Coordinated restoration optimization of power-gas integrated energy system with mobile emergency sources

In an integrated energy system(IES) composed of multiple subsystems, energy coupling causes an energy supply blockage or shutdown in one subsystem, thereby affecting the energy flow distribution optimization of other subsystems.The energy supply should be globally optimized during the IES energy supply restoration process to produce the highest restoration net income. Mobile emergency sources can be quickly and flexibly connected to supply energy after an energy outage to ensure a reliable supply to the system, which adds complexity to the decision. This study focuses on a powergas IES with mobile emergency sources and analyzes the coupling relationship between the gas distribution system and the power distribution system in terms of sources, networks, and loads, and the influence of mobile emergency source transportation. The influence of the transient process caused by the restoration operation of the gas distribution system on the power distribution system is also discussed. An optimization model for power-gas IES restoration was established with the objective of maximizing the net income. The coordinated restoration optimization decision-making process was also built to realize the decoupling iteration of the power-gas IES, including system status recognition, mobile emergency source dispatching optimization, gas-to-power gas flow optimization, and parallel intra-partition restoration scheme optimization for both the power and gas distribution systems. A simulation test power-gas IES consisting of an 81-node medium-voltage power distribution network, an 89-node medium-pressure gas distribution network, and four mobile emergency sources was constructed. The simulation analysis verified the efficiency of the proposed coordinated restoration optimization method.

Integrated Model for Resilience Evaluation of Power-Gas Systems Under Windstorms

Integrated power-gas systems(IPGS)have developed critical infrastructure in integrated energy systems.Moreover,various extreme weather events with low probability and high risk have seriously affected the stable operation of IPGSs.Due to close interconnectedness through coupling elements between the power system(PS)and natural gas system(NGS)when a disturbance happens in one system,a series of complicated sequences of dependent events may follow in another system.Especially under extreme conditions,this coupling can lead to a dramatic degradation of system performance,resulting in catastrophic failures.Therefore,there is an urgent need to model and evaluate resilience of IPGSs under extreme weather.Following this development trend,an integrated model for resilience evaluation of IPGS is proposed under extreme weather events focusing on windstorms.First,a framework of IPGS is proposed to describe states of the system at different stages under disaster conditions.Furthermore,an evaluation model considering cascading effects is used to quantify the impact of windstorms on NGS and PS.Meanwhile,a Monte Carlo simulation(MCS)technique is utilized to characterize chaotic fault of components.Moreover,time-dependent nodal and system resilience indices for IPGS are proposed to display impacts of windstorms.Numerical results on the IPGS test system demonstrate the proposed methods.

A Multi-slack Bus Model for Bi-directional Energy Flow Analysis of Integrated Power-gas Systems

The bi-directional energy conversion components such as gas-fired generators(GfG)and power-to-gas(P2G)have enhanced the interactions between power and gas systems.This paper focuses on the steady-state energy flow analysis of an integrated power-gas system(IPGS)with bi-directional energy conversion components.Considering the shortcomings of adjusting active power balance only by single GfG unit and the capacity limitation of slack bus,a multi-slack bus(MSB)model is proposed for integrated power-gas systems,by combining the advantages of bi-directional energy conversion components in adjusting active power.The components are modeled as participating units through iterative participation factors solved by the power sensitivity method,which embeds the effect of system conditions.On this basis,the impact of the mixed problem of multi-type gas supply sources(such as hydrogen and methane generated by P2G)on integrated system is considered,and the gas characteristics-specific gravity(SG)and gross calorific value(GCV)are modeled as state variables to obtain a more accurate operational results.Finally,a bi-directional energy flow solver with iterative SG,GCV and participation factors is developed to assess the steady-state equilibrium point of IPGS based on Newton-Raphson method.The applicability of proposed methodology is demonstrated by analyzing an integrated IEEE 14-bus power system and a Belgian 20-node gas system.

Reliability Assessment for Integrated Power-gas Systems Considering Renewable Energy Uncertainty and Cascading Effects

Integrated power-gas systems(IPGSs)make the power system and natural gas system(NGS)as a whole,and strengthen interdependence between the two systems.Due to bidirectional energy conversion in IPGS,a disturbance may turn into a catastrophic outage.Meanwhile,increasing proportion of renewable energy brings challenges to reliability of IPGS.Moreover,partial failure or degradation of system performance leads IPGS operate at multiple performance levels.Therefore,this paper proposes a reliability assessment model of IPGSs which represents multiple performance of components and considers cascading effects,as well as renewable energy uncertainty.First,a framework of IPGS reliability assessment is proposed:multistate models for main elements in the IPGS are represented.Especially a gas-power-generation calculation operator and a power-to-gas calculation operator are utilized to bi-directionally convert a multi-state model between NGS and power systems.Furthermore,nodal reliability indices for IPGS are given to display impacts of cascading effects and renewable energy uncertainty on reliabilities of IPGSs.Numerical results on IPGS test system demonstrate the proposed methods.

Segmented Real-time Dispatch Model and Stochastic Robust Optimization for Power-gas Integrated Systems with Wind Power Uncertainty

This paper develops a segmented real-time dispatch model for power-gas integrated systems(PGISs), where power-to-gas(P2G) devices and traditional automatic generation control units are cooperated to manage wind power uncertainty. To improve the economics of the real-time dispatch in regard to the current high operation cost of P2Gs, the wind power uncertainty set is divided into several segments, and a segmented linear decision rule is developed, which assigns adjustment tasks differently when wind power uncertainty falls into different segments. Thus, the P2G operation with high costs can be reduced in real-time adjustment. Besides, a novel segmented stochastic robust optimization is proposed to improve the efficiency and robustness of PGIS dispatch under wind power uncertainty, which minimizes the expected cost under the empirical wind power distribution and builds up the security constraints based on the robust optimization. The expected cost is formulated using a Nataf conversion-based multi-point estimate method, and the optimal number of estimate points is determined through sensitivity analysis. Furthermore, a difference-ofconvex optimization with a partial relaxation rule is developed to solve the non-convex dispatch problem in a sequential optimization framework. Numerical simulations in two testing cases validate the effectiveness of the proposed model and solving method.

Data Mining Based Integrated Electric-Gas Energy System Multi-Objective Optimization

With the proposal of carbon neutrality,how to improve the proportion of clean energy in energy consumption and reduce carbon dioxide emissions has become the important challenge for the traditional energy industry.Based on the idea of multi-energy complementarity,a typical integrated energy system consisting of electric system and gas system is constructed based on the application of power to gas(P2G)technology and gas turbine in this paper.Furthermore,a multi-objective optimization model with economic improvement,carbon emission reduction and peak-load shifting as objectives is proposed,and solved by BSO algorithm.Finally,a typical power-gas coupling system is selected as an example to verify the effectiveness of the model.The results showed that the proposed multi-objective optimization model based on BSO algorithm can better play the complementary characteristics of the electric and gas system,and significantly improve the comprehensive benefits of system operation.