Multi-period integrated natural gas and electric power system probabilistic optimal power flow incorporating power-to-gas units

The increasing adoption of gas-fired power plants directly strengthens the coupling between electric power and natural gas systems. Current industrial practice in optimal power flow for electric power systems has not taken the security constraints of gas systems into consideration, resulting in an overly-optimistic solution. Meanwhile, the operation of electric power and natural gas systems is coupled over multiple periods because of the ramp rate limits of power generators and the slow dynamical characteristics of gas systems. Based on these motivations, we propose a multi-period integrated natural gas and electric power system probabilistic optimal power flow(M-GEPOPF) model, which includes dynamic gas flow models. To address the uncertainties originating from wind power and load forecasting, a probabilistic optimal power flow(POPF) calculation based on a three-point estimate method(3 PEM) is adopted. Moreover, power-togas(Pt G) units are employed to avoid wind power curtailment and enable flexible bi-directional energy flows between the coupled energy systems. An integrated IEEE RTS 24-bus electric power system and the Belgian 20-node natural gas system are employed as a test case to verify the applicability of the proposed M-GEPOPF model, and to demonstrate the potential economic benefits of Pt G units.

A power plant for integrated waste energy recovery from liquid air energy storage and liquefied natural gas

Liquefied natural gas(LNG)is regarded as one of the cleanest fossil fuel and has experienced significant developments in recent years.The liquefaction process of natural gas is energy-intensive,while the regasification of LNG gives out a huge amount of waste energy since plenty of high grade cold energy(-160℃)from LNG is released to sea water directly in most cases,and also sometimes LNG is burned for regasification.On the other hand,liquid air energy storage(LAES)is an emerging energy storage technology for applications such as peak load shifting of power grids,which generates 30%-40%of compression heat(-200℃).Such heat could lead to energy waste if not recovered and used.The recovery of the compression heat is technically feasible but requires additional capital investment,which may not always be economically attractive.Therefore,we propose a power plant for recovering the waste cryogenic energy from LNG regasification and compression heat from the LAES.The challenge for such a power plant is the wide working temperature range between the low-temperature exergy source(-160℃)and heat source(-200℃).Nitrogen and argon are proposed as the working fluids to address the challenge.Thermodynamic analyses are carried out and the results show that the power plant could achieve a thermal efficiency of 27%and 19%and an exergy efficiency of 40%and 28%for nitrogen and argon,respectively.Here,with the nitrogen as working fluid undergoes a complete Brayton Cycle,while the argon based power plant goes through a combined Brayton and Rankine Cycle.Besides,the economic analysis shows that the payback period of this proposed system is only 2.2 years,utilizing the excess heat from a 5 MW/40 MWh LAES system.The findings suggest that the waste energy based power plant could be co-located with the LNG terminal and LAES plant,providing additional power output and reducing energy waste.

Real-time Risk-averse Dispatch of an Integrated Electricity and Natural Gas System via Condi-tional Value-at-risk-based Lookup-table Ap-proximate Dynamic Programming

The real-time risk-averse dispatch problem of an integrated electricity and natural gas system(IEGS)is studied in this paper.It is formulated as a real-time conditional value-at-risk(CVaR)-based risk-averse dis-patch model in the Markov decision process framework.Because of its stochasticity,nonconvexity and nonlinearity,the model is difficult to analyze by traditional algorithms in an acceptable time.To address this non-deterministic polynomial-hard problem,a CVaR-based lookup-table approximate dynamic programming(CVaR-ADP)algo-rithm is proposed,and the risk-averse dispatch problem is decoupled into a series of tractable subproblems.The line pack is used as the state variable to describe the impact of one period’s decision on the future.This facilitates the reduction of load shedding and wind power curtailment.Through the proposed method,real-time decisions can be made according to the current information,while the value functions can be used to overview the whole opti-mization horizon to balance the current cost and future risk loss.Numerical simulations indicate that the pro-posed method can effectively measure and control the risk costs in extreme scenarios.Moreover,the decisions can be made within 10 s,which meets the requirement of the real-time dispatch of an IEGS.Index Terms—Integrated electricity and natural gas system,approximate dynamic programming,real-time dispatch,risk-averse,conditional value-at-risk.

