Stochastic optimization model for coordinated operation of natural gas and electricity networks

Renewable energy sources will anticipate significantly in the future energy system paradigm due to their low cost of operation and low pollution. Considering the renewable generation (e.g., wind) intermittency, flexible gas-fired power plants will continue to play their essential role as the main linkage of natural gas and electricity networks, and hence coordinated operation of these networks is beneficial. Furthermore, uncertainty is always found in gas demand prediction, electricity demand prediction, and output power of wind generation. Therefore, in this paper, a two-stage stochastic model for operation of natural gas and electricity networks is implemented. In order to model uncertainty in these networks, Monte Carlo simulation is applied to generate scenarios representing the uncertain parameters. Afterwards, a scenario reduction algorithm based on distances between the scenarios is applied. Stochastic and deterministic models for natural gas and electricity networks are optimized and compared considering integrated and iterative operation strategies. Furthermore, the value of flexibility options (i.e., electricity storage systems) in dealing with uncertainty is quantified. A case study is presented based on a high pressure 15-node gas system and the IEEE 24-bus reliability test system to validate the applicability of the proposed approach. The results demonstrate that applying the stochastic model of gas and electricity networks as well as considering integrated operation strategy in the presence of flexibility provides different benefits (e.g., 14% cost savings) and enhances the system reliability in the case of contingency

Impact of local emergency demand response programs on the operation of electricity and gas systems

With increasing attention to climate change, the penetration level of renewable energy sources (RES) in the electricity network is increasing. Due to the intermittency of RES, gas-fired power plants could play a significant role in backing up the RES in order to maintain the supply–demand balance. As a result, the interaction between gas and power networks are significantly increasing. On the other hand, due to the increase in peak demand (e.g., electrification of heat), network operators are willing to execute demand response programs (DRPs) to improve congestion management and reduce costs. In this context, modeling and optimal implementation of DRPs in proportion to the demand is one of the main issues for gas and power network operators. In this paper, an emergency demand response program (EDRP) is implemented locally to reduce the congestion of transmission lines and gas pipelines more efficiently. Additionally, the effects of optimal implementation of local emergency demand response program (LEDRP) in gas and power networks using linear and non-linear economic models (power, exponential and logarithmic) for EDRP in terms of cost and line congestion and risk of unserved demand are investigated. The most reliable demand response model is the approach that has the least difference between the estimated demand and the actual demand. Furthermore, the role of the LEDRP in the case of hydrogen injection instead of natural gas in the gas infrastructure is investigated. The optimal incentives for each bus or node are determined based on the power transfer distribution factor, gas transfer distribution factor, available electricity or gas transmission capability, and combination of unit commitment with the LEDRP in the integrated operation of these networks. According to the results, implementing the LEDRP in gas and power networks reduces the total operation cost up to 11% and could facilitate hydrogen injection to the network. The proposed hybrid model is implemented on a 24-bus IEEE electricity network and a 15-bus gas network to quantify the role and value of different LEDRP models

Investing in flexibility in an integrated planning of natural gas and power systems

The growing interdependencies between natural gas and power systems, driven by gas-fired generators and gas compressors supplied by electricity, necessitates detailed investigation of the interactions between these vectors, particularly in the context of growing penetration of renewable energy sources. In this research, an expansion planning model for integrated natural gas and power systems is proposed. The model investigates optimal investment in flexibility options such as battery storage, demand side response, and gas-fired generators. The value of these flexibility options is quantified for gas and electricity systems in GB in 2030. The results indicate that the flexibility options could play an important role in meeting the emission targets in the future. However, the investment costs of these options highly impact the future generation mix as well as the type of reinforcements in the natural gas system infrastructure. Through deployment of the flexibility options up to £24.2b annual cost savings in planning and operation of natural gas and power systems could be achieved, compared to the case that no flexibility option is considered

Techno-economic assessment of battery storage and Power-to-Gas: A whole-system approach

