Optimization of drying kiln operation

When timber is to be used in the form of furniture it must be dried. Green timber contains many times more water than wood and if it is placed indoors the water will slowly evaporate. When the fibre saturation point is reached the wooden parts start to shrink and the shape of the details will change. If the wood is dried before it is used for furniture parts this calamity is reduced because shrinking has occurred already in the drying kiln when the raw material was in the form of lumber. This drying process uses a lot of heat which is produced by electricity or by firing wood chips or oil in boilers. The cost for these energy sources varies during the season or, for electricity, also during the day. This paper describes how to optimize the use of energy in two drying kilns located at a small carpentry factory in the south of Sweden. Monitored values from the factory are used in order to describe the process in close detail. These values are then used as a basis for a mathematical model which is designed in the form of a mixed integer linear program. The method makes it possible to optimize the operating schemes for the two dryers. Copyright © 2000 John Wiley & Sons, Ltd.     

多级制冷系统超结构优化及其应用研究

在多级制冷系统超结构的基础上，以年操作费用与设备年折旧费用之和的年度总费用最低为目标函数，建立了多机制冷系统优化的混合整数非线性规划。利用该模型对乙烯裂解装置乙烯-丙烯复叠制冷系统进行了优化研究，优化后系统比原制冷系统年度总费用下降15%，经济效益明显。     

Accelerated solution of the transmission maintenance schedule problem: A Bayesian optimization approach

To maximize the maintenance willingness of the owner of transmission lines, this study presents a transmission maintenance scheduling model that considers the energy constraints of the power system and the security constraints of on- site maintenance operations. Considering the computational complexity of the mixed integer programming (MIP) problem, a machine learning (ML) approach is presented to solve the transmission maintenance scheduling model efficiently. The value of the branching score factor value is optimized by Bayesian optimization (BO) in the proposed algorithm, which plays an important role in the size of the branch-and-bound search tree in the solution process. The test case in a modified version of the IEEE 30-bus system shows that the proposed algorithm can not only reach the optimal solution but also improve the computational efficiency.     

Strategic optimization of forest residues to bioenergy and biofuel supply chain

Forest residues are renewable materials for bioenergy conversion that have the potential to replace fossil fuels beyond electricity and heat generation. A challenge hindering the intensified use of forest residues for energy production is the high cost of their supply chain. Previous studies on optimal design of forest residue supply chains focused on biofuel or bioenergy production separately, mostly with a single time period approach. We present a multi‐period mixed integer linear programming model that optimizes the supply chain of forest residues for the production of bioenergy and biofuels simultaneously. The model determines (i) the location, type and size of the technologies to install and the period to install them, (ii) the mix of biofuel and bioenergy products to generate, (iii) the type and amount of forest residues to acquire and the sourcing points, (iv) the amount of forest residues to transport from sources to facilities and (v) the amount of product to transport from facilities to markets. The objective of the model is to maximize the net present value of the supply chain over a 20‐year planning horizon with yearly time steps. We applied the model to a case study in British Columbia, Canada, to investigate the production of heat, electricity, pellets and pyrolysis bio‐oil from available forest harvesting residues and sawmill wastes. Based on current energy generation costs in the region and the predicted operating costs of new conversion plants, the results of our model recommended the installation of small biomass boilers coupled with steam turbines for electricity production (0.5 and 5 MW) and pyrolysis plants with a capacity of 200 and 400 odmt day^?1. We performed a sensitivity analysis to evaluate the sensitivity of the optimal result to changes in the demand and price of products, as well as the availability and cost of forest residues. Copyright © 2014 John Wiley & Sons, Ltd.     

Power generation expansion planning with emission control: a nonlinear model and a GA‐based heuristic approach

This paper presents an application of genetic algorithms (GA) for solving the long‐term power generation expansion planning (PGEP) problem, a highly constrained nonlinear discrete optimization problem. The problem is formulated into a mixed integer nonlinear programming (MINLP) program that determines the most economical investment plan for additional thermal power generating units over a planning horizon, subject to the requirements of power demands, power capacities, loss of load probability (LOLP) levels, locations, and environmental limitations. Computational results show that the GA‐based heuristic method can solve the PGEP problem effectively and more efficiently at a significant saving in runtime, when compared with a commercial optimization package. Copyright © 2005 John Wiley & Sons, Ltd.     

