of the proposed CM approach is examined on modified IEEE 30 and practical Indian 75 bus test systems. The obtained simulation results are analyzed and they show the effectiveness of the proposed approach.     

Investigation of three system shut-down strategies alongside optimization suggestion for proton exchange membrane fuel cells via in-situ measurements

ABSTRACT

Carbon corrosion caused by H₂/O₂ interface during the shut-down process is one of the factors that exacerbate the overall degradation of proton exchange membrane fuel cells (PEMFC) in automotive applications. Numerous studies have shown that system strategies are beneficial for reducing the duration of H₂/O₂ interface and alleviating performance degradation. In this paper, three different shut-down strategies are investigated and compared based on the internal behaviors acquired by in-situ measurements. For the three shut-down strategies, reverse current and high potential are mainly observed in a lower constant current and constant power strategy. Comparatively speaking, the internal uniformity of the cell under constant current and power load is better than that with constant voltage strategy when the shut-down time is about the same. The results suggest that adopting a higher constant power load followed by a larger voltage load during the shut-down process can effectively shorten the shut-down time and relieve carbon corrosion. These results add significant new insights into the shut-down process and will be of practical importance in directing design of combined shut-down strategy that can withstand carbon corrosion.     

“We're not NIMBYs!” Contrasting local protest groups with idealised conceptions of sustainable communities

Abstract

The term “NIMBY” is used prolifically in both academic literature and general public discourse to describe a locally based action group protesting against a proposed development. It is frequently used to dismiss groups as selfish or ill-informed, as is illustrated both by those who accuse opponents of possessing such characteristics and also by the attempts of many community groups to reject the label. This lies in sharp contrast to the much encouraged notions of public participation in planning and community life as proposed by the UK government's proclaimed vision of a “sustainable community”. This paper argues that this dichotomy between “good” and “bad” participation can be misleading, by drawing on research from two case studies where locally based community groups opposed a specific, detailed development. The paper contributes to a burgeoning literature that reappraises conventional understandings of such groups by analysing often overlooked facets of protest groups, concluding that the conventional conceptualisations of them as NIMBY is inadequate and unhelpful in academic debate.     

Novel Temperature Control Technique for a Medicinal Herb Dryer System Powered by a Photovoltaic Array

Each plant has its own optimal drying temperature, especially for the medicinal herbs, because they are sensitive to heat. If the drying temperature becomes more than the optimal value, some chemical reactions will occur and influence the quality of the dried herb, such as color, taste, and aroma. While if the drying temperature becomes lower than the optimal value, the drying process will slow down, and consequently an expected degradation in the quality of the herb may occur, due to insects and fungi infestation which increase in moist conditions. This paper presents a new temperature control technique for a medicinal herb dryer system. The technique fixes the drying temperature of the medicinal herbs at 40^°C, even in cases of rapidly changing atmospheric conditions. The control of the dryer temperature is achieved through using the proportional integral (PI) controller. The designed dryer contains two systems, which are the thermal and the electrical systems. The thermal system is designed to heat the drying air by using solar energy and bio-gas fuel. Whereas the electrical system, which contains a photovoltaic (PV) modules and a battery, is designed to supply the different electrical loads of the dryer system. The control technique is investigated through simulation work by using MATLAB-SIMULINK. The simulation results indicate the high capability of the proposed technique in controlling the drying temperature, even in cases of rapidly changing atmospheric conditions.     

Investigation of the effects of battery types and power management algorithms on drive cycle simulation for a range-extended electric vehicle powertrain

