Operation Of Gas Networks Research Articles

The Role of Flexibility in the Integrated Operation of Low-Carbon Gas and Electricity Systems: A Review

The integration of gas and electricity networks has emerged as a promising approach to enhance the overall flexibility of energy systems. As the transition toward sustainable and decarbonized energy sources accelerates, the seamless coordination between electricity and gas infrastructure becomes increasingly crucial. This paper presents a comprehensive review of the state-of-the-art research and developments concerning the flexibility in the operation of low-carbon integrated gas and electricity networks (IGENs) as part of the whole system approach. Methods and solutions to provide and improve flexibility in the mentioned systems are studied and categorized. Flexibility is the system’s ability to deal with changes and uncertainties in the network while maintaining an acceptable level of reliability. The presented review underscores the significance of this convergence in facilitating demand-side management, renewable energy integration, and overall system resilience. By highlighting the technical, economic, and regulatory aspects of such integration, this paper aims to guide researchers, policymakers, and industry stakeholders toward effective decision-making and the formulation of comprehensive strategies that align with the decarbonization of energy systems.

Optimization of a gas network fuel consumption with genetic algorithm

In this paper genetic algorithm (GA) was used for the optimization of two natural gas network, the study focuses on fuel consumption minimization of the second gas network. Studies using GA to simultaneously optimize a gas network and a compressor station based on the constraint of the gas network and compressor station are limited. The relationship between several compressor speed and the total fuel consumption and the relationship between the sum of pressure drop in compressor station loops and compressor inlet flow are assessed for optimization. For this purpose, the optimization of two networks was presented and the results were compared with result from analytical methods. The first network problem was to determine the flow rates and node pressures under a given load, which serves as a guide in using GA. Comparison with result from analytical solution showed good agreement of predicted values. The second network consisted of two compressor stations, each containing six compressors with the objective to optimize the fuel consumption of the system. The simulation was divided into two main simulations, the first simulation was the flow optimization, which results in the optimum flow, based on the fitness function, which is the summation of pressure loss for each compressor station. In the second simulation which was the speed optimization, the optimum set of compressor speed was obtained which depends on the fitness function, which is the minimum fuel consumption, the flow obtained from the flow optimization served as input and remained constant. All speeds were simulated together. The predicted results were compared with literature and showed GA can be used for compressor station fuel optimization but still requires improvement. Based on the outcomes, data on natural gas network operations should be accessible to encourage studies on fuel consumption and CO2 emissions minimization.

Multi-stage linear decision rules for stochastic control of natural gas networks with linepack

The disturbances from variable and uncertain renewable generation propagate from power systems to natural gas networks, causing gas network operators to adjust gas supply nominations to ensure operational security. To alleviate expensive supply adjustments, we develop control policies to leverage instead the flexibility of linepack – the gas stored in pipelines – to balance stochastic gas extractions. These policies are based on multi-stage linear decision rules optimized on a finite discrete horizon to guide controllable network components, such as compressors and valves, towards feasible operations. Our approach offers several control applications. First, it treats the linepack as a main source of flexibility to balance disturbances from power systems without substantial impacts on nominal gas supply. Second, these policies can be optimized to minimize the variability (due to intermittency of renewables) and variance (due to their uncertainty) of network state variables, such as pressures. Finally, it enables topology optimization to decouple network parts and prevent uncertainty propagation through the network. This is demonstrated using illustrative numerical experiments.

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.

Finite‐difference‐based simulation and adjoint optimization of gas networks

The stable operation of gas networks is an important optimization target. While for this task commonly finite volume methods are used, we introduce a new finite difference approach. With a summation by part formulation for the spatial discretization, we get well‐defined fluxes between the pipes. This allows a simple and explicit formulation of the coupling conditions at the node. From that, we derive the adjoint equations for the network simply and transparently. The resulting direct and adjoint equations are numerically efficient and easy to implement.

