Dynamic optimization of natural gas networks under customer demand uncertainties

An inventory-theory-based interval stochastic programming method and its application to Beijing’s electric-power system planning

Natural gas (NG) transmission networks have been recognized as a cost-effective strategy for the distribution of hydrogen (H2). Thermophysical properties of H2-enriched NG are critical to the design and operations of these mixtures. Viscosities of H2-enriched NG mixtures (with H2 mol % values of 0, 5, 20, 50, and 80) were measured at temperatures from 223 to 323 K and pressures up to 30 MPa using a capillary tube viscometer. The measured viscosity data were evaluated against the predictions of a residual entropy scaling (SRES) method, the corresponding states using molecular dynamic simulations of Lennard-Jones fluids, a one-fluid reference corresponding states model (Pedersen), and an extended corresponding state SUPERTRAPP model. All the models were adequate for predicting the measured viscosities. This work contributes accurate viscosity data for H2-enriched NG blends and enhances the understanding of the blends’ properties, which enable modification to the NG distribution facilities to accommodate H2 transportation.

In response to Governor Brown’s January 2016 state of emergency proclamation regarding the Aliso Canyon gas leak, SB 826 (Leno, 2016) requested that the California Council on Science and Technology (CCST) provide the State with up-to-date information on all currently operating underground natural gas storage fields in California. CCST was instructed to provide an independent technical assessment answering three key questions about: The risks California’s underground gas storage facilities pose to health, safety, environment, and infrastructure; Whether California needs underground gas storage to provide for energy reliability through 2020; and How implementation of California’s climate policies changes the future need for underground gas storage. From a statewide field of leading energy researchers, CCST selected Jens T. Birkholzer, PhD, and Jane C.S. Long, PhD, to serve as co-chairs of the 12-member CCST Report Steering Committee – which supervised 21 Report Authors with expertise spanning hydrogeology and reservoir engineering, risk assessment, public and occupational health, greenhouse gas (GHG) emissions, and energy analysis and economics. Each report chapter was subject to a peer review process by independent experts, while another independent expert served as Report Monitor to oversee the process, ensuring that peer review comments were sufficiently addressed in the final report. An additional Oversight Committee reviewed the entire process, including conflict-of-interest declarations. The report’s findings and conclusions are based on a review of published literature and official and voluntary databases, which the Report Authors compiled between January through September 2017, and delivered to the California Public Utilities Commission in January 2018. Key findings and conclusions include: Safety: The risks associated with underground storage (UGS) facilities can be managed, and, with appropriate regulation and safety management, may become comparable to risks in other types of energy facilities found acceptable in California, such as oil refineries and natural gas power plants. At each UGS facility, the State should ensure timely and thorough implementation of the new regulations coming into force in 2018 set by the California Department of Conservation’s Division of Oil, Gas, and Geothermal Resources (DOGGR). Those regulations emphasize new and safer well completions, risk and safety management plans, and requirements for well integrity testing and monitoring. The report recommends that the State go further and require more quantitative risk assessment activities, including consideration of human and organizational factors affecting risk. The State should also implement an independent and mandatory review program to evaluate the effectiveness of these new regulations and the rigor of their application in practice, with opportunity for public comment and public dissemination of the review results. Facility-by-Facility Evaluation: Any industrial operation involves some risk to health, safety, and environment. This report assessed various risk-related characteristics across UGS facilities in California, and found a small list of facilities had relatively higher potential risk compared to others. Reliability of Natural Gas Supply: California’s energy system currently requires natural gas and UGS facilities to run reliably, primarily because many residential and commercial buildings in California rely on natural gas for heating during the winter, and because natural gas provides electricity when solar and wind power are not available. The peak demand for natural gas during the winter currently exceeds the ability of pipelines to bring natural gas into the State of California, so natural gas must be stored during periods of low demand in order to have it available to meet peak demand. Near-Term Alternatives to UGS: Closing any or all UGS facilities in the near term would involve replacing UGS facilities with new pipelines or natural gas storage capacity, and require very large investments. Such new natural-gas-related infrastructure would bring its own risks and would further obligate the State to the use of natural gas for decades. The risks, costs, and benefits associated with alternatives to UGS storage should be evaluated accordingly. Long-Term Need for Underground Gas Storage: California’s climate policies in future decades could still necessitate the continued use of natural gas. Also, energy systems that meet the climate goals may require underground storage of natural gas, biogas, or hydrogen, as well as sequestration of carbon dioxide. The State should develop a more complete and integrated plan to understand how the role of natural gas might evolve; assess possible energy portfolios that both meet GHG emission constraints and achieve energy reliability; and consider the potential need for UGS facilities in the future.