考虑分时电价的煤矿运输系统改造分析

介绍了生产流程中影响负荷转移的重要因素,分析了生产流程中的负荷构成,并考虑分时电价因素,建立了负荷转移模型。将该模型成功应用到煤矿传输系统中,借助分时电价,帮助煤矿企业合理转移负荷,避开峰时电价,达到节约用电成本的目的。     

考虑抽水蓄能及电网运营成本的源荷储协调优化调度

将需求侧响应与抽水蓄能电站纳入系统优化调度,借助需求侧管理与抽水蓄能电站对负荷分布的调控能力以达到提高风电消纳水平和降低电网运营费用的目的。以弃风总量最小和电网购电费用最低为优化目标,并考虑系统功率平衡、机组启停时间、爬坡能力、机组出力界限、系统备用等约束条件,构建含大规模风电的源荷储协调优化调度模型,将模型转化为混合整数问题并应用MOSEK优化软件对其进行求解。算例结果表明,借助需求侧管理与抽水蓄能电站的协作效应,系统对风电消纳能力将有所提高,电网购电费用亦进一步降低。     

A framework to determine optimal offshore grid structures for wind power integration and power exchange

This paper presents a framework to find optimal offshore grid expansions using a transportation model of the power grid. The method extends the standard mixed‐integer linear programming approach to the solution of the transmission expansion planning problem to account for fluctuations in wind power generation and load; this makes the method especially suited to identify optimal transnational offshore high‐voltage direct current grid structures for the integration of large amounts of offshore wind power. The applicability of the method is demonstrated by a case study of the North Sea region. Copyright © 2011 John Wiley & Sons, Ltd.     

Diffused introduction of Organic Rankine Cycle for biomass‐based power generation in an industrial district: a systems analysis

Specific Organic Rankine Cycle (ORC) units dedicated to biomass‐based power production have recently been developed through the introduction of novel organic working media and technology innovation. For small systems, ORC technology appears as an efficient alternative to conventional generation if also process waste heat can be exploited, as resulted in the last few years from the successful operation of several demonstration plants in Austria and Switzerland. The present study aims to investigate the impact of the introduction of ORC units in an industrial context from a system perspective, with particular reference to industrial districts, which are characterized by the concentration in small areas of a large number of medium‐ and small‐sized firms. The paper focuses on the opportunity of combining ORCs, traditional Rankine cycles and multi‐source district heating to meet energy requirements in an industrial district in North Eastern Italy. To this end, a mixed‐integer linear programming model oriented to economical optimization of the system is developed and sensitivity analysis is carried out in order to determine the conditions for the expansion of biomass‐based power generation in the analyzed industrial district and to evaluate potential for CO₂ emission reduction. Copyright © 2004 John Wiley & Sons, Ltd.     

Design and analysis of an aging‐aware energy management system for islanded grids using mixed‐integer quadratic programming

The rapid increase of renewable energy sources made coordinated control of the distributed and intermittent generation units a more demanded task. Matching demand and supply is particularly challenging in islanded microgrids. In this study, we have demonstrated a mixed‐integer quadratic programming (MIQP) method to achieve efficient use of sources within an islanded microgrid. A unique objective function involving fuel consumption of diesel generator, degradation in a lithium‐ion battery energy storage system, carbon emissions, load shifting, and curtailment of the renewable sources is constructed, and an optimal operating point is pursued using the MIQP approach. A systematic and extensive methodology for building the objective function is given in a sequential and explicit manner with an emphasis on a novel model‐based battery aging formulation. Performance of the designed system and a sensitivity analysis of resulting battery dispatch, diesel generator usage, and storage aging against a range of optimization parameters are presented by considering real‐world specifications of the Semakau Island, an island in the vicinity of Singapore.     

RDEA: A recursive DEA based algorithm for the optimal design of biomass supply chain networks

The optimal design of supply chain networks is often examined based on one or more economic or other criteria (e.g., cost, profit environmental impact, danger, time). However, the efficiency of the derived solutions is often ignored. In this work, a recursive DEA (RDEA) algorithm is presented, which introduces a different way of designing a supply chain network. The selection of possible installed facilities is based on minimum cost and maximum efficiency, through a MILP model. Optimal supply chain structure is obtained when the termination criterion is met, yielding only the efficient solutions, while simultaneously reducing the overall cost. An application of this RDEA algorithm to a biomass supply chain is examined. A comparative study is also presented, demonstrating the results obtained when solving the MILP without the proposed algorithm and with the use of an RDEA.     