Robust Flexible Unit Commitment in Network-Constrained Multicarrier Energy Systems

The coordinated operation of different energy systems, such as electrical, gas, and heating, can improve the efficiency of the whole energy system and facilitate the larger penetration of renewable energy resources in the electricity generation portfolio. However, appropriate models considering various technical constraints of the energy carriers (e.g., gas system pressure limit and heat losses in the district heating networks) are needed to effectively assess the true impact of integrated energy system (IES) operation on the overall system’s performance. This article proposes a flexible unit commitment (UC) problem for coordinated operation of electricity, natural gas, and district heating networks, called multicarrier network-constrained unit commitment (MNUC), to minimize the operation cost of the IES. Besides, an integrated demand response (IDR) program is considered as a promising solution to improve consumers’ electricity, gas, and heat consumption patterns and to increase the power dispatch of combined heat and power units. Multienergy storage systems are also included in the proposed model to decrease the impact of multienergy network constraints on the overall system’s performance. To model the uncertainties involved in the operation of the three networks, a combined robust/stochastic approach is preferred in the MNUC problem considering multicarrier energy storage systems and the IDR program. Numerical results show that the whole operation cost of the IES has decreased by 2.58% considering the IDR program and multienergy storage systems.

Will blue hydrogen lock us into fossil fuels forever?

Will blue hydrogen lock us into fossil fuels forever?

Multi-stage robust optimization of a multi-energy coupled system considering multiple uncertainties

As an effective means to improve the efficient use of energy, multi-energy coupled systems have indicated the important direction for the development of Energy Internet in the foreseeable future. However, the uncertainties that exist in various energy networks present severe challenges to the implementation of this innovative system. In this regard, this paper proposed a multi-stage robust optimization model for the coordinated operation of an electricity-gas-transportation coupled system, which simultaneously considered the uncertainties of traffic demands, wind power, and gas fuel consumption by gas-fired units. To conform to the non-anticipative sequential decision-making process for power system scheduling, the multi-stage robust unit commitment (UC) problem was established and considered as the master problem, which was solved by introducing a linear affine rule and the robust counterpart method. The gas network operation feasibility checks in each period were then addressed as the subproblems, and the generalized benders decomposition-based decoupling-coordination strategy was developed to solve the above master-subproblems iteratively. Simulation results demonstrate that the proposed multi-stage robust UC model can achieve a scheduling solution with superior economic performance and reduced conservativeness compared to the two-stage robust UC model. Furthermore, the effectiveness of the decoupling-coordination solving strategy was verified for the multi-energy coupled system.

Coordinated Operation of Electricity and Natural Gas Networks with Consideration of Congestion and Demand Response

This work presents a new coordinated operation (CO) framework for electricity and natural gas networks, considering network congestions and demand response. Credit rank (CR) indicator of coupling units is introduced, and gas consumption constraints information of natural gas fired units (NGFUs) is given. Natural gas network operator (GNO) will deliver this information to an electricity network operator (ENO). A major advantage of this operation framework is that no frequent information interaction between GNO and ENO is needed. The entire framework contains two participants and three optimization problems, namely, GNO optimization sub-problem-A, GNO optimization sub-problem-B, and ENO optimization sub-problem. Decision sequence changed from traditional ENO-GNO-ENO to GNO-ENO-GNO in this novel framework. Second-order cone (SOC) relaxation is applied to ENO optimization sub-problem. The original problem is reformulated as a mixed-integer second-order cone programming (MISOCP) problem. For GNO optimization sub-problem, an improved sequential cone programming (SCP) method is applied based on SOC relaxation and the original sub-problem is converted to MISOCP problem. A benchmark 6-node natural gas system and 6-bus electricity system is used to illustrate the effectiveness of the proposed framework. Considering pipeline congestion, CO, with demand response, can reduce the total cost of an electricity network by 1.19%, as compared to −0.48% using traditional decentralized operation with demand response.

