Electricity-gas Integrated Energy System Research Articles

Low carbon and economic optimal operation of electricity-gas integrated energy system considering demand response

Integrated Energy System is an important direction for the transformation of the power industry. IES can give full play to the complementary role of multiple energy sources and serve to achieve the industry's energy saving and emission reduction goals. Firstly, this paper establishes a P2G refined operation model considering two stages of hydrogen production from electrolytic water and hydrogen methanation. Secondly, based on the analysis of the IES load characteristics, the multi-energy loads are divided into longitudinal demand responses where the same energy type can be transferred and reduced in time, and horizontal demand responses where different energy types can be substituted for each other, and the corresponding mathematical models are established. Finally, the reward and penalty ladder carbon trading mechanism are used to quantify the carbon trading cost, and the IES low-carbon economic optimization model integrating the Power-to-gas refinement model and demand response is constructed. The model was subjected to second-order cone programming relaxation and incremental segmented linearization methods before being solved using the CPLEX commercial solver. Simulation analyses were performed in an IES consisting of an IEEE 33-node distribution network and a 24-node gas distribution network. The results show that considering demand response can fully exploit the flexible coordination performance of the load side, resulting in a 12.6% reduction in total system cost and a 38.8% reduction in carbon emissions.

Optimal scheduling for electricity–gas integrated energy system under the carbon-neutrality goal

In light of China’s carbon-neutral policy and the Energy Internet, it is crucial to reduce the carbon emissions resulting from the operation of the electricity–gas integrated energy system (EGIES). To address this issue, this paper proposes an optimal scheduling strategy for EGIES in line with the carbon-neutrality goal. Firstly, the oxygen-enriched combustion power plant, equipped with a power to gas unit, is modeled to maximize its carbon capture ability. Next, an optimal scheduling model for EGIES is proposed, which considers the bonus-penalty ladder carbon price and the oxygen-enriched combustion power plant, with the aim of minimizing the total operation costs and carbon emissions of the EGIES. Finally, the proposed model is applied to an EGIES, consisting of a 33-bus electric distribution network and a 20-bus natural gas network. The simulation results demonstrate that the proposed method can reduce the operation costs of the EGIES by up to 22.5% and the carbon emissions by up to 75.1t when compared to existing models.

Research on reliability assessment and multi-time scale improvement strategy of electricity-gas integrated energy system under cyber attack

While the coupling between various energy systems is deepening as integrated energy develops quickly, security risks in the information network system will be introduced into the physical system, and the interaction between the systems causes the security risks to increase. It is essential to maintain the multi-energy coupling integrated energy system’s safe and reliable operation. Therefore, this paper first constructs the cyber physics system (CPS) model based on the electricity-gas integrated energy system (EGIES), the fault propagation mechanism of the system caused by the cyber attack is analyzed, and the cyber attack scenario simulation method based on the N-n predicted fault set is proposed. Secondly, based on the optimal load shedding model and the reliability assessment index, the reliability assessment method of the electricity-gas integrated system under cyber attack is proposed. Then, on the basis of system reliability assessment, a multi-time scale reliability improvement strategy based on branch power and pipeline flow optimization of EGIES under cyber attack is proposed. Finally, the simulation results of the IEEE57-NGS20 electricity-gas integrated system verified the effectiveness of the proposed method. The proposed optimization strategy reduces the out-of-limit range of power transmission lines and natural gas pipelines, reduces the probability of cascading failure in the system under information attacks, and improves the resistance and energy supply reliability of the system against cyber attacks.

Incorporating gas pipeline leakage failure modes in risk evaluation of electricity-gas integrated energy systems

In order to incorporate the gas leakage failure in the EGIES risk evaluation, a multi-state Markov state transition model considering gas pipeline leakage is creatively developed, and the analytical formulas to calculate the involved transition rate parameters in this model are derived. The concept of virtual gas load is presented to reflect the impacts of gas pipeline leakage on the operation of natural gas network, and then the EGIES network analysis model considering the virtual load nodes is presented. A bi-level sampling method based on the mixed sequential and non-sequential Monte Carlo simulation is proposed to simulate the chronological and non-chronological aspects of EGIES simultaneously. The load curtailment based EGIES risk indices, including the gas leakage risk indices, are also designed. An EGIES with a modified RBTS and a 7-node gas system is used to demonstrate the application of the proposed method. The results indicate that pipeline leakage failures have significant impacts on the reliability of EGIES. Ignoring pipeline leakage failures in the risk evaluation of EGIES will result in an overly underestimation of system risk.