Fuel cell (FC) hybrid vehicle power trains are an attractive technology especially for automotive applications because of their higher efficiency and lower emissions compared to conventional vehicles. This study focuses on the design of an FC hybrid power train system and evaluation of its simulations for a given speed profile through two alternative power management algorithms (PMAs). Parameters suitable for a small vehicle were taken into consideration in the mathematical model of the vehicle. The proposed hybrid power train consists of an energy storage system, composed of a 4-kg battery pack (either lithium-ion (Li-ion) battery, nickel metal hydride, or nickel–cadmium) and a direct methanol fuel cell (DMFC) as the range extender. The PMAs basically aim to fulfill the power requirements of the vehicle and decide how to command the power split between the battery and the FC. The model comprising a DMFC, a battery, and PMAs was developed in MATLAB/Simulink environment. The polarization curve of the FC was obtained using a one-dimensional DMFC model. Vehicle power requirements for a drive cycle were calculated using the equations of longitudinal dynamics of vehicle, and the results were integrated into MATLAB/Simulink model. As a result of the simulations, methanol consumption, state of charge of the battery, and power output of the FC were compared for the PMAs. This comparison shows the effect of PMAs on the hybrid vehicle performance for three battery types. The results indicate that the vehicle range could be increased when proper strategy is used as PMA.     

Integrated energy management strategy of powertrain and cooling system for PHEV

ABSTRACT

Energy management strategy (EMS) is crucial in improving the fuel economy of plug-in hybrid electric vehicle (PHEV). Existing studies on EMS mostly manage powertrain and cooling system separately which cannot get the minimum total energy consumption. This paper aims to propose a novel EMS for a new type of dual-motor planetary-coupled PHEV, which considers cooling power demand and effect of temperature on fuel economy. Temperature-modified engine model, lithium-ion battery model, two motors, and cooling system models are established. Firstly, the separated EMS (S-EMS) is designed which manages powertrain and cooling system separately. Sequentially, after the analysis of thermal characteristics of the powertrain and cooling system, the thermal-based EMS (T-EMS) is then proposed to manage two systems coordinately. In T-EMS, cooling power demand and the charging/discharging energy of motors are calculated as equivalent fuel consumption and integrated into the object function. Besides, a fuzzy controller is also established to deicide the fuel-electricity equivalent factor with consideration of the effect of temperature and state of charge on powertrain efficiency. Finally, the hardware-in-loop experiment is carried out to validate the real-time effect of EMS under the New European Driving Cycle. The result shows that cooling power demand and temperature can significantly affect the fuel economy of the vehicle. T-EMS shows better performance in fuel economy than S-EMS. The equivalent fuel consumption of the cooling system of T-EMS decreases by 27% compared with that of S-EMS. The total equivalent fuel consumption over the entire trip of PHEV using T-EMS is reduced by 9.7%.     

Optimal sizing and siting of renewable energy resources in distribution systems considering time varying electrical/heating/cooling loads using PSO algorithm

Distributed Generation (DG) sources based on Renewable Energy (RE) can be the fastest growing power resources in distribution systems due to their environmental friendliness and also the limited sources of fossil fuels. In general, the optimal location and size of DG units have profoundly impacted on the system losses in a distribution network. In the present article, the Particle Swarm Optimization (PSO) algorithm is employed to find the optimal location and size of DG units in a distribution system. The optimal location and size of DG units are determined on the basis of a multi-objective strategy as follows: (i) the minimization of network power losses, (ii) the minimization of the total costs of Distributed Energy Resources (DERs), (iii) the improvement of voltage stability, and (iv) the minimization of greenhouse gas emissions. The related distribution system was assumed to be composed of the fuel cells, wind turbines, photovoltaic arrays, and battery storages. The electrical, cooling, and heating loads were also considered in this article. The heating and cooling requirements of the system consist of time varying water heating load, space heating load, and space cooling load. In this study, the waste and fuel cell were used to produce the required heating and cooling loads in the distribution system. In addition, the absorption chiller was used to supply the required space cooling loads. A detailed performance analysis was carried out on 13 bus radial distribution system to demonstrate the effectiveness of the proposed methodology.     

Quantified risk assessment on life and property loss from road collision vehicle fires with hydrogen-fueled tank

Hydrogen fuel cell vehicles pose hazards different from conventional vehicles. This paper performs a risk assessment on road collision vehicle fires with hydrogen-fueled tank of 70 MPa. The high voltage battery fire caused by road collision can lead to onboard hydrogen release or explosion. Events progressions are analyzed and typical hydrogen consequences are evaluated quantitatively, including hydrogen jet fires and tank catastrophic rupture. Perimeters around the accident scene are proposed for the safety of general public and first responders, respectively. Risks of fatalities, injuries, and damages are all quantified in financial terms to make it possible to combine and compare.     