Electrical and gas networks coupling through hydrogen blending under increasing distributed photovoltaic generation

Electricity and gas infrastructure coupling has the twofold effect of solving production-consumption mismatches and decarbonizing the natural gas system through power-to-gas technologies producing hydrogen to be injected within the gas network. However, little is known on how this may impact the gas network operation, especially at a local level. This paper aims to fill this gap by presenting a methodology for modeling the interactions between electricity and gas distribution networks through the implementation of their physical models. A scenario of increasing penetration of distributed photovoltaic production is considered for a sample urban area. Whenever photovoltaic production exceeds the urban area consumption, hydrogen is produced and injected into the gas network. 24 injection scenarios were examined and compared to evaluate their impacts on fluid-dynamics and the quality of gas blends. Results show possible bottlenecks against hydrogen injection caused by the gas network. During summertime operations and in the cases of injection following directly the solar over-production, the hydrogen share peaks 20–30% already in the scenario of 40% solar penetration, generating unacceptable blends. These gas quality perturbations are considerably reduced when hydrogen is injected constantly throughout the day. The choice of the injection node also contributes to perturbation reduction. Sector coupling through hydrogen blending results in a complex interplay between renewable energy excess and local gas network availability which can be enhanced by buffer storage solutions and proper choice of injection node. In the framework of integrated and multi-gas systems, combined simulation tools are necessary to evaluate sector-coupling opportunities case-by-case.

Stochastic framework for day-ahead scheduling of coordinated electricity and natural gas networks considering multiple downward energy hubs

The integrated operation of electricity and gas networks in the presence of downward energy hub networks leads to the development of smarter and more environment-friendly networks. This paper presents an optimal model for the day-ahead scheduling of electricity and natural gas networks by considering three downward energy hubs and a power-to-gas system (P2G). The system studied in this paper consists of a 33-bus distribution electricity network and a 14-node gas network. Moreover, the uncertainties of the electrical, cooling, heating loads, the renewable energy sources (RES's) output power, and price are taken into account to study their effects on the scheduling results. In the proposed model, first, each hub performs its optimal day-ahead scheduling and sends it to the ISO. Afterward, the ISO performs the scheduling of electricity and natural gas networks considering the optimal schedule of each hub. The final problem is modeled as a mixed-integer non-linear programming (MINLP) problem and is solved using the DICOPT solver in GAMS software. According to our analysis of the results, the proposed model reduces the operation costs by 5.1 and 4.8 percent in the deterministic and stochastic modes, respectively. Moreover, our analysis of the results in the contingent event reflects the loss of about 1429kW of the load in the absence of the P2G system.

Investigation of the Multi-Point Injection of Green Hydrogen from Curtailed Renewable Power into a Gas Network

Renewable electricity can be converted into hydrogen via electrolysis also known as power-to-H2 (P2H), which, when injected in the gas network pipelines provides a potential solution for the storage and transport of this green energy. Because of the variable renewable electricity production, the electricity end-user’s demand for “power when required”, distribution, and transmission power grid constrains the availability of renewable energy for P2H can be difficult to predict. The evaluation of any potential P2H investment while taking into account this consideration, should also examine the effects of incorporating the produced green hydrogen in the gas network. Parameters, including pipeline pressure drop, flowrate, velocity, and, most importantly, composition and calorific content, are crucial for gas network management. A simplified representation of the Irish gas transmission network is created and used as a case study to investigate the impact on gas network operation, of hydrogen generated from curtailed wind power. The variability in wind speed and gas network demands that occur over a 24 h period and with network location are all incorporated into a case study to determine how the inclusion of green hydrogen will affect gas network parameters. This work demonstrates that when using only curtailed renewable electricity during a period with excess renewable power generation, despite using multiple injection points, significant variation in gas quality can occur in the gas network. Hydrogen concentrations of up to 15.8% occur, which exceed the recommended permitted limits for the blending of hydrogen in a natural gas network. These results highlight the importance of modelling both the gas and electricity systems when investigating any potential P2H installation. It is concluded that, for gas networks that decarbonise through the inclusion of blended hydrogen, active management of gas quality is required for all but the smallest of installations.