Coordinate control law analysis for hydrogen blended electricity-gas integrated energy system

Hydrogen-blended electricity-gas integrated energy system (EG-IES) utilizes surplus renewable energy power generation to blends hydrogen into the natural gas pipeline network for achieve efficient and economical large-scale hydrogen consumption and long-distance transportation. While enhancing the coupling between the power grid and gas grid, the scheduling control of such a complex system becomes increasingly important. The paper presents a dynamic model of a hydrogen blended EG-IES with high renewable energy permeability, and a modeling method that considers distribution parameters of the natural gas pipeline is obtained by using the cell segmentation and calculating the blended gas composition in real-time to avoid the assumption of constant composition. After the validation against available operational data, a case study of the certain area of Central China is simulated. The coordinate control law is reasonably designed according to the dynamic characteristics of EG-IES and the objective of realizing the load increase within the hydrogen concentration constraint, and the PID is utilized as the benchmark to compare dynamic performance. The results demonstrate that the coordinated control based on the alternate adjustment control law has no overshoot and shorter adjustment time of pl and ε about 33% and 42% than benchmark on the large delay system.

Data-Driven Situation Awareness of Electricity-Gas Integrated Energy System considering Time Series Features

Clean and low-carbon electricity-gas integrated energy system (EGIES) is being developed rapidly in order to meet the dual-carbon target. Situation awareness can provide an early warning of operational risks to the EGIES, which is helpful for its promotion and application. In this paper, a data-driven situation awareness method of EGIES considering time series features is proposed. The state and deviation vectors of EGIES are solved at the situation perception level based on the state estimation. The recurrence plot (RP) is used at the situation comprehension level to extract the time series features of historical deviations, and the operating state of future deviations is encoded in the form of labels. A convolutional neural network (CNN) is established at the situation projection level to project the future operating state of the EGIES based on the RP of the historical deviations. A case study of EGIES coupling a 14-node power system with a 7-node gas system shows that the projection accuracy of the proposed method increases by 2.07 and 3.04% compared with the long-short term memory (LSTM) neural network and the support vector machine (SVM), respectively.

Multi-stage resilience scheduling of electricity-gas integrated energy system with multi-level decentralized reserve

Extreme events pose threats to secure and consistent supply of electricity-gas integrated energy system (EGIES), and adequate resilience is essential for improving risk defense abilities. Considering the constraints of power distribution network (PDN) and natural gas system (NGS), a multi-stage strategy integrating multi-level decentralized reserve is proposed for resilience enhancement in EGIES. Storages of multi-area community integrated energy systems (CIESs) serve as the secondary reserve while the primary reserve, i.e., independent electric power/natural gas system, fails to meet reserve requirements. Furthermore, the thermal storage of building air on the consumption side is taken as the tertiary reserve, so as to obtain a better emergency response effect. The scheduling framework consists of reserve calculation, economic scheduling, and fault restoration. On the basis of multi-area reserve calculation, day-ahead economic scheduling is conducted, maintaining adequate reserve with consideration of decentralized reserve constraints; thus, high-priority demands can be recovered in case of supply disruptions. In addition, the flexible topology of PDN is utilized to facilitate the restored loads by optimal islanding partition. Via conic relaxation conversion, the original nonconvex model is tracked into a unified mixed-integer second-order cone programming (MISOCP) formulation, which can be effectively and accurately solved. Finally, numerical study on a modified IEEE 33-bus test system and a modified 7-node gas system connecting multiple community integrated energy systems shows the effectiveness of the proposed resilience strategy.