Electricity Pricing for Natural Gas CHP Projects The Higher, the Better?

Regarding the state's policy that gives a higher on-grid electricity price to natural gas CHP (combined heat and power) projects, this paper studies the effect of it on the operation of those projects by theoretical analysis and a case study. It concludes that on-grid electricity price on the high side, compared to heat price, will lead power plants to produce more electricity but less heat, thus causing decrease of the plants' thermal eff iciency and harm to energy saving of the whole society.

Reliability Assessment of Integrated Electricity and Natural Gas Transmission Systems in Presence of Power-to-gas and Combined Heat and Power Technologies

Assessing the reliability of integrated electricity and gas systems has become an important issue due to the strong dependence of these energy networks through the power-to-gas(P2G)and combined heat and power(CHP)technologies.The current work,initially,presents a detailed energy flow model for the integrated power and natural gas system in light of the P2G and CHP technologies.Considering the simultaneous load flow of networks,a contingency analysis procedure is proposed,and reliability is assessed through sequential Monte Carlo simulations.The current study examines the effect of independent and dependent operation of energy networks on the reliability of the systems.In particular,the effect of employing both P2G and CHP technologies on reliability criteria is evaluated.In addition,a series of sensitivity analysis are performed on the size and site of these technologies to investigate their effects on system reliability.The proposed method is implemented on an integrated IEEE 24-bus electrical power system and 20-node Belgian natural gas system.The simulation procedure certifies the proposed method for reliability assessment is practical and applicable.In addition,the results prove connection between energy networks through P2G and CHP technologies can improve reliability of networks if the site and size of technologies are properly determined.

Coordinated optimal dispatch and market equilibrium of integrated electric power and natural gas networks with P2G embedded

As power to gas(P2 G) technology gradually matures, the coupling between electricity networks and natural gas networks should ideally evolve synergistically.With the intent of characterizing market behaviors of integrated electric power and natural gas networks(IPGNs)with P2 G facilities, this paper establishes a steady-state model of P2 G and constructs optimal dispatch models of an electricity network and a natural gas network separately. In addition, a concept of slack energy flow(SEF) is proposed as a tool for coordinated optimal dispatch between the two networks. To study how the market pricing mechanism affects coordinated optimal dispatch in an IPGN, a market equilibrium-solving model for an IPGN is constructed according to game theory, with a solution based on the Nikaido-Isoda function. Case studies are conducted on a joint model that combines the modified IEEE 118-node electricity network and the Belgian 20-node gas network.The results show that if the game between an electric power company and a natural gas company reaches market equilibrium, not only can both companies maximize their profits, but also the coordinated operation of the coupling units, i.e., gas turbines and P2 G facilities, will contribute more to renewable energy utilization and carbon emission reduction.

Reliability evaluation of integrated electricity–gas system utilizing network equivalent and integrated optimal power flow techniques

The wide utilization of gas-fired generation and the rapid development of power-to-gas technologies have led to the intensified integration of electricity and gas systems.The random failures of components in either electricity or gas system may have a considerable impact on the reliabilities of both systems.Therefore,it is necessary to evaluate the reliabilities of electricity and gas systems considering their integration.In this paper,a novel reliability evaluation method for integrated electricity-gas systems(IEGSs)is proposed.First,reliability network equivalents are utilized to represent reliability models of gas-fired generating units,gas sources(GSs),power-to-gas facilities,and other conventional generating units in IEGS.A contingency management schema is then developed considering the coupling between electricity and gas systems based on an optimal power flow technique.Finally,the time-sequential Monte Carlo simulation approach is used to model the chronological characteristics of the corresponding reliability network equivalents.The proposed method is capable to evaluate customers’reliabilities in IEGS,which is illustrated on an integrated IEEE Reliability Test System and Belgium gas transmission system.

