Gas-fired Generation Research Articles

Power Congestion Management in Integrated Electricity and Gas Distribution Grids

The proliferation of gas-fired generation (GfG) units and emerging power-to-gas (PtG) technology can set the stage for an integrated natural gas and power distribution system. PtG and gas-fired units have the potential to mitigate several existing and imminent issues of power distribution systems. This paper investigates how PtG and GfG facilities can be added to the portfolio of conventional resolutions when the motivation is (partly) congestion management in power distribution systems. It demonstrates how PtG and GfG units as merchant investments can change the operation philosophy from the traditional preventive to the novel corrective mode. To that end, a new real-time optimal scheduling algorithm is proposed to enable a PtG–GfG unit to optimally contribute to the congestion management. Merchandise operators profit, in addition to the arbitrage benefit, by relieving the distribution grid's congestion, thereby achieving a more stable return on investments. Slack variables are incorporated into the optimization problem to measure the contribution of the PtG–GfG unit to the congestion management. A new mechanism is proposed through which the merchandise operator is financially compensated by the power system operator, due to its contribution to the congestion management. Numerical studies using real-world data on a test system validate the efficacy and feasibility of the algorithm.

The value of gas-fired power plants in markets with high shares of renewable energy: A real options application

Using a real options model, this paper quantifies a gas-fired power plant's operating value and the value of a new investment against the background of a market transition to renewable electricity. The model is run with recent data for Germany's power sector and for different types of gas-fired power plants.The result is twofold. First, the paper achieves a more realistic value by improving on existing models: it models electricity and gas prices as a two-dimensional stochastic process, each component consisting of the sum of a seasonal pattern and a mean-reverting process; it uses high granularity by modelling hourly time-steps; and it incorporates power plant ramping times and costs. Second, it compares two types of power plant models, one with daily and one with hourly operating decisions, and thereby quantifies the value of a plant's intraday flexibility. The hourly model replicates operators' and investors' decision making accurately. This is evidenced by the fact that the results trace current major developments like the recent decline and come-back of gas-fired generation in Germany.The paper contributes to a better understanding of the choices operators and investors face in current electricity markets. In the absence of large scale storage solutions flexible supply of electricity, as provided by gas, is important in the transition to renewable energies in Germany and across Europe.

Flexibility and Efficiency of Steam Turbine Extraction vs Gas Fired Generation as Steam Source for Post Combustion CO2 Capture on Coal Fired Power Plant

CO2 emissions from electrical power generation must be reduced if global climate change mitigation targets are to be met. Expansion of renewable sources of power generation and the application of carbon capture and sequestration are two strategies required to reduce the CO2 emissions from this sector. As the penetration of renewable resources increases, non-renewable generation will need to become more flexible in order to back-up the intermittent renewable energy sources. Post combustion CO2 capture is the only proven full scale option currently available for reducing emissions from existing coal fired power plants. Post combustion capture processes however require significant quantities of thermal energy (or steam) to regenerate the solvent used for CO2 capture. This requirement for thermal energy can represent almost half of the de-rate associated with CO2 capture. Numerous studies have evaluated sources of this thermal energy; such as the existing steam turbine, or the integration of new gas fired sources. Most studies that have compared these sources of thermal energy have evaluated only performance at full load but this study focuses on flexibility and efficiency of these two configurations over a broader range of output. The conclusion of the study is that the existing steam turbine of the associated power plant can be re-engineered to become a more efficient and a more flexible source of the thermal energy than the addition of a gas fired generation source.

Integrated coordination scheduling framework of electricity-natural gas systems considering electricity transmission N\u2009\u2212\u20091 contingencies and gas dynamics

This paper discusses a security-constrained integrated coordination scheduling framework for an integrated electricity-natural gas system (IEGS), in which both tight interdependence between electricity and natural gas transmission networks and their distinct dynamic characteristics at different timescales are fully considered. The proposed framework includes two linear programming models. The first one focuses on hour-based steady-state coordinated economic scheduling on power outputs of electricity generators and mass flow rates of natural gas sources while considering electricity transmission N − 1 contingencies. Using the steady-state mass flow rate solutions of gas sources as the initial value, the second one studies second-based slow gas dynamics and optimizes pressures of gas sources to ensure that inlet gas pressure of gas-fired generator is within the required pressure range at any time between two consecutive steady-state scheduling. The proposed framework is validated via an IEGS consisting of an IEEE 24-bus electricity network and a 15-node 14-pipeline natural gas network coupled by gas-fired generators. Numerical results illustrate the effectiveness of the proposed framework in coordinating electricity and natural gas systems as well as achieving economic and reliable operation of IEGS.