Optimal Scheduling for Flexible Regional Integrated Energy System with Soft Open Point

The Regional Integrated Energy System (RIES) has brought new modes of development, utilization, conversion, storage of energy. The introduction of Soft Open Point (SOP) and the application of Power to Gas (P2G) technology will greatly deepen the coupling of the electricity-gas integrated energy system, improve the flexibility and safety of the operation of the power system, and bring a deal of benefits to the power system. On this background, an optimal dispatch model of RIES combined cold, heat, gas and electricity with SOP is proposed. Firstly, RIES architecture with SOP and P2G is designed and its mathematical model also is built. Secondly, on the basis of considering the optimal scheduling of combined cold, heat, gas and electricity, the optimal scheduling model for RIES was established. After that, the original model is transformed into a mixed-integer second-order cone programming model by using linearization and second-order cone relaxation techniques, and the CPLEX solver is invoked to solve the optimization problem. Finally, the modified IEEE 33-bus system is used to analyze the benefits of SOP, P2G technology and lithium bromide absorption chillers in reducing system network loss and cost, as well as improving the system’s ability to absorb wind and solar and operating safety.

Optimal Scheduling of Electrical Energy Systems Using a Fluid Dynamic Analogy

The electricity-gas transformation problem and related intrinsic mechanisms are considered. First, existing schemes for the optimization of electricity-gas integrated energy systems are analyzed through consideration of the relevant literature, and an Electricity Hub (EH) for electricity-gas coupling is proposed. Then, the distribution mechanism in the circuit of the considered electricity-gas integrated system is analyzed. Afterward, a mathematical model for the natural gas pipeline is elaborated according to the power relationship, a node power flow calculation method, and security requirements. Next, the coupling relationship between them is implemented, and dedicated simulations are carried out. Through experimental data, it is found that after 79 data iterations, the optimization results of power generation and gas purchase cost in the new system converge to $54,936 in total, which is consistent with the data obtained by an existing centralized optimization scheme. However, the new proposed optimization scheme is found to be more flexible and convenient.

A multi-agent game based joint planning approach for electricity-gas integrated energy systems considering wind power uncertainty

To improve the effective planning of electricity-gas integrated energy systems (EGIES) among various stakeholders with distinct interests, a multi-agent game based joint long-term planning approach considering wind power uncertainty is proposed in this paper. First, the planning profit models of individual stakeholders are constructed. Then, the robust optimization approach is employed to deal with uncertainties of wind power outputs, and a virtual player ”nature” is introduced to represent uncertainties in the game process. Moreover, based on the analysis of the game mechanism among various stakeholders, a bi-level dynamic game based planning model for EGIES is proposed, conducting security checks through an integrated electricity-gas energy flow model. Finally, the proposed planning model is solved by an iterative search algorithm. Simulation results illustrate superiority of the proposed approach via two aspects: first, it guarantees the equity and provide fair profit allocation of all players in the game; second, it ensures security of the integrated energy system by effectively mitigating violations on voltage and nodal gas pressure limits.

A New Calculation Method for Optimal Energy Flow of Multi-regional Electricity-Gas Integrated Energy System

A New Calculation Method for Optimal Energy Flow of Multi-regional Electricity-Gas Integrated Energy System

Two-Time-Scale Approach to Characterize the Steady-State Security Region for the Electricity-Gas Integrated Energy System

The knowledge of the steady-state security region is essential for secure operation of the integrated energy system (IES). The two-time-scale feature of the IES is explored to facilitate construction of its exact steady-state security region. Conditions allowing decomposition of the IES into fast and slow subsystems are established. A complete characterization of the IES steady-state security region via the stable equilibrium manifold of the fast subsystem and the slow subsystem is derived and theoretically proven. This characterization can significantly facilitate construction of the IES steady-state security region (SSR) and is derived under the AC power flow model and gas flow model without any model approximation and simplification. Numerical studies are conducted to validate the derived characterization of the SSR and to illustrate the advantages of the proposed characterization in terms of robustness and reduced computational burden. Numerical studies show that exploring the fast and slow subsystems can lead to fast computation of feasible solutions with a 20-fold speed up in calculation time, as compared with the direct integration of the original IES system. Hence, the proposed two-time-scale method appears to be fast and yet accurate.