The power systems in many countries are undergoing a radical transformation through employing a large capacity of renewable generation technologies such as wind turbine and solar photovoltaic. The power generation by wind and solar resources are variable and difficult to predict. Therefore, growing capacities of such technologies is expected to introduce challenges regarding balancing electricity supply and demand. This paper investigates the role of battery storage and power-to-gas systems to accommodate large capacity of intermittent power generation from wind and solar and therefore facilitates matching electricity supply and demand. The Combined Gas and Electricity Networks (CGEN) model was used to optimize the operation of gas and electricity networks in GB for typical weeks in winter and summer in 2030. The role of different capacity of battery storage and power-to-gas systems in reducing the wind curtailment and operating cost of the system were quantified and compared with the annualized cost of these technologies

Coordinated operation of gas and electricity systems for flexibility study

The increase interdependencies between electricity and gas systems, driven by gas-fired power plants and gas electricity-driven compressors, necessitates detailed investigation of such interdependencies, especially in the context of increased share of renewable energy sources. 6 In this paper, the value of an integrated approach for operating gas and electricity systems is assessed. An outer approximation with equality relaxation (OA/ER) method is used to deal with the optimization class of mixed integer non-linear problem of integrated operation of gas and electricity systems. This method significantly improved the efficiency of the solution algorithm and achieved nearly 40% reduction in computation time compared to successive linear programming. The value of flexibility technologies including flexible gas compressors, demand side response, battery storage, and power-to-gas is quantified in the operation of integrated gas and electricity systems in GB 2030 energy scenarios for different renewable generation penetration levels. The modeling demonstrates that the flexibility options will enable significant cost savings in the annual operational costs of gas and electricity systems (up to 21%). On the other hand, the analysis carried out indicates that deployment of flexibility technologies support appropriately the interaction between gas and electricity systems

The role of inhalational anesthetic drugs in patients with hepatic dysfunction: A review article

Context: Anesthetic drugs including halogenated anesthetics have been common for many years. Consequent hepatic injury has been reported in the literature. The mechanism of injury is immunoallergic. The first generation drug was halothane; it had the most toxicity when compared to other drugs. The issue becomes more important when the patient has an underlying hepatic dysfunction. Evidence Acquisition: In this paper, reputable internet databases from 1957�2014 were analyzed and 43 original articles, 3 case reports, and 3 books were studied. A search was performed based on the following keywords: inhalational anesthesia, hepatic dysfunction, halogenated anesthetics, general anesthesia in patients with hepatic diseases, and side effects of halogenated anesthetics from reliable databases. Reputable websites like PubMed and Cochrane were used for the searches. Results: In patients with hepatic dysfunction in addition to hepatic system and dramatic hemostatic dysfunction, dysfunction of cardiovascular, renal, respiratory, gastrointestinal, and central nervous systems may occur. On the other hand, exposure to inhalational halogenated anesthetics may have a negative impact (similar to hepatitis) on all aforementioned systems in addition to direct effects on liver function as well as the effects are more pronounced in halothane. Conclusions: Despite the adverse effects of inhalational halogenated anesthetics (especially halothane) on hepatic patients when necessary. The effects on all systems must be considered and the necessary preparations must be provided. These drugs are still used, if necessary, due to the presence of positive effects and advantages mentioned in other studies as well as the adverse effects of other drugs. © 2015, Iranian Society of Regional Anesthesia and Pain Medicine (ISRAPM)

A fuzzy-logic-based control methodology for secure operation of a microgrid in interconnected and isolated modes

Due to the global concerns regarding the climate change, integration of renewable energy sources is considered as a mitigation approach in electric power generation. This requires advanced frequency and voltage control methodologies to overcome the challenges especially in microgrids. This paper presents a 2-step frequency and voltage control methodology for microgrids with high penetration of variable renewable energy sources. An optimized Proportional-Integral controller is designed for a Superconductor Magnetic Energy Storage System to minimize the transient frequency deviations. In cases that the Superconductor Magnetic Energy Storage System cannot stabilize the microgrid frequency in the isolated mode, the microgrid controller activates the next level of the frequency control. In the second level, an intelligent fuzzy-logic frequency controller is designed to adjust controllable loads, controllable generation units as well as perform load shedding. In the interconnected mode, the microgrid controller is able to activate the second level to contribute to the system frequency control. Finally, an intelligent fuzzy-logic voltage controller, realized through distribution static synchronous compensator, is devised to control the voltage magnitude of the main feeders of the microgrid. In this work, a real-time operation algorithm for frequency as well as voltage control is proposed and has been tested by set of simulations on a low voltage benchmark network