Energy consumption estimation model for dual-motor electric vehicles based on multiple linear regression

ABSTRACT

The drive range of electric vehicle (EV) is one of the major limitations that impedes its universalism. A great deal of research has been devoted to drive range improvement of EV, an accurate and efficiency energy consumption estimation plays a crucial role in these researches. However, the majority of EV’s energy consumption estimation models are based on single motor EV, these models are not suitable for dual-motor EVs, which are composed of more complex transmission mechanisms and multiple operating modes. Thus, an energy consumption estimation model for dual-motor EV is proposed to estimate battery power. This article focuses on studying the operating modes and system efficiency in each operating mode. The limitation of working area of each mode ensures the vehicle dynamic performance, then PSO algorithm is adopted to optimize the torque (speed) distribution between two motors to improve the system efficiency in the coupled driving mode. Finally, the energy consumption estimation model is established by multiple linear regression (MLR). The result shows that the proposed model has a high precision in energy consumption estimation of dual-motor EV.     

Local or global food markets: A comparison of energy use for transport

Abstract

This study compares energy use for food transport to a farmers' market in Sweden with energy use for transport in the conventional food system. The farmers' market was investigated through data sampling from on-site investigations. The conventional food system was studied with the aid of life cycle assessments reported in the literature. Overall, the study found no significant differences in levels of energy use for transport to the farmers' market compared with the conventional food system. For certain products, such as fresh fruits and vegetables, transport-related energy use was much lower in the local system although the season in Sweden for this kind of product is restricted to two or three months at the end of the summer. However, there is considerable potential to increase energy efficiency in local food systems by organizing the selling in new ways and by using more energy efficient vehicles.     

Pollution,place, and premature death: evidence from a mid-sized city

ABSTRACT

Neighborhood life expectancy varies by as much as 10 years across the City of Louisville. In 2013, the Greater Louisville Project funded by local government, businesses, and foundations, argued these differences had little to do with environmental factors. The Greater Louisville Project (2013) study argued that these neighborhood differences could be attributed 40% to socio-economic factors (with a major emphasis on education), 10% to physical environment, 30% to health behaviors, and 20% to access to medical care. To test these claims, we construct our own model of neighborhood variation in years of potential life lost (YPLL) by adding two variables testing environmental degradation. We operationalise two separate measures of environmental contamination: proximity to EPA designated brownfield sites and proximity to chemical factories in an industrial park in the neighborhood known as “Rubbertown”. We conduct several regression analyses, which show a relationship between proximity to environmental contaminants and an increase in neighborhood YPLL. Our beta weights challenge the claims made by the Greater Louisville Project, which minimize the impact nearness to environmental contaminants has on reductions in life expectancy in Louisville neighborhoods.     

Electricity nanogenerator from egg shell membrane: A natural waste bioproduct

ABSTRACT

In the era of developing technologies, there is always been a crisis of rising demands of energy. There is no skepticism that a lot of energy is being produced every hour for almost each and every field, but still an exploration is needed to come up with new and viable options for energy creation. The same is the objective of this paper which proposes the use of waste biomaterials in association with organic and inorganic materials as a source of energy to power up small electronic devices. In this research egg shell membrane (ESM)-based triboelectric nanogenerator (TENG) is proposed in combination with calotropis (Calo), cellulose from fruit of Bombax Ceiba (BOM), cellulose in form of tissue paper (TISU), dog hair (DH), polytetrafluoroethylene (PTFE), aluminum (Al), and copper (Cu). ESM is eco-friendly waste food by-product and available in abundance. Characterization of ESM is done by scanning electron microscope (SEM), atomic force microscope (AFM), X-ray diffraction (XRD), and Fourier transform infrared spectrophotometer (FTIR). The proposed ESM-PTFE-based TENG power up 462 green LEDs (462 × 2 V = 924 V ~ 1 kV) without rectifier and produced up to 7.61 µJ energy with 4.7 µF capacitor at 200 tapings. All the proposed ESM-based TENG combinations generate sufficient voltage to turn ON the wrist watch. This green-energy-based TENG has potential application in various fields especially related to medical devices.