Toward Complete Characterization of the Steady-State Security Region for the Electricity-Gas Integrated Energy System

The steady-state security region of the integrated energy system (IES) is a useful tool for rapid security assessment and security evaluation of the integrated energy system. A complete characterization of the IES steady-state security region is derived. The derivation is under the nonlinear and non-convex AC power flow model, the gas flow model, and the uncertainty of renewable energy without any linear simplification. Then a novel and robust computation scheme to compute the IES steady-state security region is proposed and shown to eliminate the estimation errors of the existing methods. It is shown that the IES steady-state security region is non-convex and composed of several disjoint components. Numerical studies are conducted to show that the IES steady-state security regions obtained from the existing methods can be inaccurate, while the proposed characterization gives an exact estimation of the IES steady-state security region that significantly improves the previously proposed methods.

Reliability evaluation of EGIES with highly nonlinear modeling of gas system components

The interconnection and coordinated operation of electricity-gas integrated energy system (EGIES) is becoming a trend. The flexible energy conversion achieved by gas-fired power generation (GPG) and power to gas (P2G) has brought a new opportunity for improving the reliability of both electricity and gas systems in EGIES and enhancing the ability in absorbing fluctuant renewable energy. In this paper, a reliability evaluation framework for EGIES with the high nonlinearities of gas system components and the assessment of wind power absorption is proposed. To capture the practical operation behaviors of gas system, the highly nonlinear characteristics of gas system components are accurately modeled and incorporated into the proposed sequential simulation process. To address the convergence difficulties caused by the high nonlinearity of energy flow equations, an improved energy flow calculation algorithm based on a relaxation idea is presented, achieving an effective convergence acceleration in the reliability evaluation of EGIES. The validity and performance of the proposed method are verified by using the RBTS integrated with a gas network.

Incorporating compressor station multiple failure modes in risk evaluation of electricity-gas integrated energy systems

Multiple failure modes of gas compressor stations have not been modeled in the risk evaluation of electricity-gas integrated energy system (EGIES). This paper presents a method to incorporate the multiple failure modes of compressor stations with bypass system in the EGIES risk evaluation. Three outage models representing the multi-states and multi-failure-modes of compressor stations and a bi-level Monte Carlo sampling algorithm for the models are developed. A novel network model of EGIES considering the compressor stations with multiple failure modes is presented. An EGIES with a modified RBTS and an 11-node gas system is used to demonstrate the effectiveness of the proposed method and models. The results indicate that compressor stations have both positive and negative significant impacts on the risk of EGIES. The bypass systems for the compressor stations can effectively offset the negative impacts. Ignoring compressor stations and their station failures in the risk evaluation of EGIES may result in an inaccurate estimation of the system risk levels and even lead to a misleading conclusion in system planning.

Situation awareness and security risk mitigation for integrated energy systems with the inclusion of power‐to‐gas model

Power-to-gas (P2G) and gas-fired generation units (GFGUs) enable the bidirectional energy flow of integrated energy systems (IESs). The static security of IES should be analysed considering the interdependence between energy systems. In this study, the static security of IES is analysed, and a novel static security control strategy to improve the security of IES after N−1 contingency is proposed considering P2G. First, electricity–gas IES model is presented, and the multi-energy flow of IES is solved by the Newton–Raphson method. Then, N − 1 static security analysis is carried out for the electricity system and natural gas system. Based on the obtained Jacobian matrix during the energy flow calculation process after N − 1 contingency, variable sensitivity matrixes of voltage, gas pressure, branch power flow and pipeline flow to control variables are derived. Furthermore, a static security control strategy for IES based on the sensitivity matrices is developed to regulate operation statuses of P2G and GFGU and compressor outlet pressure to mitigate the violation of security constraints. The performance of the proposed analysis method and control strategy is evaluated by IES 4-12 and IES 118-48 test systems. The results demonstrate that the proposed control strategy can mitigate security risks of IES after N − 1 contingencies.