Strong coupling of power systems and natural gas transmission networks through gas-fired generators and power-to-gas (P2G) bring great possibility of collaborative control of the integrated electricity-gas system (IEGS) in the future. For power grid, corrective control (CC) is employed to satisfy security constraints at post-contingency state with lowest control cost. This paper proposes an approach for alleviating post-contingency overload by taking advantage of the complementarity between power grid and natural gas system. The key issue of this approach is treated as a security-constrained optimal gas-power flow (SC-OGPF) model to minimize corrective cost. At post-contingency stage, various controllable resources in IEGS are comprehensively considered, including gas generators, P2G, wind curtailment, conventional generators and loads. The optimization model is solved based on second order cone programming (SOCP), whose efficiency is much higher than traditional nonlinear methods. Further, for the deficiency in accuracy of the SOCP based OGPF model, which is caused by the second order cone relation of non-convex Weymouth gas flow equation, a convex hull (CH) theory based improved relaxation method for SC-OGPF is proposed to displace the existing model. Finally, case studies on a IEGS system which integrates the IEEE 118-bus grid and the Belgian 20-node natural gas network demonstrate the superiority in effectiveness and efficiency of the proposed approach.

This presentation demonstrates a new natural gas network module implemented in the optimization model ldquoeTransportrdquo, including nodes, pipes, valves and compressors. A special linearization technique is used to keep track of the gas pressure in a generic network structure. Together with models for gas source and storage, gas-fired power plants and the existing electricity network module, the new gas module makes it possible to analyze interconnected natural gas and electricity networks where both operational and structural (investment) changes in one part of the system will influence capacities and performance in the rest of the system.

The security of natural gas supply and demand has always been an important topic, and as a result, analyzing and predicting the supply and demand of natural gas has received considerable attention from researchers. Numerous studies have extensively researched the supply and demand of natural gas. The main purpose of this study is to explore the supply‐demand balance mechanism for natural gas security. A system dynamics model is constructed to assess the supply and demand of natural gas in Sichuan Province, China. A new system dynamics model based on domestic gas, production gas, ecological environment and natural gas supply is proposed. The study considers four scenarios: natural development, economic priority development, environmental priority development and coordinated development. The results show that the rapid economic development has led to an excessive environmental carrying capacity, a larger gap between natural gas supply and demand, a decline in the quality of life of residents, and even affected the energy security of Sichuan Province and China. The findings also show that people's overprotection of the environment can lead to slow economic development, which prevents it from achieving its desired goals. The coordinated development scenario in this paper not only ensures the production of natural gas and the quality of life of residents, but also is an optimal scheme with low energy consumption and pollution. According to the research conclusions, considering the overall situation of China's energy security and the situation in Sichuan Province, the author proposes reforms from the supply and demand sides of natural gas.

Accommodating of future demand uncertainty is an important issue in IP networks to continue at acceptable level of service during high traffic load periods. This aspect should also be considered during optical backbones design for high-speed client networks. This paper presents an intelligent fuzzy adaptive approach for spare bandwidth management in Dense Wavelength Division Multiplexing (DWDM) optical transport network based on link state variables. First forecasted part of demand matrix is routed in the network using shortest path algorithm. Then, the available wavelengths are allocated to future demand uncertainties. The fuzzy controller decides according to bandwidth availability and demand uncertainty memberships. The simulation results achieved from the Pan European test bench network demonstrate the efficiency of proposed approach to accommodate future demand uncertainty in uncertain environments.