Optimal Operation of Integrated Energy Systems Subject to Coupled Demand Constraints of Electricity and Natural Gas

This paper proposes a hybrid multi-objective optimization and game-theoretic approach(HMOGTA)to achieve the optimal operation of integrated energy systems(IESs)consisting of electricity and natural gas(E&G)utility networks,multiple distributed energy stations(DESs),and multiple energy users(EUs).The HMOGTA aims to solve the coordinated operation strategy of the electricity and natural gas networks considering the demand characteristics of DESs and EUs.In the HMOGTA,a hierarchical Stackelberg game model is developed for generating equilibrium strategies of DESs and EUs in each district energy network(DEN).Based on the game results,we obtain the coupling demand constraints of electricity and natural gas(CDCENs)which reflect the relationship between the amounts and prices of electricity and cooling(E&C)that DESs purchase from utility networks.Furthermore,the minimization of conflicting costs of E&G networks considering the CDCENs are solved by a multi-objective optimization method.A case study is conducted on a test IES composed of a 20-node natural gas network,a modified IEEE 30-bus system,and 3 DENs,which verifies the effectiveness of the proposed HMOGTA to realize fair treatment for all participants in the IES.

Stochastic Dynamic Economic Dispatch of Wind-integrated Electricity and Natural Gas Systems Considering Security Risk Constraints

As the proportion of wind power generation increases in power systems,it is necessary to develop new ways for wind power accommodation and improve the existing power dispatch model.The power-to-gas technology,which offers a new approach to accommodate surplus wind power,is an excellent way to solve the former.Hence,this paper proposes to involve power-to-gas technology in the integrated electricity and natural gas systems(IEGSs).To solve the latter,on one hand,a new indicator,the scale factor of wind power integration,is introduced into the wind power stochastic model to better describe the uncertainty of grid-connected wind power;on the other hand,for quantizing and minimizing the impact of the uncertainties of wind power and system loads on system security,security risk constraints are established for the IEGS by the conditional value-at-risk method.By considering these two aspects,an MILP formulation of a security-risk based stochastic dynamic economic dispatch model for an IEGS is established,and GUROBI obtained from GAMS is used for the solution.Case studies are conducted on an IEGS consisting of a modified IEEE 39-bus system and the Belgium 20-node natural gas system to examine the effectiveness of the proposed dispatch model.

Cascading Failure Propagation Simulation in Integrated Electricity and Natural Gas Systems

The sharp increase in the total installed capacity of natural gas generators has intensified the dynamic interaction between the electricity and natural gas systems,which could induce cascading failure propagation across the two systems that deserves intensive research.Considering the distinct time response behaviors of the two systems,this paper discusses an integrated simulation approach to simulate the cascading failure propagation process of integrated electricity and natural gas systems(IEGSs).On one hand,considering instantaneous re-distribution of power flows after the occurrence of disturbance or failure,the steady-state AC power flow model is employed.On the other hand,gas transmission dynamics are represented by dynamic model to capture the details of its transition process.The interactions between the two systems,intensified by energy coupling components(such as gas-fired generator and electricity-driven gas compressor)as well as the switching among the operation modes of compressors during the cascading failure propagation process,are studied.An IEGS composed of the IEEE 30-bus electricity system and a 14-node 15-pipeline gas system is established to illustrate the effectiveness of the proposed simulation approach,in which two energy sub-systems are coupled by compressor and gas-fired generator.Numerical results clearly demonstrate that heterogeneous interactions between electricity and gas systems would trigger the cascading failure propagation between the two coupling systems.