Economic leverage affords post-combustion capture of 43% of carbon emissions: Supersonic separators for methanol hydrate inhibitor recovery from raw natural gas and CO2 drying

Offshore oil/gas productions are power intensive and CO2 emitters from gas-fired power generation. This work investigates supersonic separator as a strategy for affording post-combustion capture backed up by cost reductions. Conventional offshore gas processing usually loses thermodynamic hydrate inhibitor methanol in processing and exported gas. This work analyses a supersonic separator variant gas processing simultaneously reducing methanol losses. Such process dramatically improves gas-plant profitability via cost-reduction of methanol make-up and power-consumption, simultaneously increasing revenues from liquefied-petroleum-gas by-product. This economic leverage affords post-combustion carbon capture, including subsequent CO2 dehydration and compression for exportation of high-pressure liquid CO2. This corresponds to abate 43% of CO2 emissions boosting revenues via enhanced oil recovery. Moreover, CO2 is dehydrated via another supersonic separator operating with minimum head-loss, minimizing compression costs. Despite its much higher investment, the new process with carbon capture presents higher net value (865.63 MMUSD) than the conventional processing without carbon capture (829.31 MMUSD), being economically feasible and more environmentally adequate with cleaner natural gas production and successful CO2 management. The new process is superior in several scenarios and particularly favored by oil prices above 55 USD/bbl. Rising oil price from 40 to 100 USD/bbl, the new process net value rises 29%, whereas the conventional counterpart rises only 7.5%. In addition, as a plausible future scenario, CO2 taxation favors the new process, which always has superior economic performance, even without CO2 taxation. In summary, implementing supersonic separators in offshore natural gas processing aiming at anti-hydrate recovery and CO2 dehydration for enhanced oil recovery creates economic leverage sustaining Carbon Capture & Storage without loss of competitiveness. This result, backed up by rigorous thermodynamic simulations and economic-environmental assessments, configure an original achievement to the literature.

An Emissions Arbitrage Algorithm to Improve the Environmental Performance of Domestic PV-Battery Systems

Domestic PV-battery systems are rarely operated in a way which specifically maximizes environmental benefit. Consequently the studies that seriously examine such systems often find that the greenhouse gas and pollutant emissions savings of rooftop PV, though still positive, are lessened by adding a domestic battery. This study shows thatby simulating a PV-battery system with a range of sizes that this need not be inevitable. A novel algorithm was designed specifically to perform ‘emissions arbitrage’: to charge the battery when the grid emissions intensity is low and to discharge when it is high. It was found that the CO2 saved relative to the same system with PV only can more than pay back the CO2 debt of manufacturing the battery. This is true as long as the UK moves away from the present-day situation where natural gas-fired generators are nearly always the marginal generator. This work underlines the importance of both the operating strategy and the interactions between the system and the entire grid, in order to maximize the environmental benefit achievable with domestic PV-battery systems.

Robust dispatch for Integrated Electricity and Natural Gas System Considering Wind Power Uncertainty

With the support of flexible gas-fired generations and power-to-gas technologies, the integrated electricity and natural gas system (IEGS) is able to achieve a deep penetration of renewable energy. This paper proposes a two-stage robust day-ahead dispatch model for IEGS against the uncertainty of wind power, electricity load and gas load. Nonlinear and nonconvex natural gas flow constraints are relaxed into the second-order cone constraints considering the gas flow directions. Then the Column &Constraint Generation method is adopted to solve the proposed two-stage robust optimization problem. An IEEE 39-bus-20-gas- node test IEGS is used to test the effectiveness of proposed model.

