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Abstract For 118 million residential housing units in the U.S., there is currently a gap between the potential energy savings that can be achieved through the use of existing energy efficiency technologies, and the actual level of energy savings realized, particularly for the 37% of housing units that are considered residential rental properties. Additional quantifiable benefits are needed beyond energy savings to help further motivate residential property owners to invest in energy efficiency upgrades. This research focuses on assessing the adoption of energy efficient upgrades in U.S. residential housing and the impact on rental prices. Ten U.S. cities are chosen for analysis; these cities vary in size across multiple climate zones, and represent a diverse set of housing market conditions. Data was collected for over 159,000 rental property listings, their characteristics, and their energy efficiency measures listed in rental housing postings across each city. Following an extensive data quality control process, over thirty different types energy efficient features were identified. The level of adoption was determined for each city, ranging from 5.3% to 21.6%. Efficient lighting and appliances were among the most common, with many features doubling as energy efficient and other desirable aesthetic or comfort improvements. Then using propensity score matching and conditional mean comparison methods, the relative impact on rent charged in each city was calculated, which ranged from a 6% to 14.1% increase in rent for properties with energy efficient features, demonstrating a positive economic impact of these features, particularly for property owners. This was further subdivided into five types of energy efficiency upgrade and three housing types. Single family homes generally demanded higher premiums with energy efficient features, however there was not a consistent pattern across the types of efficient upgrades. The results of this work demonstrate that investment in energy efficient technologies has quantifiable benefits for rental property owners in the U.S. beyond just energy savings. This methodology and results can also be used in other cities and by property owners, utility companies, or others, ultimately encouraging further investment and positive economic impact in residential energy efficiency and in turn improving energy and resource conservation in the building sector.

Abstract A resilient strategy for optimal demand response control based on the management of highly-distributed electric loads is presented to meet transmission-level control aimed at maintaining voltage stability. The proposed load control scheme balances device- and grid-level objectives simultaneously, and is demonstrated for a system comprising a distributed responsive population of 14,000 residential-sized buildings integrated in a transmission system network consisting of six buses. Air-source heat pumps are implemented as the primary heating source in the responsive building population, and are introduced as a dispatchable grid-side energy resource, where aggregated output can be objectively ramped up or down through the use of an optimal centralized control strategy. A two step multi-objective optimization procedure is implemented to simultaneously satisfy balancing of the power system and customer objectives across a multi-scalar system. At the power system-level, the optimal preventive control scheme is obtained based on steady-state voltage stability constraints. At the customer-level, an optimal demand response strategy is proposed, wherein the aggregate power demand from a population of heat pumps is controlled to follow load-shedding requirements. The customer comfort is continuously maintained by constrained regulation of the thermal set-point governing operation of the heat pump device. The proposed demand-side strategy achieves similar goals to conventional approaches to regulation and spinning reserve ancillary services, but with the significant benefit of higher efficiencies. Under the proposed scheme, ancillary services provided by the electric loads effectively become virtual generators that enhance the voltage stability in power systems operating under increased uncertainty, and replace severe or multiple contingency reserves typically supplied by conventional generators. The proposed demand response control scheme can be extended to other potentially responsive end-use appliances, and opens avenues for increased exploitation of intermittent renewable energy resources while reducing operating costs and emissions.

Abstract Attention is devoted to the application of cylindrical-parabolic solar concentrators in the intermediate temperature range for which wide receivers are used. Suitable indices that describe the performance of the concentrator are defined and evaluated. The effect of each individual parameter on total concentrator performance is investigated. The results of the analysis are presented as a set of graphs which can be used easily when designing parabolic concentrators.

Abstract This paper introduces a new switching means giving a real time optimum connection mode of domestic appliances on either the electrical grid or a photovoltaic panel (PVP) output. A fuzzy algorithm makes the decision which ensures the optimal energy-management based on PVP generation and appliances states with respect to energy-saving criteria. Validation is driven on a 1 kW peak (kWp) PVP and domestic appliances of different powers installed at the Energy and Thermal Research Centre (CRTEn) in the north of Tunisia. Results confirm that energy saved during daylight is 80–90% of the PVP generated energy.