Coordinated Dispatch of Integrated Electricity-Natural Gas System and the Freight Railway Network

With the significant development of liquefied natural gas(LNG)rail transport,the railway system is increasingly more closely connected with the integrated electricity-natural gas system(IEGS).To coordinate the economic operations of the two systems,this paper innovatively proposes a coordinated dispatch model of IEGS with LNG infrastructures and a freight railway network with LNG transport.First,an operational scheduling model of the railway network,considering energy consumption,is put forward for both LNG transmission and ordinary freight transport.Then,the coordinated dispatch problem of IEGS and the railway network is formulated into a mixed-integer linear programming model via the big M method and a modified incremental linearization approach.Finally,a bi-level optimization algorithm based on generalized benders decomposition(GBD)is presented to solve the coordinated dispatch problem due to the restrictions on exchanging private information.Case studies demonstrate the effectiveness of the proposed model and algorithm as well as the potential benefit for wind power accommodation.

Analysis and Economic Evaluation of Hourly Operation Strategy Based on MSW Classification and LNG Multi-Generation System

In this study,a model of combined cooling,heating and power system with municipal solid waste(MSW)and liquefied natural gas(LNG)as energy sources was proposed and developed based on the energy demand of a large community,andMSW was classified and utilized.The systemoperated by determining power by heating load,and measures were taken to reduce operating costs by purchasing and selling LNG,natural gas(NG),cooling,heating,and power.Based on this system model,three operation strategies were proposed based on whether MSW was classified and the length of kitchen waste fermentation time,and each strategy was simulated hourly throughout the year.The results showed that the strategy of MSW classified and centralized fermentation of kitchen waste in summer(i.e.,strategy 3)required the least total amount of LNG for the whole year,which was 47701.77 t.In terms of total annual cost expenditure,strategy 3 had the best overall economy,with the lowest total annual expenditure of 2.7730×108 RMB at LNG and NG unit prices of 4 and 4.2 RMB/kg,respectively.The lower heating value of biogas produced by fermentation of kitchen waste from MSW being classified was higher than that of MSW before being classified,so the average annual thermal economy of the operating strategy of MSW being classified was better than that of MSW not being classified.Among the strategies in which MSW was classified and utilized,strategy 3 could better meet the load demand of users in the corresponding season,and thus this strategy had better thermal economy than the strategy of year-round fermentation of kitchen waste(i.e.,strategy 2).The hourly analysis data showed that the net electrical efficiency of the system varies in the same trend as the cooling,heating and power loads in all seasons,while the relationship between the energy utilization efficiency and load varied from season to season.This study can provide guidance for the practical application of MSW being classified in the system.

Optimal Energy Reserve Scheduling in Integrated Electricity and Gas Systems Considering Reliability Requirements

With the growing interdependence between the electricity system and the natural gas system,the operation uncertainties in either subsystem,such as wind fluctuations or component failures,could have a magnified impact on the reliability of the whole system due to energy interactions.A joint reserve scheduling model considering the cross-sectorial impacts of operation uncertainties is essential but still insufficient to guarantee the reliable operation of the integrated electricity and natural gas system(IEGS).Therefore,this paper proposes a day-ahead security-constrained unit commitment(SCUC)model for the IEGS to schedule the operation and reserve simultaneously considering reliability requirements.Firstly,the multi-state models for generating units and gas wells are established.Based on the multi-state models,the expected unserved energy cost(EUEC)and the expected wind curtailment cost(EWC)criteria are proposed based on probabilistic methods considering wind fluctuation and random failures of components in IEGS.Furthermore,the EUEC and EWC criteria are incorporated into the day-ahead SCUC model,which is nonconvex and mathematically reformulated into a solvable mixed-integer second-order cone programming(MISOCP)problem.The proposed model is validated using an IEEE 30-bus system and Belgium 20-node natural gas system.Numerical results demonstrate that the proposed model can effectively schedule the energy reserve to guarantee the reliable operation of the IEGS considering the multiple uncertainties in different subsystems and the cross-sectorial failure propagation.

