Electricity Gas Systems Research Articles

Measurement configuration for integrated electric–gas systems via observability analysis considering gas flow dynamics

AbstractState estimation plays an important role in the monitoring and control of integrated electric–gas systems (IEGSs), but it faces limitations due to insufficient measurement configurations and low data redundancy in these systems; additional measurement configurations are needed to increase the overall system observability. Owing to the lack of suitable observability analysis methods, optimal measurement configurations for IEGSs remain underexplored. This paper presents an IEGS observability analysis method that incorporates gas flow dynamics via the Lie derivative. This method incorporates the complex topological structure of the gas network and the dynamic process of gas flow into the IEGS observability analysis. Furthermore, the measurement configuration problem for IEGSs considering gas flow dynamics is formulated as a rank‐constrained optimization problem. To handle the rank constraints effectively, an iterative cutting method is developed with convergence guarantees. Finally, the efficacy and practicality of the proposed methods are validated through case studies of varying scales. The proposed optimal measurement configuration model reduces measurement configuration costs while maintaining system observability.

Techno-economic assessment of Green Hydrogen Production for Blending in the Natural Gas Network

Abstract Increased electricity generation from renewable sources is critical for the transition towards a zero-carbon future. While this growth of production presents challenges in grid management due to inadequate storage systems for surplus electricity, solutions such as green hydrogen production offer promising avenues for integration into existing infrastructure. By leveraging surplus renewable electricity to power electrolyzers and inject green hydrogen into natural gas networks, we take a significant step forward in realizing an integrated gas-electric system. This study delves into this concept by conducting a comprehensive techno-economic assessment of a hydrogen production facility. The initial step is to determine the required volume of hydrogen to achieve a 10% concentration within a real natural gas distribution network. This value is such that the gas mixture remains within the Higher Heating Value (HHV), Wobbe Index (WI) ranges defined by Italian legislation. The goal is to optimize component sizing using a genetic algorithm to minimize the Levelized Cost of Hydrogen (LCOH) while meeting criteria for green hydrogen production. In fact, results show that an input from electricity grid is necessary to meet the hydrogen demand while maintaining the techno-economic feasibility of the system. A sizing optimization is therefore performed on photovoltaic, electrolyzer and storage system. Furthermore, the study underscores the critical role of energy policies, particularly green hydrogen incentives, in determining the economic feasibility of the system. By analyzing their impact on economic revenues, the authors emphasize the importance of supportive regulatory frameworks in driving the transition towards a more sustainable future.

Low carbon economic dispatch of power-gas interconnected systems considering carbon capture technologies

Abstract To address wind power curtailment and high carbon emissions in power systems, this paper proposes a low-carbon economic dispatch model for an electricity-gas system with carbon capture technology. It integrates a carbon storage system, thermal power, wind power, and P2G units, aiming to minimize daily operating costs while adhering to operational constraints. This interconnected approach enhances the system’s low-carbon and economic efficiency.

Low-carbon operation of integrated electricity–gas system with hydrogen injection considering hydrogen mixed gas turbine and laddered carbon trading

Green hydrogen produced by the power-to-gas facilities can be blended into the natural gas system, which is a promising way toward a low-carbon energy system. This paper proposes a laddered carbon trading-based operation model for integrated electricity–gas system with hydrogen injection considering the complex combustion properties of hydrogen mixed gas turbine (HMGT). The power-to-hydrogen, hydrogen methanation, and carbon emission processes are combined with the methane reactor and the flexible carbon capture, utilization and storage facility. Then, a HMGT combustion model based on the system thermodynamics and chemical reaction kinetics is introduced. The piecewise linearization technique is adopted to describe the varying hydrogen production efficiency of electrolysis system. Moreover, an energy balance based quasi-steady-state model to deal with the calorific value problem of the gas mixture is proposed and solved by an advanced sequential cone programming algorithm. Case studies are carried on a 30-bus-20-node system and a 197-bus-171-node practical system in Northwest China to illustrate the effectiveness of the proposed model.