Influence of increased content of selected sulfur compounds on the response of the THT detector used in ANAT-M analyzers

Proper and systematic control of the odorization process is a basic condition for ensuring public safety in the distribution and use of gaseous fuels and for the continuity of the process. Maintaining a constant level of gas odorization requires gas network operators to constantly monitor the odorizing process. The control is carried out, among others by measuring the concentration of odorant in the gas. This is an important and inseparable element of controlling the degree of odorization of gaseous fuels, aimed at controlling the operation of odorizing devices by verifying the dose of odorizing agent or controlling the composition of gaseous fuel at any point of the gas distribution network. The correctness of uninterrupted control of the degree of gas odorization depends on the availability and quality of measuring instruments. The only process chromatographic analyzer intended for continuous measurement of the odorant concentration in gaseous fuels used on a national scale is the ANAT-M analyzer. Since this device works under process conditions, not supervised by an analyst, it is extremely important to recognize the restrictions on the correctness of its indications resulting from the presence of certain compounds in the gas. The article presents the analysis of observations and results of analyzes regarding the impact of selected sulfur compounds and other components of high-methane natural gas on the response of the THT detector currently used in ANAT-M analyzers. The significance of this influence for the quality of obtained THT concentration measurement results was determined. Gases containing sulfur compounds that may be present in the network gas, such as hydrogen sulfide, methyl mercaptan, dimethyl sulfide, as well as network gas containing the addition of LNG and biogas gases were tested. The obtained test results were analyzed in terms of determining the magnitude of the impact of the tested parameters on the precision of measurements performed with the ANAT-M analyzer.

Distributed Multi-Energy Operation of Coupled Electricity, Heating, and Natural Gas Networks

This article proposes a distributed multi-period multi-energy operational model for the multi-carrier energy system. In this model, energy hubs function as distributed decision-makers and feature the synergistic interactions of generation, delivery, and consumption of coupled electrical, heating, and natural gas energy networks. The multi-period multi-energy scheduling is a challenging optimization problem due to its strong couplings and inherent nonconvexities within the multi-energy networks. The original problem is thus reformulated as a mixed integer second-order cone programming (MISOCP) and subsequently solved with a sequential second-order cone programming (SOCP) approach to guarantee a satisfactory convergence performance. Furthermore, a fully-distributed consensus-based alternating direction method of multipliers (ADMM) approach with only neighboring information exchange required is developed to optimize the multi-energy flows while considering the local energy-autonomy of heterogeneous energy hubs. The proposed methodology is performed and benchmarked on a four-hub urban multi-energy system over a 24 hourly scheduling periods. Simulation results demonstrated the superiority of the proposed scheme in system operational economy and renewable energy utilization, and also verify the effectiveness of the proposed distributed approach.

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.

A Method of Optimal Malfunction Management in Urban Natural Gas Transmission and Distribution Systems

Given the increasing number of urban natural gas transmission and distribution systems, it is particularly crucial to optimize the management of natural gas operations, especially when equipment failure or pipeline leakage occurs in the supply system. To meet the needs of customers for natural gas, in this paper, we considered two cases of pipeline rupture leakage and pressure regulation station failure for different supply areas. We combined natural gas supply pipelines, pressure regulating stations and a gasholder station to establish a failure optimization management model and used genetic algorithms and one-dimensional fluid dynamics models for optimization management and proposed the following two solutions: 1. Complete operation strategy: modify both the pressure of the pressure regulating station and the air supply volume of the gasholder station; 2. Partial operation strategy: modify the pressure of the pressure regulating station only, and keep the supply volume of the gasholder station constant. Finally, our model is applied to an urban natural gas transmission and distribution system. Based on the actual results, failure optimization management is proposed according to the location and the type of failure and constructive options are suggested for the operation of natural gas networks.

Natural Gas Flow Solvers Using Convex Relaxation

The vast infrastructure development, gas flow (GF) dynamics, and complex interdependence of gas with electric power networks call for advanced computational tools. Solving the equations relating gas injections to pressures and pipeline flows lies at the heart of natural gas network (NGN) operation, yet existing solvers that require careful initialization and uniqueness has been an open question. In this context, this article considers the nonlinear steady-state version of the GF problem. It first establishes that the solution to the GF problem is unique under arbitrary NGN topologies, compressor types, and sets of specifications. For GF setups where pressure is specified on a single (reference) node and compressors do not appear in cycles, the GF task is posed as n convex minimization. To handle more general setups, a GF solver relying on a mixed-integer quadratically constrained quadratic program (MI-QCQP) is also devised. This solver can be used for any GF setup at any NGN. It introduces binary variables to capture flow directions, relaxes the pressure drop equations to quadratic inequality constraints, and uses a carefully selected objective to promote the exactness of this relaxation. The relaxation is probably exact in NGNs with nonoverlapping cycles and a single fixed-pressure node. The solver handles efficiently the involved bilinear terms through McCormick linearization. Numerical tests validate our claims, demonstrate that the MI-QCQP solver scales well, and that the relaxation is exact even when the sufficient conditions are violated, such as in NGNs with overlapping cycles and multiple fixed-pressure nodes.

