District heating systems offer the possibility of lowering emissions and support the goal of reaching a carbon-neutral energy system by integrating renewable heat sources. Therefore, this work provided a systematic li...
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District heating systems offer the possibility of lowering emissions and support the goal of reaching a carbon-neutral energy system by integrating renewable heat sources. Therefore, this work provided a systematic literature review to identify potential research gaps and show the literature distribution over the relevant topics. The focus is on the design optimization with (non-)linear programming of district heating systems in the context of decarbonization. Furthermore, crucial energy balance equations were extracted from the literature for a potential optimization problem. The systematic literature review limited its search to two databases, 10 years timespan, a quality measure, and uses keywords regarding topic and method. Categories were derived based on the subject and literature to cluster the found publications and identify potential research gaps. The results showed potential research gaps in the depiction of different stakeholder decisions, reduction of computational efforts, and their resulting uncertainties. Additionally, they identified gaps in the integration of low-grade heat sources, thermal storage facilities, and energy converters, especially geothermal energy, large-scale heat pumps, and seasonal storages.
In the past years, augmented Lagrangian methods have been successfully applied to several classes of non-convex optimization problems, inspiring new developments in both theory and practice. In this paper we bring mos...
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In this paper, we propose two proximal gradient algorithms with variance reduction for stochastic mixed variational inequality problems. One is a proximal extragradient algorithm and another is a proximal forward-back...
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In this paper, we propose two proximal gradient algorithms with variance reduction for stochastic mixed variational inequality problems. One is a proximal extragradient algorithm and another is a proximal forward-backward-forward algorithm. Under the monotonicity assumption on the mapping F and other moderate conditions, we derive some asymptotic convergence properties and O(1/k) convergence rate in terms of the restricted gap function values for the proposed algorithms. Furthermore, under the bounded metric subregularity condition, we investigate the linear convergence rate and oracle complexity bounds for the proposed algorithms when the sample-size increases at a geometric rate. If the sample-size increases at a polynomial rate of [k+1](-s) with s > 0, the mean-squared distance of the iterates to the solution set decays at a corresponding polynomial rate, while the iterations and oracle complexities to obtain an epsilon-solution are O(1/epsilon(1/s)) and O(1/epsilon(1+1/s)) respectively. Finally, some numerical experiments on stochastic network games and traffic assignment problems indicate that the proposed algorithms are efficient. (c) 2022 Elsevier B.V. All rights reserved.
Smart grids with self-healing (SH) capability provide an important intelligent feature to help in fast correction actions in case of network faults. SH architecture consists of modern communication systems, smart equi...
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Smart grids with self-healing (SH) capability provide an important intelligent feature to help in fast correction actions in case of network faults. SH architecture consists of modern communication systems, smart equipment, and intelligent sensors. With the high cost of SH components (especially smart ring main unit (SRMU)), optimization is required to achieve optimum performance with minimum cost. This study presents a proposed methodology to determine the optimum number and locations of SRMUs in electricity distribution networks considering various cost issues. The disconnection cost of on-grid photovoltaic (PV) plants is taken into consideration as an important factor in determining the locations of the SRMUs. The nonlinear programming (NLP) optimization technique is used to determine the required number of SRMUs, considering the cost/benefit analysis (cost of upgrading MRMUs to SRMUs/benefit due to interruption time reduction), which is the most important factor from DISCOs' perspective. The mixed integer linear programming (MILP) optimization technique is employed for selecting the optimal locations of the SRMUs considering the cost of losses, energy not supplied (ENS), and PV disconnection, which improves network operation cost. The methodology takes into consideration the cable failure rate and the interest rate. Moreover, the study introduces the Egyptian electrical distribution network and a pilot project for control centre development using SRMUs. The methodology is applied to a modified IEEE 37-node test feeder and a part of a specific district network in South Cairo consisting of 158 nodes;both systems include a number of PV distributed generation plants. Simulation results are presented to show the effectiveness of the proposed method.
This paper introduces an approach for synthesizing feasible safety indices to derive safe control laws under state-dependent control spaces. The problem, referred to as Safety Index Synthesis (SIS), is challenging bec...
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Increasing process of sour crude oil and demand of low-sulfur oil products expand the desulfurization units in refineries, which raises the desulfurization solvent circulation as well as the energy cost for solvent re...