Summary The industrial and residential market for natural gas produced in the United States has become increasingly significant. Within the past 10 years, the wellhead value of produced natural gas has rivaled and sometimes exceeded the value of crude oil. Forecasting natural gas supply is an economically important and challenging endeavor. This paper presents a new approach to predict natural gas production for the United States with an artificial neural network (NN). We developed an NN model to forecast the U.S. natural gas supply to 2020. Our results indicate that the U.S. will maintain its 1999 production of natural gas until 2001, after which production increases. The network model indicates that natural gas production will increase by an average rate of 0.5%/yr from 2002 to 2012. This increase will more than double from 2013 to 2020. The NN was developed with a large initial pool of input parameters. The input pool included exploratory, drilling, production, and econometric data. Preprocessing the input data involved normalization and functional transformation. Dimension-reduction techniques and sensitivity analysis of input variables were used to reduce redundant and unimportant input parameters and to simplify the NN. The remaining parameters included data from gas exploratory wells, oil/gas exploratory wells, oil exploratory wells, gas depletion rate, proved reserves, gas wellhead prices, and growth rate of the gross domestic product. The three-layer NN was successfully trained with yearly data from 1950 to 1989 using the quick-propagation learning algorithm. The NN's target output is the production rate of natural gas. The agreement between predicted and actual production rates was excellent. A test set not used to train the network and containing data from 1990 to 1998 was used to verify and validate the network prediction performance. Analysis of the test results showed that the NN approach provides an excellent match with actual gas production data. An econometric approach, called stochastic modeling or time-series analysis, was used to develop forecasting models for NN input parameters. A comparison of forecasts between this study and another is presented. The NN model has use as a short-term as well as a long-term predictive tool for natural gas supply. The model can also be used to quantitatively examine the effects of the various physical and economic factors on future gas production.

In this paper, a multi-product, multi-period, multi-site supply chain production and transportation planning problem under customer demand uncertainty is considered. The problem is modelled using a multi-stage stochastic programming model taking into account the production amount, the inventory and backorder levels as well as the quantity of products to be transported between the different plants and customers in each period. Risk management is also addressed by incorporating a risk metric into the stochastic programming model which leads to a multi-objective optimisation model. The objective aims simultaneously to maximise the expected profit as well as the worst case profit. A real example from textile and apparel industry is studied in order to illustrate the effectiveness of the proposed model and the robustness of the supply chain planning solutions.

A branch-and-price algorithm for the robust single-source capacitated facility location problem under demand uncertainty

Using pure hydrogen or hydrogen/natural gas blends in gas-fired power plants poses a lower carbon footprint. This paper evaluates replacing natural gas with hydrogen/natural gas blends in existing power plants. Five gas-fired power plants were evaluated. For a comprehensive evaluation, these power plants were selected in different countries: Australia, Denmark, Germany, UK, and US. Energy, exergy, and economic analysis were applied to depict the implications of the various blends. The simulation was performed using EBSILON Professional software. The results demonstrate the following advantages: lower carbon emissions and higher energy and exergy efficiencies keeping the net power output constant. However, NOx emissions and the volumetric flowrate of the fuel (hydrogen/natural gas blends) increased drastically, i.e., by nearly 16% with the introduction of 20 vol%H2. This affects to design parameters of the gas-fired power plants. The introduction of hydrogen into natural gas affects the levelized cost of fuel. However, it depends on the price disparity between hydrogen and natural gas. The main technological and economic constraints of using hydrogen/natural gas blends in existing gas-fired power plants are assessed in this paper as well.