Review on health-conscious energy management strategies for fuel cell hybrid electric vehicles: Degradation models and strategies

Considering the overwhelming pressure on worldwide demand of fossil fuels and the climate change caused by air pollution, hybrid electric vehicles have seen a promising future thanks to the development of renewable energy sources. Among various kinds of energy sources that have been used in hybrid electric vehicles, lithium-ion battery and proton exchange membrane (PEM) fuel cell exist to be the most favorable ones owing to their high energy density and power density. However, the degradation issues of the energy sources tend to be neglected when designing the energy management strategies for the hybrid electric vehicles. Concerning existing literature, degradation modelling methods of lithium-ion batteries and PEM fuel cells are reviewed and the possibility of integrating them into health-conscious energy management is discussed. Besides, a variety of energy management strategies that have taken the influence of degradations into consideration are reviewed and classified. The contribution of this paper is to investigate the possibility of developing a health-conscious energy management strategy based on accurate estimation of degradation to improve the durability of the system.     

Cost minimization for a local utility through CHP,heat storage and load management

The energy-system optimization model MODEST is described, especially heat storage and electricity load management. Linear programming is used for minimization of capital and operation costs. MODEST may be used to find the optimal investments and when to make them. The period under study can be divided into several linked subperiods which may consist of an arbitrary number of years. MODEST is here applied to a municipal electricity and district-heating system during three five-year periods. Each year is divided into three seasons. Demand peaks, as well as weekly and diurnal variations of, for example, costs are considered. The electricity demand is divided into the three sectors households, industries, and service. The electricity demand may be reduced by energy conservation, replacement of electric heating and load management. The profitability of load management, as well as cogeneration with and without heat storage at different prices of purchased power is calculated. At traditional Swedish electricity prices, the local utility should build a woodchips-fired steam-cycle CHP (combined heat and power) plant. Consumers would find it beneficial to reduce their electricity use by conservation and switching from electric heating to oil and biofuel. If just marginal power production costs are paid, the utility should introduce biomass-fired heat-only boilers instead. Electricity conservation is smaller at these lower prices. Load management is mainly profitable at the first price scheme which includes output-power-related charges. The heat storage should be used threefold: to cover demand peaks, as well as to enable increased CHP output when it is limited by the heat demand or to run heat pumps at cheap night electricity instead of in the daytime. © 1998 John Wiley & Sons, Ltd.     

Predictive models for PEM-electrolyzer performance using adaptive neuro-fuzzy inference systems

Predictive models were built using neural network based Adaptive Neuro-Fuzzy Inference Systems for hydrogen flow rate, electrolyzer system-efficiency and stack-efficiency respectively. A comprehensive experimental database forms the foundation for the predictive models. It is argued that, due to the high costs associated with the hydrogen measuring equipment; these reliable predictive models can be implemented as virtual sensors. These models can also be used on-line for monitoring and safety of hydrogen equipment. The quantitative accuracy of the predictive models is appraised using statistical techniques. These mathematical models are found to be reliable predictive tools with an excellent accuracy of ±3% compared with experimental values. The predictive nature of these models did not show any significant bias to either over prediction or under prediction. These predictive models, built on a sound mathematical and quantitative basis, can be seen as a step towards establishing hydrogen performance prediction models as generic virtual sensors for wider safety and monitoring applications.     

