Economic assessment of a distributed energy system in a new residential area with existing grid coverage in China

A distributed energy system refers to an energy system where energy production is close to end use, typically relying on various small-scale energy generation, conversion and storage technologies. The Chinese government has recently expressed interest in promoting this type of energy system. The paper develops an optimization model to evaluate the economic feasibility of adopting a distributed energy system in a new residential community in Beijing, where grid coverage is already well developed and accessible. The economic implications of adopting different grid connection regimes are also assessed.Results show that compared to the more conventional approach of relying entirely on the grid for electricity supplies, a distributed energy system is cheaper when a connection to the power grid can still be used to draw some electricity during periods of peak demand. Additionally, the economic benefits of electricity buy-back provisions for the distributed energy system are found to be minimal.     

Design and Optimization of an Innovative Solid Oxide Fuel Cell–Gas Turbine Hybrid Cycle for Small Scale Distributed Generation

Distributed power generation and cogeneration is an attractive way toward a more rational conversion of fuel and biofuel. The fuel cell‐gas turbine hybrid cycles are emerging as the most promising candidates to achieve distributed generation with comparable or higher efficiency than large‐scale power plants. The present contribution is devoted to the design and optimization of an innovative solid oxide fuel cell–gas turbine hybrid cycle for distributed generation at small power scale, typical of residential building applications. A 5 kW planar SOFC module, operating at atmospheric pressure, is integrated with a micro gas turbine unit, including two radial turbines and one radial compressor, based on an inverted Brayton cycle. A thermodynamic optimization approach, coupled with system energy integration, is applied to evaluate several design options. The optimization results indicate the existence of optimal designs achieving exergy efficiency higher than 65%. Sensitivity analyses on the more influential parameters are carried out. The heat exchanger network design is performed for an optimal configuration and a complete system layout is proposed. An example of hybrid system integration in a common residential building is discussed.     

Control of proton exchange membrane fuel cells using data driven state space models

Proton exchange membrane fuel cells (PEMFCs) are increasingly being researched upon due to their potential toward sustainable energy generation. Toward improved productivity of PEMFCs, it is important to develop systematic approaches for optimization and control of their operations. PEMFCs pose interesting challenges toward these tasks due to their complex behavior such as nonlinearity and spatial variations. While first principles model based approaches could be used, a more mathematically attractive and cost-effective alternative is to use empirical modeling approaches for representing the system dynamics toward optimization and control. In this paper, we propose to use a novel, innovation form of state space models that facilitate the development of advanced control algorithms such as linear quadratic Gaussian (LQG) and model predictive control (MPC), and provide improved disturbance rejection necessary for these applications. We demonstrate the applications of such model based algorithms via simulations involving a distributed along-the-channel model of the PEMFC, and also present experimental validation on a PEMFC setup.     

Approximate ODE models for population balance systems

We propose an approximate polynomial method of moments for a class of first-order linear PDEs (partial differential equations) of hyperbolic type, involving a filtering term with applications to population balance systems with fines removal terms. The resulting closed system of ODEs (ordinary differential equations) represents an extension to a recently published method of moments which utilizes least-square approximations of factors of the PDE over orthogonal polynomial bases. An extensive numerical analysis has been carried out for proof-of-concept purposes. The proposed modeling scheme is generally of interest for control and optimization of processes with distributed parameters.     

A Modular Process Modeling Tool for the Analysis of Energy Use and Cost in the Pulp and Paper Industry

A novel process modeling tool to facilitate the study of how various process changes in the paper dryer section affect the mill-wide energy system has been developed. A model library with steady-state block models describing paper dryers, heat recovery equipment, and auxiliary systems on component level have been developed using the software Extend. Process models are then created from these block models using graphical programming. In this article, the characteristics of the developed tool are described and a case study where the tool is shown to be useful for analyzing the energy performance of a hybrid dryer section is presented.     