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Increasing process of sour crude oil and demand of low-sulfur oil products expand the desulfurization units in refineries, which raises the desulfurization solvent circulation as well as the energy cost for solvent regeneration. In this work, synthesis of desulfurization solvent network with multi-stage solvent regeneration is investigated to reduce the energy cost. Firstly, this work presents superstructures for desulfurization solvent network with regeneration considering one-stage structure, two-stage cascaded structure, and two-stage parallel structure, respectively. Next, mathematical models for the three cases are formulated as nonlinear programming problems where the objective function aims to minimize the total energy consumption. Finally, a case study is conducted to illustrate the proposed method. The results show that the two-stage structures reduce more energy costs than the one-stage structure by 7.65% and 8.46%, respectively, which means that two-stage regeneration is more attractive. Besides, the parallel structure is better than the cascaded structure, because the energy requirement for solvent regeneration is more sensitive to the outlet concentration of hydrogen sulfide than the inlet concentration. (c) 2022 Elsevier Ltd. All rights reserved.
This paper presents a novel approach to solve linear and nonlinear model predictive control (MPC) problems that requires small memory footprint and throughput and is particularly suitable when the model and/or control...
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This paper presents a novel approach to solve linear and nonlinear model predictive control (MPC) problems that requires small memory footprint and throughput and is particularly suitable when the model and/or controller parameters change at runtime. The contributions of the paper include: (i) a formulation of the nonlinear MPC problem as a bounded-variable nonlinear least-squares (BVNLS) problem, demonstrating that the use of an appropriate solver can outperform industry -standard solvers;(ii) an easily-implementable library-free BVNLS solver with a novel proof of global convergence;(iii) a matrix-free method for computing the products of vectors and Jacobians, required by BVNLS;(iv) an efficient method for updating sparse QR factors when using active-set methods to solve sparse BVNLS problems. Thanks to explicitly parameterizing the optimization algorithm in terms of the model and MPC tuning parameters, the resulting approach is inherently and immediately adaptive to any changes in the MPC formulation. The same algorithmic framework can cope with linear, nonlinear, and adaptive MPC variants based on a broad class of prediction models and sum-of-squares cost functions. (c) 2022 Elsevier Ltd. All rights reserved.
The use of the directional distance function (DDF) in empirical studies has steadily increased over the past decade due to its general representation of a production technology. The DDF is particularly useful in healt...
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The use of the directional distance function (DDF) in empirical studies has steadily increased over the past decade due to its general representation of a production technology. The DDF is particularly useful in health economics as a tool for modeling the hospital technology. Choosing the direction when modeling technology with the DDF is a crucial, albeit not fully resolved, issue that has important ramifications. We first address the choice of direction by using a recently proposed approach for endogenizing the DDF's direction vector and then extend it by imposing regularity conditions on the technology. We apply this framework to a sample of U.S. hospitals and obtain their technology characteristics after grouping them into several distinct categories. We find that publicly owned non-teaching hospitals face substantial opportunity costs of inpatient care - hundreds of outpatient visits must be forgone for each additional admission. This information can help these hospitals forecast the adjustment in outpatient capacity needed to achieve a desired level of inpatient activity. We also find that while urban-area teaching hospitals can substitute approximately two nurses per bed at the frontier of technology, the rate of substitution is less than one nurse per bed at public non-teaching hospitals as well as at all rural-area hospitals. Information on the technological trade offbetween beds and nurses is helpful to hospital administrators and policy makers as nursing shortages intensify and staffing requirements continue to be debated. In addition, we demonstrate that rural public hospitals, which heavily rely on licensed practical nurses (LPNs) to stafftheir beds, are the only hospitals that can meaningfully substitute LPNs for the other inputs, replacing each bed and each registered nurse with medians of 17 and 23 LPNs, respectively. (C) 2022 Elsevier Ltd. All rights reserved.
Binaural reproduction for headphone-based listening is an active research area due to its widespread use in evolving technologies such as augmented and virtual reality (AR and VR). On the one hand, these applications ...
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Reducing the fuel consumption within a power network is crucial to enhance the overall system efficiency and minimize operating costs. Fuel consumption minimization can be achieved through different optimization techn...
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