Convex optimization based adjustable robust dispatch for integrated electric-gas systems considering gas delivery priority

With the mushrooming deployment of volatile renewable energy sources as well as the intrinsic uncertainty from the demand side, secure and economic energy dispatch has become increasingly challenging for energy systems, especially for the emerging and promising integrated electric-gas system. Aside from the aforementioned uncertainties, the dispatch of the integrated electric-gas system suffers from two inherent obstacles, which are model nonconvexities, originating from the Weymouth equations in the gas network, and the demand-side differentiated gas delivery priorities according to current industrial practice, respectively. To deal with the conundrum, an adjustable robust dispatch method is proposed for operating the integrated electric-gas system, where uncertain wind generation outputs and gas loads are described by intervals. In contrast to existing work employing pre-determined intervals, the admissible wind output intervals in this paper are optimized, reflecting the interdependencies between the regulation capabilities of gas-fired generation and the gas delivery adequacy. By this means, gas delivery priority is considered in comply with gas industrial practice, and it also provides a more flexible mechanism to maintain robustness of the dispatch strategy. Through analyzing the feasibility impact of uncertain variables, a deterministic robust counterpart is derived, in which uncertainties are eliminated based on affine generator dispatch and estimation of total line pack. Furthermore, nonconvex quadratic terms in the Weymouth equations are expressed as difference-of-convex functions. A sequential convex optimization procedure is developed, and a heuristic method is suggested to initiate the sequential algorithm. The proposed models and methods are tested on three test systems. Key impact factors on the dispatch strategy, such as gas prices, wind generation forecast accuracy and gas network initial operation conditions, are analyzed, and the computational benefits brought by convex programming are validated by scalability tests.

Integrated Electricity and Natural Gas Demand Response for Manufacturers in the Smart Grid

The smart grid opens many opportunities for electricity suppliers and customers to maintain grid stability, reduce electricity cost, and promote environmentally sustainable operation. Unfortunately, these benefits cannot be fully realized from industrial energy customers due to inadequate manufacturing decision-making methodology that fails to consider manufacturers and energy suppliers simultaneously. The influence manufacturers have on the grid comes from their large electricity demand contributing to peak power and their large natural gas usage due to the increasing dependency of the electricity sector on gas-fired generation. Nonetheless, the interdependency between manufacturers’ electricity and natural gas demand has not been well studied. In this paper, an electricity and natural gas driven production scheduling model for manufacturers is established. The model considers time-based and event-based electricity and gas demand response. A modified simulated annealing (MSA) algorithm is proposed to solve the problem in reaction to real-time supply notifications to promote the interaction between manufacturers and energy providers. Numerical case studies are implemented and illustrate that 66%–68% in energy cost savings for the manufacturer can be achieved when using the proposed model compared to baseline scenarios. Meanwhile, the MSA algorithm outperforms various solution methods in solving the proposed problem.

Some economic estimates of gas-fired power generation in a carbon constrained Australia

The future of Australia’s electricity industry has resulted in significant debate about the mix of electricity generating technologies. The Finkel Review and ensuing National Electricity Guarantee policy discussion have revealed divisions between key stakeholders over the future generating mix between renewable and fossil fuel power generation options. A portfolio of technologies will be required, including the need for gas-fired power generation with and without carbon capture and storage (CCS), to provide dispatchable synchronous electricity. Gas Vision 2050 has stated that CCS, along with biogas and hydrogen, will be one of the three transformational technologies affecting the gas industry going forward. Through the use of a techno-economic model, the costs for a hypothetical new-build gas-fired power plant in the Hunter Valley with and without CCS were estimated. The model is cross referenced with other authoritative publications including the CO2CRC Australian Power Generation Technology Report. The model considers the base-case scenario and sensitivity analysis of key cost drivers such as the domestic gas price and labour. The results of the model will enable key energy and gas industry stakeholders to make informed decisions about the vital role of gas as a power generation technology in Australia to deliver dispatchable synchronous electricity in a carbon constrained environment.

Renewables, gas and batteries: reliable and efficient power for industry

Woodside believes gas-fired power and renewables are ideal partners to power industry. There are environmental and commercial reasons to integrate solar photovoltaic panels, or other intermittent renewable generation, with gas-fired power generation to support industry, especially in the Pilbara where sunlight is plentiful. This would increase energy efficiency, and reduce emissions, enabling a transformative shift towards a lower carbon future without compromising reliability or affordability. Woodside is studying a concept to integrate an industrial-scale solar farm, a battery energy storage system and reciprocating gas engines, to provide hybrid renewable, dispatchable, power generation for industry on the Burrup Peninsula. Feasibility studies have identified that a combination of solar photovoltaics, with high efficiency, fast starting, medium speed gas engines, can supply reliable power at world class energy efficiencies, while meeting local cyclonic design conditions and proposed grid stability requirements.