A Modular Process Modeling Tool for the Analysis of Energy Use and Cost in the Pulp and Paper Industry

A novel process modeling tool to facilitate the study of how various process changes in the paper dryer section affect the mill-wide energy system has been developed. A model library with steady-state block models describing paper dryers, heat recovery equipment, and auxiliary systems on component level have been developed using the software Extend. Process models are then created from these block models using graphical programming. In this article, the characteristics of the developed tool are described and a case study where the tool is shown to be useful for analyzing the energy performance of a hybrid dryer section is presented.     

Smart grid technologies and applications for the industrial sector

Smart grids have become a topic of intensive research, development, and deployment across the world over the last few years. The engagement of consumer sectors—residential, commercial, and industrial—is widely acknowledged as crucial for the projected benefits of smart grids to be realized. Although the industrial sector has traditionally been involved in managing power use with what today would be considered smart grid technologies, these applications have mostly been one-of-a-kind, requiring substantial customization. Our objective in this article is to motivate greater interest in smart grid applications in industry. We provide an overview of smart grids and of electricity use in the industrial sector. Several smart grid technologies are outlined, and automated demand response is discussed in some detail. Case studies from aluminum processing, cement manufacturing, food processing, industrial cooling, and utility plants are reviewed. Future directions in interoperable standards, advances in automated demand response, energy use optimization, and more dynamic markets are discussed.     

Stochastic modeling and multi-objective optimization for the APECS system

The Advanced Process Engineering Co-Simulator (APECS), developed at the U.S. Department of Energy's (DOE) National Energy Technology Laboratory, is an integrated software suite that enables the process and energy industries to optimize overall plant performance with respect to complex thermal and fluid flow phenomena. The APECS system uses the process-industry standard CAPE-OPEN (CO) interfaces to combine equipment models and commercial process simulation software with powerful analysis and virtual engineering tools. The focus of this paper is the CO-compliant stochastic modeling and multi-objective optimization capabilities provided in the APECS system for process optimization under uncertainty and multiple and sometimes conflicting objectives. The usefulness of these advanced analysis capabilities is illustrated using a simulation and multi-objective optimization of an advanced coal-fired, gasification-based, zero-emissions electricity and hydrogen generation facility with carbon capture.     

Energy demand management for process systems through production scheduling and control

Demand response (DR) is an integral part of the Smart Grid paradigm, and has become the focus of growing research, development, and deployment in residential, commercial and industrial systems over the last few years. In process systems, energy demand management through production scheduling is an increasingly important tool that has the potential to provide significant economic and operational benefits by promoting the responsiveness of the process operation and its interactions with the utility providers. However, the dynamic behavior of the underlying process, especially during process transitions, is seldom taken into account as part of the DR problem formulation. Furthermore, the incorporation of energy constraints related to electricity pricing and energy resource availability presents an additional challenge. The goal of this study is to present a novel optimization formulation for energy demand management in process systems that accounts explicitly for transition behaviors and costs, subject to time‐sensitive electricity prices and uncertainties in renewable energy resources. The proposed formulation brings together production scheduling and closed‐loop control, and is realized through a real‐time or receding‐horizon optimization framework depending on the underlying operational scenarios. The dynamic formulation is cast as a mixed‐integer nonlinear programming problem based on a proposed discretization approach, and its merits are demonstrated using a simulated continuous stirred tank reactor where the energy required is assumed to be roughly proportional to the material flow. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3756–3769, 2015     

Optimal design of residential cogeneration systems under uncertainty

This paper presents a multi-objective optimization method for designing cogeneration systems in residential complexes and accounting for the involved uncertainty. The model accounts for satisfying the hot water and electric energy demands in a residential complex, while minimizing the total annual cost and the associated greenhouse gas emissions. The proposed model incorporates uncertain data for the ambient temperature, energy demands and prices of the local energy market, which are predicted through forecasting methods for determining the financial and environmental risks. Furthermore, the model accounts for determining the type and size of the central cogeneration unit, thermal storage unit, the needed auxiliary units, as well as the operating conditions. A housing complex in central Mexico is presented as case study. The results show significant economic and environmental benefits for the implementation of the proposed scheme as well as the importance of accounting for the involved uncertainty.     