火电厂脱硫系统运行优化控制模型研究

脱硫系统的投用运行,是火电厂二氧化硫减排的重要举措。针对脱硫系统运行过程存在的不确定性与复杂性,基于ILP(区间线性规划)和MIP(混合整数规划)方法,研究开发了一个OOC(运行优化控制)模型,实现脱硫系统运行的经济性和可靠性。开发的OOC模型不仅能够处理表示为离散区间数的不确定性,而且能够反映系统复杂性;同时,模型能够对吸收塔浆液再循环泵组和吸收塔浆液pH的选择进行动态分析。OOC模型应用到一个假设的脱硫系统运行案例问题中,模型结果分析表明:基于原烟气二氧化硫浓度和烟气体积流量以及最低的脱硫效率,权衡吸收塔浆液再循环泵组电能耗费和石灰石粉耗费,选择合适的吸收塔浆液再循环泵组和吸收塔浆液pH,确定脱硫系统运行的总费用,从而实现脱硫系统运行的经济性和可靠性。     

New vortex‐lift and tangential‐force models for HAWT aerodynamic load prediction

Horizontal axis wind turbines (HAWTs) experience three‐dimensional rotational and unsteady aerodynamic phenomena at the rotor blades sections. These highly unsteady three‐dimensional effects have a dramatic impact on the aerodynamic load distributions on the blades, in particular, when they occur at high angles of attack due to stall delay and dynamic stall. Unfortunately, there is no complete understanding of the flow physics yet at these unsteady 3D flow conditions, and hence, the existing published theoretical models are often incapable of modelling the impact on the turbine response realistically. The purpose of this paper is to provide an insight on the combined influence of the stall delay and dynamic stall on the blade load history of wind turbines in controlled and uncontrolled conditions. New dynamic stall vortex and nonlinear tangential force coefficient modules, which integrally take into account the three dimensional rotational effect, are also proposed in this paper. This module along with the unsteady influence of turbulent wind speed and tower shadow is implemented in a blade element momentum (BEM) model to estimate the aerodynamic loads on a rotating blade more accurately. This work presents an important step to help modelling the combined influence of the stall delay and dynamic stall on the load history of the rotating wind turbine blades which is vital to have lighter turbine blades and improved wind turbine design systems.     

绿电与绿氢耦合煤化工的系统建设方案

目的  随着“双碳”进程的推进,煤化工行业的减碳降排势在必行。煤化工过程用氢量大,且目前多以化石燃料转化的灰氢为主,造成了余碳排放。如果将零碳的绿电绿氢与煤化工耦合建设,既有利于煤化工行业节能减排,同时也能为绿电与绿氢的发展提供巨大应用场景。 方法  在此背景下,以典型煤化工工艺煤制乙二醇为例,详细阐述了绿电与绿氢耦合煤制乙二醇的系统建设方案。 结果  分析表明绿氢的引入提高了煤制乙二醇的碳利用率,从传统工艺的21.1%提高到40.5%,而生产每吨成品乙二醇的碳排放强度从2.58 t CO₂降到了0.93 t CO₂。同时通过一体化建设可以降低二次系统建设、运维成本。 结论  绿电绿氢与煤化工耦合建设具有技术可行性,发展前景广阔,但还面临着诸多挑战。     

Overall Optimization for Offshore Wind Farm Electrical System

Based on particle swarm optimization (PSO), an optimization platform for offshore wind farm electrical system (OWFES) is proposed in this paper, where the main components of an offshore wind farm and key technical constraints are considered as input parameters. The offshore wind farm electrical system is optimized in accordance with initial investment by considering three aspects: the number and siting of offshore substations (OS), the cable connection layout of both collection system (CS) and transmission system (TS) as well as the selection of electrical components in terms of voltage level and capacity. Because hundreds of optimization variables, continuous or discrete, are involved in the problem, a mix integer PSO (MIPSO) is required to obtain the solution. The fuzzy C‐means clustering (FCM) algorithm is used to partition the wind farm into several sub regions. The collection system layout in each sub region as well as the connection scheme between offshore substations are optimized by an adaptive PSO‐minimum spanning tree algorithm (APSO‐MST) which has been proposed in a previous work. The simulation results show that the proposed optimization platform can find an optimized layout that save 3.01% total cost compared with the industrial layout, and can be a useful tool for OWFES design and evaluation. Copyright © 2016 John Wiley & Sons, Ltd.     

余热锅炉仿真建模方法的探讨

作为燃气蒸汽联合循环系统中的重要设备，余热锅炉对整个系统的性能起到决定性作用。应用仿真技术进行余热锅炉系统性能研究是一项切实可行的方法，也是进行余热锅炉设计的重要辅助手段。列举了余热锅炉结构及热力特性，系统划分、建模方法、参数选取、二次建模等，并对建模及计算方面要注意的问题进行了详细的阐述。