Survey of educational drop-out indexes and its related factors in alumni of paramedical faculty of Kashan Medical University

BACKGROUND AND OBJECTIVE: Educational dropout is one of the problems of educational system. The educational drop-out prevention and its complications require recognition of the probability risk factors. So, this study is carried out in order to assess the indexes of educational drop-out and its related factors in alunmi of paramedical faculty of Kashan medical University, Iran. METHODS: This cross-sectional study was performed on the entire alunmi from 1990-2003 (n=1439). The questionnaire including probability related factors and the indexes of educational drop-out (probation, unacceptable total average, lesson repeating, major changing, withdrawing, ejection from university, education leaving and delay in graduating) was used. FINDINGS: Prevalence of probation, unacceptable total average and delay in graduating were 9.2 (n=133), 14.5 (n=209), and 14.1 (n=203), respectively. The utmost probation frequency was related to first and then second semester. Delay duration was only one semester in 152 (10.56). 413 (28.7) had repeated lesson that 227 (15.8) had repeated only one lesson. Prevalence of major changing, withdrawing, ejection from university and education leaving were 2 (n=29), 0.9 (n=13), 0.4 (n=6), and 0.6 (n=9), respectively. There was an association between demographic data, prior educational status, and admission criteria with academic drop-out. CONCLUSION: With attention to the considerable prevalence of educational drop-out and its risk factors, diagnosing and supporting of the vulnerable students is a must

Climate finance and disclosure for institutional investors: why transparency is not enough

The finance sector’s response to pressures around climate change has emphasized disclosure, notably through the recommendations of the Financial Stability Board’s Task Force on Climate-related Financial Disclosures (TCFD). The implicit assumption—that if risks are fully revealed, finance will respond rationally and in ways aligned with the public interest—is rooted in the “efficient market hypothesis” (EMH) applied to the finance sector and its perception of climate policy. For low carbon investment, particular hopes have been placed on the role of institutional investors, given the apparent matching of their assets and liabilities with the long timescales of climate change. We both explain theoretical frameworks (grounded in the “three domains”, namely satisficing, optimizing, and transforming) and use empirical evidence (from a survey of institutional investors), to show that the EMH is unsupported by either theory or evidence: it follows that transparency alone will be an inadequate response. To some extent, transparency can address behavioural biases (first domain characteristics), and improving pricing and market efficiency (second domain); however, the strategic (third domain) limitations of EMH are more serious. We argue that whilst transparency can help, on its own it is a very long way from an adequate response to the challenges of ‘aligning institutional climate finance’

Techno-economic assessment of energy storage systems in multi-energy microgrids utilizing decomposition methodology

Renewable resources and energy storage systems integrated into microgrids are crucial in attaining sustainable energy consumption and energy cost savings. This study conducts an in-depth analysis of diverse storage systems within multi-energy microgrids, including natural gas and electricity subsystems, with a comprehensive focus on techno-economic considerations. To achieve this objective, a methodology is developed, comprising an optimization model that facilitates the determination of optimal storage system locations within microgrids. The model considers various factors, such as operating and emission costs of both gas and electricity subsystems, and incorporates a sensitivity analysis to calculate the investment and maintenance costs associated with the storage systems. Due to the incorporation of voltage and current relations in the electricity subsystem as well as gas pressure and flow considerations in the natural gas subsystem, the developed model is classified as a mixed-integer nonlinear programming model. To address the inherent complexity in solving, a decomposition approach based on Outer Approximation/Equality Relaxation/Augmented Penalty is developed. This study offers scientific insights into the costs of energy storage systems, potential operational cost savings, and technical considerations of microgrid operation. The results of the developed decomposition approach demonstrate significant advantages, including reduced solving time and a decreased number of iterations