The Case for Natural Gas Fueled Solid Oxide Fuel Cell Power Systems for Distributed Generation

Natural‐gas‐fueled solid oxide fuel cell (NGSOFC) power systems yield electrical conversion efficiencies exceeding 55% and may become a viable alternative for distributed generation (DG) if stack life and manufacturing economies of scale can be realized. Currently, stacks last approximately 2 years and few systems are produced each year because of the relatively high cost of electricity from the systems. PNNL has performed cost modeling for production of 270 kW (DC) NGSOFC power systems, sized for light industry or large box stores. If mass manufacturing (10.000 units per year) and a stack life of 15 years can be reached, the cost of electricity from an NGSOFC system is estimated to be about 8,2 ¢/kWh, well within the range of commercial and residential retail prices at the national level (9,9–10 ¢/kWh and 11–12 ¢/kWh, respectively). With 5 ¢/kWh in estimated additional benefits from DG, NGSOFC could be well positioned to replace the forecasted 59–77 gigawatts of capacity loss resulting from coal plant closures due to stricter emissions regulations and low natural gas prices.     

A multi-paradigm modeling framework for energy systems simulation and analysis

The modern world energy system is highly complex and interconnected and the effects of energy policies may have unintended consequences. Modeling and analysis tools can therefore be crucial to gaining insight into the interactions between system components and formulating policies that will shape the future energy system. We present in this work a multi-paradigm modeling framework that allows for the continual adjustment and refinement of energy system models as the understanding of the system under study increases. This flexible and open framework allows for the consideration of different levels of model aggregation, timescales and geographic considerations within the same model through the use of different modeling formalisms. We also present a case study of the combined California natural gas and electricity systems that illustrates how the framework may be used to account for the significant uncertainty that exists within the system.     

Status and Promise of Fuel Cell Technology

The niche or early entry market penetration by ONSI and its phosphoric acid fuel cell technology has proven that fuel cells are reliable and suitable for premium power and other opportunity fuel niche market applications. Now, new fuel cell technologies – solid oxide fuel cells, molten carbonate fuel cells, and polymer electrolyte fuel cells – are being developed for near‐term distributed generation shortly after 2003. Some of the evolving fuel cell systems are incorporating gas turbines in hybrid configurations. The combination of the gas turbine with the fuel cell promises to lower system costs and increase efficiency to enhance market penetration. Market estimates indicate that significant early entry markets exist to sustain the initially high cost of some distributed generation technologies. However, distributed generation technologies must have low introductory first cost, low installation cost, and high system reliability to be viable options in competitive commercial and industrial markets. In the long‐term, solid state fuel cell technology with stack costs under $100/kilowatt (kW) promises deeper and wider market penetration in a range of applications including a residential, auxillary power, and the mature distributed generation markets. The Solid State Energy Conversion Alliance (SECA) with its vision for fuel cells in 2010 was recently formed to commercialize solid state fuel cells and realize the full potential of the fuel cell technology. Ultimately, the SECA concept could lead to megawatt‐size fuel‐cell systems for commercial and industrial applications and Vision 21 fuel cell turbine hybrid energy plants in 2015.     