Active-reactive power scheduling of integrated electricity-gas network with multi-microgrids

Advances in natural gas-fired technologies have deepened the coupling between electricity and gas networks,promoting the development of the integrated electricity-gas network(IEGN)and strengthening the interaction between the active-reactive power flow in the power distribution network(PDN)and the natural gas flow in the gas distribution network(GDN).This paper proposes a day-ahead active-reactive power scheduling model for the IEGN with multi-microgrids(MMGs)to minimize the total operating cost.Through the tight coupling relationship between the subsystems of the IEGN,the potentialities of the IEGN with MMGs toward multi-energy cooperative interaction is optimized.Important component models are elaborated in the PDN,GDN,and coupled MMGs.Besides,motivated by the non-negligible impact of the reactive power,optimal inverter dispatch(OID)is considered to optimize the active and reactive power capabilities of the inverters of distributed generators.Further,a second-order cone(SOC)relaxation technology is utilized to transform the proposed active-reactive power scheduling model into a convex optimization problem that the commercial solver can directly solve.A test system consisting of an IEEE-33 test system and a 7-node natural gas network is adopted to verify the effectiveness of the proposed scheduling method.The results show that the proposed scheduling method can effectively reduce the power losses of the PDN in the IEGN by 9.86%,increase the flexibility of the joint operation of the subsystems of the IEGN,reduce the total operation costs by $32.20,and effectively enhance the operation economy of the IEGN.

Prime Energy Challenges for Operating Power Plants in the GCC

There is a false notion of existing available, abundant, and long lasting fuel energy in the Gulf Cooperation Council (GCC) Countries;with continual income return from its exports. This is not true as the sustainability of this income is questionable. Energy problems started to appear, and can be intensified in coming years due to continuous growth of energy demands and consumptions. The demands already consume all produced Natural Gas (NG) in all GCC, except Qatar;and the NG is the needed fuel for Electric Power (EP) production. These countries have to import NG to run their EP plants. Fuel oil production can be locally consumed within two to three decades if the current rate of consumed energy prevails. The returns from selling the oil and natural gas are the main income to most of the GCC. While NG and oil can be used in EP plants, NG is cheaper, cleaner, and has less negative effects on the environment than fuel oil. Moreover, oil has much better usage than being burned in steam generators of steam power plants or combustion chambers of gas turbines. Introducing renewable energy or nuclear energy may be a necessity for the GCC to keep the flow of their main income from exporting oil. This paper reviews the GCC productions and consumptions of the prime energy (fuel oil and NG) and their role in electric power production. The paper shows that, NG should be the only fossil fuel used to run the power plants in the GCC. It also shows that the all GCC except Qatar, have to import NG. They should diversify the prime energy used in power plants;and consider alternative energy such as nuclear and renewable energy, (solar and wind) energy.

Unified probabilistic gas and power flow

The natural gas system and electricity system are coupled tightly by gas turbines in an integrated energy system. The uncertainties of one system will not only threaten its own safe operation but also be likely to have a significant impact on the other. Therefore, it is necessary to study the variation of state variables when random fluctuations emerge in the coupled system. In this paper, a multislack-bus model is proposed to calculate the power and gas flow in the coupled system. A unified probabilistic power and gas flow calculation, in which the cumulant method and Gram–Charlier expansion are applied, is first presented to obtain the distribution of state variables after considering the effects of uncertain factors. When the variation range of random factors is too large, a new method of piecewise linearization is put forward to achieve a better fitting precision of probability distribution. Compared to the Monte Carlo method, the proposed method can reduce computation time greatly while reaching a satisfactory accuracy.The validity of the proposed methods is verified in a coupled system that consists of a 15-node natural gas system and the IEEE case24 power system.