Review and prospect on the construction method of security region for integrated natural gas and power systems

Natural gas and power systems are both important components of modern energy systems. As an efficient and clean peak-shaving power source, natural gas power generation is crucial for ensuring the safe operation of a high-penetration renewable energy power system —supporting China's strategic goal of "carbon peaking and carbon neutrality." However, in recent years, there have been frequent incidents of cascading faults between the gas and power grids. Studying the security region of the integrated electricity-gas system (IEGS) and identifying the system's security margin online is the key to actively preventing such accidents. In view of this, this paper first introduced the typical coupling forms of electricity-gas networks and summarizes the security analysis and evaluation methods from the perspectives of power systems and natural gas systems, respectively. Then, the basic model of the IEGS security region considering the interconnection of gas and electricity networks was extracted, and various methods for solving IEGS security boundaries and dealing with uncertain disturbance factors were compared. Finally, the possible development directions of the construction method of the security region for IEGS were proposed.

Fast Resilience Assessment of Integrated Electricity-Gas Systems Considering Non-Convex Gas Flow Dynamics

Fast Resilience Assessment of Integrated Electricity-Gas Systems Considering Non-Convex Gas Flow Dynamics

Reliability Evaluation of Multi-Area Integrated Electricity-Gas Systems Based on the Improved Uniform Design

Reliability Evaluation of Multi-Area Integrated Electricity-Gas Systems Based on the Improved Uniform Design

Modeling Load Redistribution Attacks in Integrated Electricity-Gas Systems

Modeling Load Redistribution Attacks in Integrated Electricity-Gas Systems

Early warning and proactive control strategies for power blackouts caused by gas network malfunctions

There is growing consensus that gas-fired generators will play a crucial role during the transition to net-zero energy systems, both as an alternative to coal-fired generators and as a flexibility service provider for power systems. However, malfunctions of gas networks have caused several large-scale power blackouts. The transition from coal and oil to gas fuels significantly increases the interdependence between gas networks and electric power systems, raising the risks of more frequent and widespread power blackouts due to the malfunction of gas networks. In a coupled gas–electricity system, the identification and transmission of gas network malfunction information, followed by the redispatch of electric power generation, occur notably faster than the propagation and escalation of the malfunction itself, e.g., significantly diminished pressure. On this basis, we propose a gas-electric early warning system that can reduce the negative impacts of gas network malfunctions on the power system. A proactive control strategy of the power system is also formulated based on the early warning indicators. The effectiveness of this method is demonstrated via case studies of a real coupled gas–electricity system in China.

Risk-averse distributed optimization for integrated electricity-gas systems considering uncertainties of Wind-PV and power-to-gas

The uncertainties of wind power and photovoltaic (Wind-PV) systems pose a threat to the steady functioning of integrated electricity-gas systems and restrict their effective consumption. In this case, an optimal operation model considering the cost risk of Wind-PV uncertainties is proposed. Firstly, the cost risk of uncertainties in typical scenarios is measured by conditional value at risk (CVaR). Secondly, considering that the power system and the natural gas system as different stakeholders have barriers in information exchange, a distributed optimization operation model is established, and the uncertainty of the conversion efficiency of the coupling unit from Power-to-Gas (P2G) is considered. Then, the integrated electricity-gas systems are decoupled through consistency constraints, and the model is solved by an algorithm framework based on adaptive penalty ADMM. This work analyzed the impact of uncertainty and CVaR parameters on optimized operation, and discussed the performance of related distributed algorithms. The following conclusions were drawn: 1) the proposed model reduces costs by 1.72% and can measure the operation risk caused by uncertainty factors, which provide guidance for decision makers; 2) the total cost will increase by 3.9% when the uncertainty factor reaches the preset maximum value, which demonstrates that the uncertainty of conversion efficiency should be controlled to reduce the operation cost of P2G; 3) As the convergence accuracy gradually improves, the proposed method is easier to converge and converges faster.

Energy Management of Distribution-Level Integrated Electric-Gas Systems With Fast Frequency Reserve

This paper studies the energy management of distribution-level integrated electric-gas systems (D-IEGSs), considering their frequency support capability via providing the fast frequency reserve (FFR) service. The dynamics of the main grid frequency as well as frequency regulation behaviors of gas-fired turbines (GTs), power-to-gas (P2G) units, wind turbines (WTs) and Photovoltaic (PV) units in the D-IEGS are formulated, including the dead zone, limiting ranges, and the time constant of the governors. The impacts of frequency regulation behaviors of GTs and P2G units on the operation constraints of the D-IEGS are examined through a feasibility check sub-problem. Thus, the overall problem becomes a two-stage one, which is solved by the column-and-constraint generation (C&CG) algorithm. The variable-step difference and the binary variable reduction schemes are devised to decrease the computation burden. Simulation results on the IEGS with a 13-bus power network and a 6-node gas network verify the value of FFR provided by the D-IEGS and the necessity of modeling the operation constraints of the gas network.