混合供电系统中退役电池的模块化储能操作优化

将退役的动力电池用于混合供电系统可有效地降低投资成本，而针对退役电池储能系统的操作优化则可降低混合供电系统的操作费用，并提升混合供电系统的运行收益。以多个初始容量存在差异的电池组构成的退役电池储能系统为对象，在综合考虑退役电池容量衰退特性和电池组初始状态差异的基础上，构建了以年总费用最小为目标的混合供电系统操作优化模型，并将该方法用于一个由光伏发电和储能电池系统构成的混合供电系统的操作优化中。研究表明：储能电池系统中多组退役电池初始状态的差异，使得各电池组在操作过程中的充放电顺序和频率存在显著差异；储能电池系统的操作优化可有效缓解电池容量衰退，与固定比例调度流程相比，该储能电池系统的年总费用更低。     

Feed distribution in distillation: Assessing benefits and limits with column profile maps and rigorous process simulation

This contribution describes the column profile map (CPM) methodology for designing distributed feed distillation columns. For non‐sharp product distributions, a case study shows that energy savings of approximately 35% can be obtained if the feed stage(s) are designed optimally. Feed distribution allows capital cost savings, expands operating leaves, and can obtain greater separation feasibility. However, this column only has benefits in ternary and higer‐order systems and when product distributions are non‐sharp. To validate these counter‐intuitive claims, a real Benzene, p‐Xylene, Toluene system is modeled using CPMs, and the resulting design parameters are transported to Aspen Plus^®. Using a sum of squared errors objective function to quantify savings, a cost saving trend very similar to the one predicted by the CPM method is obtained. This article therefore describes a complete design methodology for distributed feed systems and provides convincing evidence of benefits of such a system. © 2012 American Institute of Chemical Engineers AIChE J, 59: 1668–1683, 2013     

化工过程系统用能诊断和调优的“夹点分析”法

把热力学与系统工程的方法相结合，进一步将“夹点分析”应用于化工过程系统的用能诊断及调优。首先，从能量的角度将以能量驱动的过程单元如，反应器、精馏塔、压缩机等与换热器网络中的冷、热流股统一起来；然后，利用格子图，总组合曲线（ＧＣＣ）、扩充的总组合曲线（ＥＧＣＣ）、分离的总组合曲线（ＳＧＣＣ）等诊断工具，对化工过程系统进行用能诊断，给出相应的调优措施，并将该方法应用于实际的化工过程。     

Optimal integrated energy systems design incorporating variable renewable energy sources

The effect of variability in renewable input sources on the optimal design and reliability of an integrated energy system designed for off-grid mining operation is investigated via a two-stage approach. Firstly, possible energy system designs are generated by solving a deterministic non-linear programming (NLP) optimization problem to minimize the capital cost for a number of input scenarios. Two measures of reliability, the loss of power supply probability (LPSP) and energy index of reliability (EIR), are then evaluated for each design based on the minimization of the external energy required to satisfy load demands under a variety of input conditions. Two case studies of mining operations located in regions with different degrees of variability are presented. The results show that the degree of variability has an impact on the design configuration, cost and performance, and highlights the limitations associated with deterministic decision making for high variability systems.     

面向服务的开放架构复杂过程系统模型化与优化

分析了复杂过程系统建模优化软件的需求与现状,提出了一种面向服务的开放架构的应用模式.以复杂系统开放方程建模软件ASCEND为基础,对其内在结构、运行模式、外部接口等进行了重组,在AUTOMATION技术支持下实现了AscendServer建模优化核心服务器(组件),能提供基于组件化封装、消息驱动机制和进程间协同工作的一种应用程序接口,使得大规模、复杂系统的建模与优化能够具有更广泛的数据交互、更弹性的应用模式、更强的适应性.某石化企业PTA生产过程水平衡数据调和计算实例验证了这种开放架构优化求解服务的有效性.     

Research Platform: Decentralized Energy System for Sector Coupling

Industrial facilities usually need multiple energy subsystems, e.g., for heat, cold, and electric power supply. Normally, these energy subsystems are controlled locally and independent of each other. Coupling of the different subsystems can open up additional potential. Fraunhofer IISB has developed a demonstration and research platform for investigating the benefits of such sector coupling. A major precondition is to understand the energy flows in the system and establish an overall and flexible system control to realize the required algorithms for setting up an intelligent decentralized energy system. Major components of the overall system are various storages, which extend the degree of freedom for sector coupling and increase the effectiveness of the different subsystems.