考虑氢混燃机动态混氢特性的电-气互联系统优化调度

电–气互联系统是综合能源系统的重要组成部分,燃气机组是其中关键的能源耦合元件,而随着能源系统低碳化转型,燃气机组掺氢燃烧发电的技术应运而生。传统氢混燃机相关研究大多只考虑固定掺氢比运行的情况,并未考虑机组动态调整掺氢比运行的影响。传统电–气互联系统优化调度相关研究主要面向运行经济性,而对计及氢混燃机的能量与备用统一出清鲜有研究。为此,该文提出了一种考虑氢混燃机动态混氢比的电–气互联系统优化调度方法,基于动态混氢特性建立氢混燃机精细化模型,并通过电解水制氢技术为氢混燃机提供氢气来源,配置储氢罐和储气罐作为联合体为系统提供备用;采用二项式松弛方法对氢混燃机耗气流量方程进行线性转化,将原有非凸非线性模型转化为混合整数线性规划模型求解;最后通过仿真验证所提方法的有效性,分析不同场景下系统运行状态,实现了“风电–电解水制氢–氢混燃机”模式下风电消纳潜力的深度挖掘。

Bi-Level Bidding and Multi-Energy Retail Packages for Integrated Energy Service Providers Considering Multi-Energy Demand Elasticity

How to effectively use the multi-energy demand elasticity of users to bid in the multi-energy market and formulate multi-energy retail packages is an urgent problem which needs to be solved by integrated energy service providers(IESPs)to attract more users and reduce operating costs.This paper presents a unified clearing of electricity and natural gas based on a bi-level bidding and multi-energy retail price formulation method for IESPs considering multi-energy demand elasticity.First,we propose an operating structure of IESPs in the wholesale and retail energy markets.The multi-energy demand elasticity model of retail-side users and a retail price model for electricity,gas,heat and cooling are established.Secondly,a bi-level bidding model for IESPs considering multi-energy demand elasticity is established to provide IESPs with wholesale-side bidding decisions and retail-side energy retail price decisions.Finally,an example is given to verify the proposed method.The results show that the method improves the total social welfare of the electricity and natural gas markets by 7.99%and the profit of IESPs by 1.40%.It can reduce the variance of the electricity,gas,and cooling load curves,especially the reduction of the variance of the electricity load curve can which reach 79.90%.It can be seen that the research in this paper has a positive effect on repairing the limitations of integrated energy trading research and improving the economics of the operation of IESPs.

考虑氢能-天然气混合储能的电-气综合能源微网日前经济调度优化

在可再生能源渗透率的快速增长背景下,构建电-气综合能源系统具有重要的经济和环保意义。传统电-气综合能源系统模型对电转气（power to gas,P2G）过程处理过于简化,且环保效益考虑不充分。在电-气综合能源系统中,提出带有中间缓冲环节的P2G实现系统—氢能-天然气混合储能系统（hydrogen-gas energy storage system,HGESS）,将P2G过程细分为电转氢和电转天然气,并分别与燃料电池和微型燃气机形成高效型和能量型两阶段电-气-电的能量闭环流动圈。然后将HGESS与微网结合,提出计及P2G过程能量转换损失和环境成本的日前经济调度优化模型。算法中分别采用分段线性化和二阶锥松弛方法,对电网潮流和天然气网络潮流非线性边界做线性化处理。最后在算例中采用高、低风电并网渗透率两种场景,结果证明所提HGESS在高、低渗透率下的电-气综合能源系统都具很好的经济性和环保性,具有广阔的应用前景。

电–气混联综合能源系统概率能量流分析

由电力系统(electric power systems,EPS)、天然气系统(natural-gas systems,NGS)之间的耦合与互联构成的综合能源系统(integrated energy systems,IES),对于构建经济、环保、高效的能源系统至关重要。同时,由于IES中大量的不确定因素,有必要将不确定建模技术应用于IES分析。该文将广泛应用于EPS的概率潮流的概念推广到IES的概率能量流分析中,计及了EPS、NGS之间3方面的耦合:1)燃气轮机组;2)电力驱动加压站;3)能源集线器。在IES稳态能量流的基础上,考虑了电、气、热负荷以及风电场出力的不确定性,并采用蒙特卡罗模拟法求解IES概率能量流。算例分析表明,NGS(或EPS)中不确定性因素会对EPS(或NGS)的概率能量流产生影响;同时NGS能量流方程线性化精度明显低于EPS。