Online Operational Decision-Making for Integrated Electric-Gas Systems With Safe Reinforcement Learning

Online Operational Decision-Making for Integrated Electric-Gas Systems With Safe Reinforcement Learning

The Static Stability Region of an Integrated Electricity-Gas System Considering Voltage and Gas Pressure

In an integrated electricity-gas system (IEGS), load fluctuations affect not only the voltage in the power system but also the gas pressure in the natural gas system. The static voltage stability region (SVSR) method is a tool for analyzing the overall static voltage stability in a power system. However, in an IEGS, the SVSR boundary may be overly optimistic because the gas pressure may collapse before the voltage collapses. Thus, the SVSR method cannot be directly applied to an IEGS. In this paper, the concept of the SVSR is extended to the IEGS-static stability region (SSR) while considering voltage and gas pressure. First, criteria for static gas pressure stability in a natural gas system are proposed, based on the static voltage stability criteria in a power system. Then, the IEGS-SSR is defined as a set of active power injections that satisfies multi-energy flow (MEF) equations and static voltage and gas pressure stability constraints in the active power injection space of natural gas-fired generator units (NGUs). To determine the IEGS-SSR, a continuation MEF (CMEF) method is employed to trace the boundary point in one specific NGU scheduling direction. A multidimensional hyperplane sampling method is also proposed to sample the NGU scheduling directions evenly. The obtained boundary points are further used to form the IEGS-SSR in three-dimensional (3D) space via a Delaunay triangulation hypersurface fitting method. Finally, the numerical results of typical case studies are presented to demonstrate that the proposed method can effectively form the IEGS-SSR, providing a tool for IEGS online monitoring and dispatching.

Interval State Estimation of Electricity-Gas Systems Considering Measurement Correlations

The popularization of electricity-gas systems leads to increasing demand for state management of systems. However, the existence of neglected measurement correlations brings uncertainties to the electricity-gas systems state estimation. In this paper, an interval state estimation method that considers measurement correlations existing in the electricity-gas systems is presented. We derive the linear measurement model for the electricity-gas systems through Taylor series expansion and estimate the measurement variance-covariance matrix with measurement correlations. The system parameter matrix and the measurement variance-covariance matrix containing measurement correlations are combined into an interval, and the interval state matrix considering measurement correlations is constructed. Then, the linear equations for the state estimation interval considering measurement correlations are established based on the measurement containing correlations and interval state matrix; as a result, the electricity-gas system state estimation model containing measurement correlations is established. In addition, a method for determining the range of state estimation intervals is proposed. Numerical tests on an integrated electricity-gas system comprising a 10-node natural gas network and IEEE 30-bus system indicate that the proposed approach has more advantages over the UT+KO approach in computation accuracy and computation efficiency.

Hidden Convexity-Based Distributed Operation of Integrated Electricity-Gas Systems

Hidden Convexity-Based Distributed Operation of Integrated Electricity-Gas Systems

Coordinated Low-Carbon Dispatching on Source-Demand Side for Integrated Electricity-Gas System Based on Integrated Demand Response Exchange

With the exploration of deep decarbonization around the world, the contradiction between the low-carbon operation and energy supply in energy systems has been aggravating. There is an urgent need to tap the interactive potential between source and demand sides. In view of the current lack of efficient incentive measures for low-carbon energy consumption, an integrated demand response exchange (IDRX) mechanism is proposed to promote the coordinated low-carbon dispatching on source-demand side for integrated electricity-gas system (IEGS). The value model of IDRX for emission reduction is built to measure the ability of multi-energy load aggregators (MELAs) for decarbonization, and guide the IEGS operator to trade with the appropriate MELAs. An IDRX market clearing model is established based on non-cooperative game theory to allocate the decarbonization benefits among the entities in IEGS, thereby motivating the low-carbon demand response of users. Combined with the optimal operation of carbon capture power plant and power-to-gas (CCPP-P2G) on the source side, a two-stage low-carbon dispatching model for IEGS is established. Case studies are carried out with seasonal and uncertainty scenarios to verify the effectiveness of IDRX in emission mitigation and highlight the economic benefits of the proposed low-carbon dispatching model.