Abstract Predicting the distribution and resource of gas hydrates and understanding gas hydrate forming mechanisms are critical for assessing natural gas hydrate exploration potential, as well as exploiting hydrates. This study aims to provide a portable solution for evaluating resource of natural gas hydrate and quantifying contribution of methane sources via numerical simulations constrained by site-specific data. To numerically describe the complex process of biogenic methane production, an integrated simulation package, TOUGH + Hydrate + React (TOUGH + HR), was developed by coupling reactive transport, biodegradation and deposition of organic matter with behavior of hydrate-bearing system. Based on observed data from site SH2 in the South China Sea, a growing one-dimensional column model was constructed, and simulated via the developed TOUGH + HR tool. The results showed that when considering biogenic methane was the only source for hydrate, simulated maximum saturation of hydrate reached ~ 0.19, which is much lower than the observed value (~0.46), suggesting that the in-situ biogenic methane is not enough to form the high-saturation hydrate. When the upward flux of methane (considered as thermogenic methane) increased to 1.00 × 10−11 k g · m - 2 · s - 1 , both simulated saturation and distribution of hydrates matched the observed data well, including the profile of remained total organic carbon (TOC), the location of interface between dissolved methane and sulfate (SMI), and the derived chlorinity. Simulation results suggest that the ratio of biogenic methane to thermogenic methane forming hydrates was about 1:3. Predicted amount of methane hydrate using the column model was 3258.33 kg, very close to the estimated based on field observation (3112.82 kg).

Abstract The transport of electrons through the gas diffusion layer (GDL) of polymer electrolyte membrane (PEM) fuel cells has a significant impact on the optimal design and operation of PEM fuel cells and is directly affected by the anisotropic nature of the carbon paper material. In this study, a three-dimensional reconstruction of the GDL is used to numerically estimate the directional dependent effective electrical conductivity of the layer for various porosity values. The distribution of the fibers in the through-plane direction results in high electrical resistivity; hence, decreasing the overall effective electrical conductivity in this direction. This finding is in agreement with measured experimental data. Further, using the numerical results of this study, two mathematical expressions were proposed for the calculation of the effective electrical conductivity of the carbon paper GDL. Finally, the tortuosity factor was evaluated as 1.7 and 3.4 in the in- and through-plane directions, respectively.

The biological degradation potential on toluene of the bacteria Pseudomonas fluorescens isolated from soil, as influenced by humic acids, was investigated. The major environmental factors considered of interest for this experiment were temperature, pH of the media, and agitation (rpm), which were optimized using Response Surface Methodology. A face-centered cube design was adopted for this study, and the optimal values for these factors were predicted by the resulting experimental equations. The degradation of toluene by P. fluorescens was tested by incorporating different concentrations (0.02, 0.04, 0.06, 0.08 and 0.10%) of humic acids, extracted from peat moss, in a hydrocarbon degradation medium. The results showed that the microbial degradation of toluene was inhibited by the presence of humic acids.

Abstract The Net Zero Energy House (NZEH) presented in this paper is an energy efficient house that uses available solar technologies to generate at least as much primary energy as the house uses over the course of the year. The computer simulation results show that it is technically feasible to reach the goal of NZEH in the cold climate of Montreal. In terms of the life cycle energy use, which considers the operating and embodied energy of the house, the energy payback time is 8.4–8.7 years, when the NZEH is compared with an average house that complies with the provincial code. The energy payback ratio of the combisystem is 3.5–3.8 compared with the heating system of conventional house. By converting solar energy, the combisystem supplies at least 3.5 times more energy than the energy invested for manufacturing and shipping the system. The life cycle cost analysis of the NZEH shows, however, that due to the high cost of the solar technologies and the low cost of electricity in Montreal, financial payback is never achieved.

Abstract In this paper, we apply flexibility-based operational planning method to microgrid (MG) unit commitment (UC). The problem is formulated based on model predictive control (MPC) paradigm. Conventionally, such paradigm requires the online solution of a mixed-integer optimization problem, which faces difficulties in practical field implementations in a low-power computing microgrid controller. The explicit model predictive control (EMPC) can address this problem of MPC by computing the control laws of MPC in an explicit form offline to enable fast online computation. However, the complexity of the explicit control laws usually grows exponentially with the dimension of the problem, which hinders the application of EMPC in larger systems. In this paper, we integrate learning and EMPC to develop a computationally efficient and rigorous approach for implementing flexibility-based unit commitment paradigms in a microgrid controller with limited computational power. The computational complexity of the proposed approach can be adjusted to meet the hardware limitation of any given microgrid controller, while preserving as much as possible the optimality of the full-fidelity EMPC. This overcomes the drawbacks of traditional EMPC. Moreover, compared to the existing learning-based methods for accelerating optimization algorithms, the proposed approach is able to handle the variables and constraints of the original unit commitment problem systematically, which guarantees the feasibility of its output unit commitment schedules. We conduct case studies to demonstrate the effectiveness of the proposed approach.