In assessing a committee's estimates of our natural gas reserves, as in evaluating an inventory of stock in the larder, we must know which system was used. Did they count only the labeled cans? did they include also the fruit on the vines? or did they add a little more for the seeds in the packet and the pictures in the catalog? packet and the pictures in the catalog? There is a shortage of natural gas in the United States. This is the consensus of experts in industry, financial institutions and government bureaus who study this clean fuel that provides one-third of our energy needs. Recent investigations have demonstrated the accuracy of the present methods of estimating natural gas reserves. But there are still critics of the gas industry who suspect that the natural gas producers might be hiding some of their reserves. They complain that natural gas figures are reported by industry-oriented committees. The figures, they say, are based upon secret information locked in company files and the consumers and government agencies have access to only a minimum of information. Furthermore, the figures are so conservative they scare the consumer to death. Since 1945, proved reserves have been compiled and reported by the American Gas Association (AGA) Committee on Natural Gas Reserves, a committee of more than 100 geologists and engineers. Since 1963, the Potential Gas Committee, a committee composed of about 150 geologists and engineers and sponsored by the Colorado School of Mines, has estimated the potential or undiscovered supply of natural gas in the U. S. Hidden Reserves - The Figment Any charge that the industry is hiding natural gas reserves implies that the AGA proved reserves committee has not been doing its job. Natural gas experts argue that even without a check of the AGA committee's figures, complaints of a "rigged shortage" can be proved to be unwarranted. It has been shown that the gas shortage is the direct result of a decline in drilling wells. The Potential Gas Committee has reported enormous supplies Potential Gas Committee has reported enormous supplies of natural gas waiting to be discovered. Proved additions to natural gas reserves per foot of hole drilled were as high in 1970 as in 1960. The problem is that the footage of hole drilled has declined drastically. John D. Emerson, an energy economist with the Chase Manhattan Bank, has pointed out that the reason for the drilling slump is that "between 1960 and 1970 the industry's exploration and development expenditures per foot drilled rose by over 50 percent. During this period crude oil prices, which provide the bulk of the industry's revenue, rose by 9 percent Natural gas prices rose faster, but gas prices were so depressed in 1960 that natural gas provided only 5 percent of the industry's revenue. percent of the industry's revenue. The Federal Power Commission (FPC) has investigated the charge that gas reserves were being hidden by the producers in southern Louisiana. It checked the USGS records and the records of the Louisiana Conservation Dept. The gas producers in the South Louisiana area allowed the FPC to examine their normally confidential information. Result: The FPC confirmed the accuracy of the reserves reported and found no hidden reserves. But this has not satisfied the critics. In Dec., 1971, the FPC announced a new, massive survey to cover gas reserves as of year-end 1970. P. 531

An analysis of industrial demand for natural gas

In this paper we discuss the real options valuation of investments in flexible power plants. After the energy supply crisis lived in 2001, new investments in gas fired power plants were made to increase electricity generation in the short term, due to the reduced maturity time of these investments. More recently, the nationalization of the Bolivian natural gas reserves raised uncertainties over the prices and supply of this commodity. First we analyze an operating power plant which can switch fuels among natural gas and oil. Second, we study the option to temporarily shut down the plant. Finally, we assess the interaction between these two flexibilities. Valuation involves the use of two quadranomial trees, supporting co rrelated GBM for the fuel prices.

Simulation modeling combined with decision control can offer important benefits for analysis, design, and operation of semiconductor supply-chain network systems. Detailed simulation of physical processes provides information for its controller to account for (expected) stochasticity present in the manufacturing processes. In turn, the controller can provide (near) optimal decisions for the operation of the processes and thus handle uncertainty in customer demands. In this paper, we describe an environment that synthesizes discrete-event system specification (DEVS) with model predictive control (MPC) paradigms using a knowledge interchange broker (KIB). This environment uses the KIB to compose discrete event simulation and model predictive control models. This approach to composability affords flexibility for studying semiconductor supply-chain manufacturing at varying levels of detail. We describe a hybrid DEVS/MPC environments via a knowledge interchange broker. We conclude with a comparison of this work with another that employs the Simulink/MATLAB environment.