A Dynamic Equivalent Energy Storage Model of Natural Gas Networks for Joint Optimal Dispatch of Electricity-Gas Systems

A Dynamic Equivalent Energy Storage Model of Natural Gas Networks for Joint Optimal Dispatch of Electricity-Gas Systems

Centralized Multifunctional Control of Integrated Electricity–Gas Network in District Energy System Considering Resilience

District energy systems (DESs) and integrated electricity-gas systems (IEGSs) are closely related. The performance of these systems under critical situations, such as faults and equipment outages, has not been adequately investigated. The operation of DESs may also be significantly affected by installing central generating systems for gas or electricity sectors. These central generating units may deal with outages and faults. In the literature, there is not a comprehensive model that considers renewables in IEGS, uncertainties of generating systems, mutual connection between electricity and gas sub-grids, ability of exchanging power with upstream grid, centralized storage device for electrical sector, and centralized power supply for gas sector. All these points are considered and modeled in the proposed model. This paper presents several multi-purpose control strategies for DES that are designed and implemented on an IEGS. Electricity and thermal loads are used to model the DES energy needs. In the electricity subsystem, by using several local renewable energy sources (RESs) and a central battery, not only the electric loads are supplied, but also the DES can be connected to the upstream grid and trade the scheduled power in accordance with the electricity market contract in all normal and critical conditions. On the other hand, the gas subsystem is powered by a central fuel cell. Gas and electricity subsystems in the DES region are designed to assist each other during outages and events in order to increase the resilience. All RESs, central battery, and fuel cell are equipped with individual controllers to achieve the above objectives. A centralized control framework is used to manage all these controllers under a variety of operating conditions. Numerical simulations in MATLAB software verify the model ability to control DES and IEGS properly.

A market framework to exploit the multi-energy operating reserve of smart energy hubs in the integrated electricity-gas systems

Faced with increasing uncertainties in the integrated electricity and gas system (IEGS), the multi-energy operating reserve(MOR), i.e., extra electric and gas reserve capacity, is becoming vitally important to guarantee the reliable operation of the system. Smart energy hubs(SEHs) located at the demand side of the IEGS can adjust their electricity and gas consumption through energy substitution, which has great potential to provide the MOR. Current studies mainly concentrate on the energy trading mechanism among different SEHs in the energy-only market, which may not effectively incentivize SEHs to provide MOR for system operation. Besides, due to the limited energy capacity, SEHs cannot directly participate in the wholesale reserve market along with other large-capacity resources, e.g., power plants and gas wells. To address these, a two-stage market framework is proposed for exploiting the multi-energy operating reserve of SEHs. In the first stage, the wholesale market is cleared considering the participation of large-capacity resources to determine the clearing results of MOR. Based on the results, an energy-loss-cost calculation model is developed to measure the value of the specific MOR level. By altering the reserve requirements, the values of different MOR levels can be accordingly calculated to formulate the multi-energy operating reserve demand surface(MOR-DS), which can quantify varying MOR values with different levels of the reserve. With the MOR-DS describing the price elasticity of the MOR, a distributed MOR clearing mechanism is developed in the second stage to determine the quantity and price of the reserve from SEHs. The clearing mechanism is constructed as a distributed optimization model considering optimal collaboration among different SEHs. Case studies verify that the proposed market framework can effectively stimulate SEHs to provide MOP through economic incentives, which can realize the reliability improvement of IEGS and the revenue increase of SEHs.

A data-driven distributionally robust chance constrained approach for optimal electricity-gas system operation

The extensive installation of gas-fired units and the substantial increase in natural gas consumption have strengthened the interdependence between power system and natural gas system. Therefore, the uncertainty of wind power brings new challenges to the safe and economic operation of the electricity–gas integrated energy system (IES). To optimize the operating costs of the energy supply side, an optimal electricity–gas energy flow (OEGEF) framework considering wind power uncertainty is established to maximize the social welfare (SW) of energy suppliers, energy storage suppliers and flexible users. Under this framework, based on the historical wind power data, a data-driven distributionally robust chance constrained (DRCC) model is proposed and the tractable reformulation form is given. In addition, a distributed manner via alternating direction method of multipliers (ADMM) is adopted to solve the power system sub-problems and the natural gas system sub-problems for protecting privacy data. Compared with the deterministic model, the uncertain model of Gaussian distribution and symmetrical distribution, the proposed model has stronger robustness. The case studies are conducted by two IESs of different scales, the results of numerical examples show that the model is effective for the optimal coordination of uncertain IES.