Robust Stochastic Dynamic Optimal Power Flow Model of Electricity-Gas Integrated Energy System considering Wind Power Uncertainty

The application of gas turbines and power to gas equipment deepens the coupling relationship between power systems and natural gas systems and provides a new way to absorb the uncertain wind power as well. The traditional stochastic optimization and robust optimization algorithms have some limitations and deficiencies in dealing with the uncertainty of wind power output. Therefore, we propose a robust stochastic optimization (RSO) model to solve the dynamic optimal power flow model for electricity-gas integrated energy systems (IES) considering wind power uncertainty, where the ambiguity set of wind power output is constructed based on Wasserstein distance. Then, the Wasserstein ambiguity set is affined to the eventwise ambiguity set, and the proposed RSO model is transformed into a mixed-integer programming model, which can be solved rapidly and accurately using commercial solvers. Numerical results for EG-4 and EG-118 systems verify the rationality and effectiveness of the proposed model.

Security region of natural gas network in electricity-gas integrated energy system

The strengthening interdependency between electricity network and natural gas network not only promotes the renewable energy integration and flexibility of electricity-gas integrated energy system (IES) operation, but also escalates the operation risk of the IES. Security region (SR) is a powerful tool to improve the situational awareness of IES security. However, the concept and application of SR for the natural gas network in IES is rare. This paper presents a SR of natural gas network in IES considering the influence of the electricity network and natural gas network. Firstly, the concepts of the SR, pressure security region (PSR) and transmission security region (TSR) of the natural gas network in the IES are defined by referring the definitions of electricity network SR. Then, the general nonlinear optimization energy flow (OEF) models are developed to form the SR, PSR and TSR of natural gas network in the IES, and the frameworks for constructing the SR of natural gas network in multi-dimensional space are also proposed. Results for the IES 30-20 and IES 118-3 × 20 test systems indicate that the proposal approach can construct the SR of natural gas network in IES with high accuracy.

A new modeling and solution method for optimal energy flow in electricity‐gas integrated energy system

With the increasing interdependency of electricity and gas, it is necessary to simultaneously investigate electric power system and natural gas system from the perspective of an electricity-gas integrated energy system (EGIES). As an extension and integration of both optimal power flow (OPF) and optimal gas flow (OGF), optimal energy flow (OEF) is regarded as the cornerstone of the EGIES and lays an essential foundation for further research on the EGIES's operation and analysis considering stochastic conditions and contingency states. The objective of this paper is to develop a generalized mathematical model and a universally applicable simulation tool for the OEF problem. First, natural gas system is modeled in a way similar to electric power system according to electricity-gas analogy analysis, where gas admittance, gas nodal admittance matrix, and the nodal equation of gas flow conservation are derived. Then, a generalized accurate OEF model is formulated by simultaneously integrating the OPF model and the OGF model as well as their coupling constraints in a unified modeling framework. Furthermore, an available hybrid optimization approach consisting of whale optimization algorithm, MATPOWER, hydraulic calculation iterative program, and nonstationary penalty function method is put forward to solve the OEF problem. The accuracy, feasibility, and applicability of the proposed modeling and solution method is finally demonstrated by analyzing Belgian 20-node gas system combined with IEEE 30-bus test system.

Convex Hull Based Robust Security Region for Electricity-Gas Integrated Energy Systems

Increasing interdependency between electric power systems and natural gas systems creates additional dimensions of flexibility of system operation; but it may also escalate risk levels if the two systems are managed without proper coordination. This paper presents a robust security region (RSR) for electricity-gas integrated energy systems (IESs). It is a collection of uncertain parameters, especially wind power generations, under which system power flow has at least one feasible solution. First, a nonlinear optimization model is employed to obtain a set of uniformly distributed points on power flow solvability boundaries, from which the IES security region is constructed using a convex hull. Then, the proposed RSR is constructed to provide secure operation for the base-case scenario, where uncertain wind power generation values are replaced with expected values, and provide a feasible redispatch plan for each wind power generation scenario. Other implications of the RSR on IES security assessment are also envisioned. Results for two test systems indicate that the convex hull approach provides a more accurate approximation of the IES security region than a hyperplane approach. Meanwhile, the benefits of RSR are demonstrated by comparing test results with those obtained for a deterministic security region.