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In this paper, a management strategy is developed to realize the real-time optimal torque distribution between the internal combustion (IC) engine and the electric motor of parallel hybrid electric vehicles (HEVs). Without depending on future information, a set of instantaneous cost functions is defined as the objective of a multiobjective problem, which includes vehicle energy consumption, selected emission species, and an evaluation criterion for the battery state of charge (SOC). The varying-domain method is then utilized to introduce a flexible priority among objectives and to transform the multiobjective problem into a nonlinear programming problem, the optimal solution of which is subsequently found by a genetic algorithm, i.e., GENOCOPIII. A comparison of the simulation results demonstrates the flexibility of the proposed varying-domain optimal management strategy (VOMS) under different driving conditions. Compared with the rule-based management strategy (RBMS) and the weighted sum management strategy (WSMS), the VOMS potentially improves the fuel economy, emission reduction, and stability of the SOC. [ABSTRACT FROM PUBLISHER]

This paper describes the application of a novel multiobjective self-adaptive differential evolution (MOSADE) algorithm for the simultaneous optimization of component sizing and control strategy in parallel hybrid electric vehicles (HEVs). Based on an electric assist control strategy, the HEV optimal design problem is formulated as a nonlinear constrained multiobjective problem with competing and noncommensurable objectives of fuel consumption and emissions. The driving performance requirements are considered constraints. The proposed MOSADE approach adopts an external elitist archive to retain nondominated solutions that are found during the evolutionary process. To preserve the diversity of Pareto optimal solutions, a progressive comparison truncation operator based on the normalized nearest neighbor distance is proposed. Moreover, a fuzzy set theory is employed to extract the best compromise solution. Finally, the optimization is performed over the following three typical driving cycles that are currently used in the U.S. and European communities: 1) the file transfer protocol; 2) ECE +EUDC; and 3) Urban Dynamometer Driving Schedule. The results demonstrate the capability of the proposed approach to generate well-distributed Pareto optimal solutions of the HEV multiobjective optimization design problem. The comparison with the reported results of genetic-algorithm-based weighting sum approaches and Nondominated Sorting Genetic Algorithm II reveals the superiority of the proposed approach and confirms its potential for optimal HEV design. [ABSTRACT FROM PUBLISHER]

Hybrid energy storage system (HESS) based on Li-ion and supercapacitor (SC) can play a potential role to stabilize the grid by providing the fast frequency ancillary services. The SC helps to reduce the battery charge/discharge stress and, hence, assists to extend the battery lifespan. The power sharing method (PSM) is the heart in control part to improve the HESS performance and reduce the battery stress. This paper proposes a hybrid PSM and investigates its impact on battery life extension along with its relation to the system design and regulation signal. The performance of hybrid PSM is compared with three other PSMs (low-pass filter, first and second rule based) in a 10 MW/10 MWh full-active parallel HESS for frequency regulation service in two networks: U.K. (national grid) and USA (PJM). Considering maximum possible battery lifetime upto 25 years, result shows that the hybrid PSM approach allows a degree of the better performance for both grid while the sharing of SC is kept maximum 2.0% and 2.5% (for U.S. and U.K. grid, respectively) of the HESS capacity. This study also analyses the impact of PSM on shared capacity and design of HESS for different grid regulation signals. [ABSTRACT FROM AUTHOR]

This paper investigates the fuel consumption minimization problem of a blended-mode plug-in hybrid electric vehicle (PHEV). A simplified mathematical model of the PHEV was constructed to obtain optimal solutions for depleting the battery to a given final state of charge (SOC) under constant vehicle speed. An optimal power strategy was constructed from theoretical analysis and simulation for constant speed cases and then applied to typical drive-cycle simulations for a middle-size plug-in sport utility vehicle in the Urban Dynamometer Driving Schedule, the U.S. Environmental Protection Agency US06 (Supplemental Federal Test Procedure), and the CR-City drive cycles. Simulation results indicate that the proposed control strategy is more efficient than other strategies of interest. Only the electric system loss characteristics, vehicle power demand, total battery energy, and trip distance are needed to implement the proposed control strategy in a PHEV. It does not rely on the detailed trip information other than the total trip distance. Therefore, it is possible to implement the control strategy in real time if the total trip distance is known before the trip. [ABSTRACT FROM PUBLISHER]