Real-time subsidy based robust scheduling of the integrated power and gas system

In this work, a real-time subsidy based robust scheduling method for the integrated gas and power system is proposed. Bi-directional energy conversion, including the power-to-gas and gas-fired generation, is operated via dynamic variant price signals. The gaming between the electrical power system and the natural gas system is formulated in the bi-level optimization. The upper-level problem minimizes the operational cost, in which the real-time subsidy for power-to-gas and gas-fired units is obtained. The lower-level problem maximizes the profit for the power-to-gas and gas-fired units, in which the transient gas flow is introduced. In addition, in order to counter the uncertainties brought on by wind power, a real-time subsidy update strategy based on robust optimization is proposed to stimulate the regulation capabilities of the power-to-gas and gas-fired units. This bi-level optimization is reformulated as a mixed-integer quadratic programming problem using the Karush-Kuhn-Tucker optimization conditions. Simulation results show that the real-time subsidy scheduling can make power-to-gas and gas-fired units follow the system operator’s preferences such as wind power accommodation, mitigation of unsupplied load, and relieving network congestion.

Optimal co-scheduling of distributed generation resources and natural gas network considering uncertainties

Abstract It must be noticed that renewable energy resources operation with battery is the best method of electrical load cost provision. In this regard, integrated natural gas (NG) network with power system is utilized in this paper in order to increase system reliability and reduce pressure of power generators. In fact, NG is considered as clean and available fuel in order to support power system. It is possible to connect power system and gas network by Joint Unit (JU). JUs include Natural gas-fired distributed power generators (NGDG) and Power to Gas (PtG) units. In this paper, gas-fired turbine fuel supply process is prioritized. That is, desired gas is supplied by gas wells of gas network piping entry; PtG unit will supply NGDG gas as long as electricity cost is low. After optimal scheduling, By applying mixed integrated linear programming (MILP) for integrated system and two essential factors (power not supplied and gas not supplied), system operation under load and resources fluctuation studied. Finally, appropriate location and optimum capacity of new distributed energy resources for power system or compressor for gas network are selected. 24-Bus power system with renewable resources of Photovoltaic (PV) ،Wind Turbine (WT), battery energy storage, with 7- node natural gas network and two gas wells integration are selected as studied case for time range of 24 h in order to analyze process numerically.

A Chance Constrained Programming Approach to the Integrated Planning of Electric Power Generation, Natural Gas Network and Storage

Natural gas is increasingly becoming the preferred choice of fuel for flexible electricity generation globally resulting in an electricity system whose reliability is progressively dependent on that of the natural gas transportation system. The cascaded relationship between the reliabilities of these system necessitates an integrated approach to planning both systems. This paper presents a chance constrained programing approach to minimize the investment cost of integrating new natural gas-fired generators, natural gas pipeline, compressors, and storage required to ensure desired confidence levels of meeting future stochastic power and natural gas demands. The proposed model also highlights the role of natural gas storage in managing short-time uncertainties in developing a long-term expansion plan for both the electric and natural gas systems. A two-stage chance constrained solution algorithm is employed in solving the mix-integer nonlinear programing optimization problem and illustrated on a standard IEEE 30 bus test system superimposes on the Belgian high-calorific gas network.

Robust Day-Ahead Scheduling of Electricity and Natural Gas Systems via a Risk-Averse Adjustable Uncertainty Set Approach

The requirement for energy sustainability drives the development of renewable energy technologies and gas-fired power generation. The increasing installation of gas-fired units significantly intensifies the interdependency between the electricity system and natural gas system. The joint scheduling of electricity and natural gas systems has become an attractive option for improving energy efficiency. This paper proposes a robust day-ahead scheduling model for electricity and natural gas system, which minimizes the total cost including fuel cost, spinning reserve cost and cost of operational risk while ensuring the feasibility for all scenarios within the uncertainty set. Different from the conventional robust optimization with predefined uncertainty set, a new approach with risk-averse adjustable uncertainty set is proposed in this paper to mitigate the conservatism. Furthermore, the Wasserstein–Moment metric is applied to construct ambiguity sets for computing operational risk. The proposed scheduling model is solved by the column-and-constraint generation method. The effectiveness of the proposed approach is tested on a 6-bus test system and a 118-bus system.

Methology and Case Study on Water Footprint of Gas-fired Power Generation Company

Scientific evaluation of the impact of human activities on water resources is a prerequisite for the sustainable use of water resources. Combined with the development status of China's thermal power generation industry, a water footprint accounting method for thermal power plants was constructed, and a typical gas-fired power generation company was used for empirical analysis. The results show that energy and material water footprints account for the largest proportion of the company's water footprint. Enhancing energy efficiency and selecting clean energy are the keys to reducing the water footprint of gas-fired power companies.