A Statistical Learning-Based Algorithm for Topology Verification in Natural Gas Networks Based on Noisy Sensor Measurements

Accurate knowledge of natural gas network topology is critical for the proper operation of natural gas networks. Failures, physical attacks, and cyber attacks can cause the actual natural gas network topology to differ from what the operator believes to be present. Incorrect topology information misleads the operator to apply inappropriate control causing damage and lack of gas supply. Several methods for verifying the topology have been suggested in the literature for electrical power distribution networks, but we are not aware of any publications for natural gas networks. In this paper, we develop a useful topology verification algorithm for natural gas networks based on modifying a general known statistics-based approach to eliminate serious limitations for this application while maintaining good performance. We prove that the new algorithm is equivalent to the original statistics-based approach for a sufficiently large number of sensor observations. We provide new closed-form expressions for the asymptotic performance that are shown to be accurate for the typical number of sensor observations required to achieve reliable performance.

Research on energy efficiency of operation of city gas networks

The task of choosing the criterion of energy efficiency of operation of city gas networks of high and medium pressure, under the condition of transition to the system of individual energy supply is set and solved. It is shown
 that in conditions of substantial increase of prices for natural gas and deepening of its deficit, the city gas network is often not able to provide consumers with energy in a given volume, so the approach to forecasting its operating modes should fundamentally change. First of all it concerns the field of permissible modes, which in such conditions considerably expands. Given the reloading of the gas distribution network as a result of changing the nature of gas consumption, a large role is given to the criteria for energy efficiency of gas transportation and to ensure maximum operational reliability while being within the scope of optimal maintenance.
 In order to assess the energy efficiency of gas transportation by gas pipelines of a distribution network, it is suggested to use the notion of the net efficiency coefficient, which is determined by the ratio of useful work performed when providing a given volume of gas transportation by pipelines to total energy consumption. It is shown that the efficiency of the distribution network or its individual elements differs fundamentally from the coefficient of its hydraulic efficiency, which is a characteristic of the technical state of the system. On the basis of analytical studies, the correlation between them is established.
 Calculated dependencies are proposed for determining the coefficient of hydraulic efficiency of a branched gas pipeline as an element of an urban gas distribution network. The influence of various factors on the value of the coefficient of hydraulic efficiency of the urban gas distribution network has been analyzed. The examples of calculating the efficiency of the network are given, conclusions on improving the efficiency of operation are made.

Analysis of the Safety of Functioning Gas Pipelines in Terms of the Occurrence of Failures

The development of appropriate methods by which to assess the functioning of gas pipelines helps limits the consequences of disasters, in that way protecting users better. Assessment methods of this kind are presented in this paper, which advocates the integrated risk area identification method. The risk taken account of is understood to be a function of the probability or frequency of occurrence of undesirable events, and comes with parameters defining the consequences of these events, should they arise, in terms of their magnitude. The level of system vulnerability to events of these types is a factor considered, and the risk calculation is of a kind that encompasses both quantitative and qualitative aspects. The approach taken is regarded as a quick and simple risk-assessment tool applicable to the daily operation of gas networks for a gas company. Specifically, the framework of the research carried out extends to: (1) Estimation of the average cost of failure of gas pipelines in the case of an urban agglomeration in SE Poland; (2) assessment of the level of integrated risk facing the gas-supply subsystem, by reference to the risk area identification method; (3) failure forecasting by way of regressions with delay; and (4) conclusions regarding failure risk assessment in a gas-supply network, as well as a consideration of prospects. The framework referred here, thus constitutes the basis for both analysis and assessment of the safety of a gas-supply system.