In this paper, a multiinput dc–dc converter is proposed and studied for hybrid electric vehicles. Compared to conventional works, the output gain is enhanced. Fuel cell (FC), photovoltaic panel, and energy storage system are the input sources for the proposed converter. The FC is considered as the main power supply, and roof-top PV is employed to charge the battery, increase the efficiency, and reduce fuel economy. The converter has the capability of providing the demanded power by load in absence of one or two resources. Moreover, the power management strategy is described and applied in a control method. A prototype of the converter is also implemented and tested to verify the analysis. [ABSTRACT FROM AUTHOR]

Buildings account for nearly 40 percent of the total energy consumption in the United States. As a critical step toward smart cities, it is essential to intelligently manage and coordinate the building operations to improve the efficiency and reliability of overall energy system. With the advent of smart meters and two-way communication systems, various energy consumptions from smart buildings can now be coordinated across the smart grid together with other energy loads and power plants. In this paper, we propose a comprehensive framework to integrate the operations of smart buildings into the energy scheduling of bulk power system through proactive building demand participation. This new scheme enables buildings to proactively express and communicate their energy consumption preferences to smart grid operators rather than passively receive and react to market signals and instructions such as time varying electricity prices. The proposed scheme is implemented in a simulation environment. The experiment results show that the proactive demand response scheme can achieve up to 10 percent system generation cost reduction and 20 percent building operation cost reduction compared with passive demand response scheme. The results also demonstrate that the system cost savings increase significantly with more flexible load installed and higher percentage of proactive customers participation level in the power network. [ABSTRACT FROM AUTHOR]

Hybrid electric vehicles (HEVs) are considered to be one of the energy-efficient technologies for near-term sustainability of the transportation sector. Over the years, research has focused on improving fuel economy (FE) for a given drive cycle, but FE variability over a realistic range of real-world driving patterns has been generally overlooked, and this can lead to FE benefits not being fully realized in real-world usage. No systematic methodology exists to reduce FE variability by design optimization of powertrain components. This study proposes a methodology of powertrain component optimization to reduce the FE variability due to variations in driving patterns. In the proposed methodology, powertrain components are optimum over a range of driving patterns of different traffic conditions and driving styles simultaneously. The proposed methodology demonstrates the potential to reduce FE variability by up to 34% over six driving patterns of different traffic conditions and driving styles. [ABSTRACT FROM PUBLISHER]

Energy storage is a natural option toward adding the much-needed flexibility for integrating higher amounts of wind generation into the existing power system. This paper presents field results and analyses quantifying the ability and the value of Sodium Sulfur (NAS) battery energy storage toward shifting wind generation from off-peak to on-peak, limiting the ramp rate of wind farm output, and a strategy to integrate the aforementioned goals. The battery can also be considered on a system level independent of wind. It is argued that even in its capacity as a system resource independent of wind, the battery can aid integration of wind generation. Analyses quantifying the value of the battery in the energy and operating reserve markets are presented. Financially optimal locations to site the battery have also been identified. The presented research is a part of the “Wind to Battery” project led by Xcel Energy, a major U.S. utility. [ABSTRACT FROM PUBLISHER]

Residential energy consumption accounts for 21% of the total electricity use in the United States. Unfortunately, research indicates that almost 41% of this power is wasted. Changing the way that consumers use energy may be important in reducing home energy consumption. This paper looks at whether the implementation of certain real-time energy monitors has an impact on the residential rate of energy consumption in a metropolitan area with relatively low electricity rates. In the following case study, 151 Omaha residences were equipped with two variants of the Aztech In-Home Display (Aztech) as well as the Blue Line Power Cost Monitor (PCM) real-time energy monitors for a period of 16 months. The results of the data, 30 days after installation, revealed a statistically insignificant reduction of 12% in mean electrical consumption in houses equipped with a PCM and no reduction in mean consumption in homes using either variants of the Aztech device when compared to a randomly selected control sample. However, they proved effective in the short term if utilized by utilities for mass distribution to foster awareness among participating residents of their own patterns of residential electricity consumption and on the environmental impacts of energy saving. [ABSTRACT FROM AUTHOR]

This paper proposes methodologies to estimate the electric energy and power consumption by light-duty plug-in electric vehicles (PEVs). Using the travel patterns of light-duty vehicles in the U.S. obtained from the 2009 National Household Travel Survey, the PEVs' energy and power consumption are estimated for two uncontrolled charging scenarios. [ABSTRACT FROM PUBLISHER]