A Tight Convex Relaxation for the Natural Gas Operation Problem

With the increase in the investment in the gas-fired electricity generation technology, capturing the operation constraints of the natural gas network in the electricity and natural gas operation problems becomes more crucial. The non-convexity in the feasibility region formed by natural gas network constraints will impede achieving the global solution for these problems. This letter proposed an algorithm to procure a tight and tractable convex relaxation for the natural gas network constraints that can be leveraged in the electricity and/or natural gas network operation problems. The merit of the proposed algorithm is illustrated using a case study and the efficiency of the proposed formulation is compared with mixed integer linear and semidefinite programming formulations.

Co-optimization scheduling of interdependent power and gas systems with electricity and gas uncertainties

The rapid growth of natural gas fuel consumption by gas-fired generators and the new emerging power-to-gas technology have intensified interdependency of electric power and natural gas systems. Consequently, such interdependency, together with heterogeneous uncertainties of the power system (e.g., power loads and renewable energy) and the gas system (e.g., gas loads), has brought new challenges to energy system operators for the secure and economic operation of interdependent power and gas systems. Specifically, uncertainties from one infrastructure could easily spread to the other, which consequently increase vulnerability and eventually lead to cascading outages of both systems. This paper proposes a two-stage adjustable robust model to study day-ahead coordinated optimal scheduling of the interdependent power and gas systems. Dual-fuel generating units are also considered for shaving gas fuel consumptions and ensuring the security of both systems during peak gas demand hours. Moreover, Weymouth gas flow constraints are linearized via Taylor series expansion, which facilitates the implementation of column-and-constraint generation algorithm to effectively solve the proposed two-stage adjustable robust model with nonlinear gas flow constraints in the second stage. Numerical case studies illustrate that dual-fuel units can enhance the secure and economical operation of interdependent power and gas systems, especially when natural gas demands present upward uncertainties. It is also demonstrated that power-to-gas facilities can facilitate a deeper penetration of volatile renewable energy by effectively converting excessive renewable generation into natural gas.

Garbage can theory and Australia's National Electricity Market: Decarbonisation in a hostile policy environment

After two decades of consistent economic and technical performance, conditions in Australia's National Electricity Market (NEM) deteriorated sharply in 2016/17. Prices more than doubled on the east coast, tripled in South Australia (SA), and the SA regional grid collapsed. Nothing spectacular occurred with final demand – this was a supply-side energy crisis driven by the exit of 18% of Australia's coal-fired generation fleet and the inadequate entry of new plant. Australia's NEM encountered an uncoordinated exit-driven episode of the Resource Adequacy problem. In the USA where 18% of coal plant has also exited, Resource Adequacy and low cost energy has been maintained by the entry of an enormous fleet of wind, solar and gas-fired generators. In Australia, an equivalent response did not occur; decades of climate change policy discontinuity meant the speed of coal plant exit was unpredictable, entry of renewables delayed through stop-start policy, and gas-fired plant was subject to critical hold-up due to excess LNG plant investment. Resolution requires a united and stable climate change policy architecture that works with, not against, the NEM's world-class institutional design, and greater transparency around planned plant exit.

Optimal energy flow and nodal energy pricing in carbon emission-embedded integrated energy systems

Green energy is driving the evolutions of energy industry and carbon emission is becoming an important concern. Considering the increasing couplings among various energy sectors, this paper investigates multi-period optimal energy flow and energy pricing in carbon-emission embedded integrated energy systems, including electricity, natural gas, and district heating networks. Firstly, an optimal scheduling model of integrated energy systems was proposed in this paper. The models of DC power flow, natural gas pipeline flow and heating network energy flow are presented and linearized for the optimization problem. Natural gas-fired generators and combined heat and power (CHP) units are modeled as coupling components of electricity-gas and electricity-heating networks. Then, based on the optimal scheduling model, the locational marginal prices (LMP) for electricity, natural gas and heating network are determined. Moreover, the carbon emission caused by energy production has been taken into account in the optimal scheduling and energy pricing process. Finally, case studies on a combined network consisting of IEEE 39-bus system, Belgium 20-node natural gas system and 6-node heating system demonstrate the effectiveness of the proposed model and the impacts of carbon emission on system scheduling and LMP.