P2G Facilities Research Articles

Bridging chance-constrained and stochastic optimization for risk estimation of virtual energy hubs dominated by hybrid vehicles under diverse uncertainties: To improve economic sustainability

Virtual energy hubs (VRHBs) combine dispersed energy resources to enhance the efficient use of various energy sources, grid flexibility, and renewable energy adoption. This paper investigates the adoption of VRHBs with power-to-gas (P2G) facilities and hybrid electric-compressed natural gas vehicles (HNGEVs) in the presence of renewable resources to effectively tackle carbon emissions and increase the flexibility of VRHBs. The proposed P2G facility is constructed from carbon capture to collect carbon pollution from fossil fuel resources and HNGEVs to recycle into synthesis gas in a methanation plant. Furthermore, due to severe uncertainties due to renewable resources and energy consumption intensity, the proposed framework utilizes stochastic-driven chance-constrained optimization, which enables decision-makers in VRHBs to account for the probabilistic nature of uncertainties. Chance-constrained optimization explicitly considers uncertainty through probabilistic constraints, providing a more robust and reliable solution compared to deterministic methods. By modeling uncertainties using chance-constrained programming, VRHBs can manage the economic risks under unexpected worst realizations in uncertainties. Based on the results, the P2G facility leads to a significant reduction in the daily emissions by 63.06 % and 42.77 % observed under no-risk and full-risk conditions, respectively. In addition, the suggested chance-constrained method resulted in a major decrease of 69 % in overall operational costs.

Two-stage planning model of power-to-gas station considering carbon emission flow

The widespread use of fossil fuels has substantially contributed to global climate change. One of the most crucial ways to address climate change is to minimize carbon emissions in the energy sector. Power-to-Gas (P2G) technology provides a potential solution. In this context, this paper introduces a novel two-stage P2G planning method for the electric-gas coupling system, using carbon emission flow technology. The carbon emission flow model employed facilitates the distribution of carbon emissions across the entire energy network. Central to our planning strategy is the identification of nodes with reduced carbon emissions for the siting of P2G facilities, predicated on the premise that such nodes are indicative of significant renewable energy utilization. Constructing P2G systems at these particular nodes is strategically advantageous for augmenting renewable energy consumption. In the initial phase, a P2G siting planning methodology predicated on a low-carbon criterion is advanced, resulting in a definitive siting scheme. Subsequently, the second phase involves establishing a P2G capacity optimization model that seeks to strike an economic equilibrium between the utilization of surplus wind power and P2G operational investment. An enhanced pigeon optimization algorithm is employed to resolve the proposed model. Our method is verified by simulation. Compared with other conventional models, the accommodation capacity of renewable energy with the proposed method is enhanced, and the carbon emissions and operating costs of IES are also reduced.

Systematic planning of power-to-gas for improving photovoltaic acceptance rate: Application of the potential RES penetration index

This paper proposes a novel method for integrating renewable energy sources (RES) and power-to-gas (P2G) technologies to optimize energy utilization efficiency as RES capacity increases. The method introduces the potential RES penetration index (PRPI) to select the appropriate capacity of P2G facilities for improved RES acceptance rates. In order to establish input constraints for RES and P2G facilities, this study determines the saturation point of RES (R-SP) and the saturation point of P2G (PG-SP). Additionally, the paper introduces the marginal capacity rate of RES to P2G (MCRG) as a useful tool for evaluating the adequacy of planned facilities. This paper's index is limited to PV as a renewable energy source. By incorporating PRPI into the input plan of P2G facilities, the proposed method improves PV's acceptance rate, contributes to facilities' economic planning, and streamlines optimization complexity. Previous studies have demonstrated the potential for P2G technology to optimize the integration of PV into the grid. However, the proposed method considers the PV's acceptance rate and provides system planners with necessary information on RES and P2G facility capacity. The method proposed in this paper can be extended to include other RES.

Rolling dispatch framework of integrated electricity-gas system considering power-to-gas facilities and natural gas network dynamics: Modelling and case studies

Rolling dispatch strategy is widely used in power systems to handle the uncertainty and volatility of renewable energy. Meanwhile, flexible gas-fired units and emerging power-to-gas (P2G) facilities integrate the power system and natural gas system as an integrated electricity-gas system (IEGS). Hence, rolling dispatch should be applied to the whole IEGS. This paper designs the rolling dispatch framework in the IEGS and proposes the partial-differential-equations-involved (PDEs) mathematical models that accurately formulate the natural gas network dynamics and the operation properties of P2G facilities to retain the facticity of the IEGS in the rolling dispatch process (e.g., the linepack characteristics of natural gas networks and the physical limits of the P2G facilities). The impact of uncertain wind power on the IEGS operation is also considered. In order to reduce the computational burdens, this paper employs a combination of implicit difference method and the technique of linearization to transform the original rolling dispatch model with PDEs and chance constraints into mixed-integer linear programming which is solvable by off-the-shelf solvers. The results of the case studies demonstrate that the proposed rolling dispatch strategy promotes renewable energy accommodation, enhances the flexibility, security, and efficiency of the IEGS, and mitigates the impact of renewable energy's uncertainty and volatility on the IEGS.

Regret-based multi-objective optimization of carbon capture facility in CHP-based microgrid with carbon dioxide cycling

Nowadays it is estimated that the Earth's temperature is above the standard level compared to pre-industrial time. The main reason for this issue is the burning of conventional energy resources namely oil, gas, and coal which speeds up global warming. In this concern, a CHP-based multi-energy microgrid is studied in this paper which involves heating, cooling, and electricity carriers to supply the energy demands. The proposed system is a multi-objective problem with operation cost management and emission cost reduction. In order to develop the environmental and economic aspects, a power-to-gas (P2G) technology as an environmentally friendly system is taken into account to curb CO2 emissions and achieve a sustainable function. The presence of the P2G system can minimize the emission level and improve the ability to take advantage of Notwithstanding this, the uncertain parameters originate from the thermal, electrical, and cooling loads, electricity price, and the renewable generations impose inflexibility and financial threats to the system function. In this regard, a scenario-based risk assessment approach, p-robust optimization, is applied to handle these uncertainties. The uncertainty analysis is carried out in With-p-robust, No-p-robust, With-P2G, and No–P2G models to appraise the components' performance. Results showed 11% of the operation cost increment to achieve a zero-level risk. Also, 55% of the emission cost is minimized in the presence of the P2G facility, which enhances the efficiency of the system.

Joint chance-constrained multi-objective optimal function of multi-energy microgrid containing energy storages and carbon recycling system

Nowadays, the emission of CO 2 has become a serious issue around the globe, upon which the Earth's temperature has dramatically risen. In this concern, a multi-energy CHP-based microgrid (MG) is considered to meet the multi-energy energy smart cities. As many generation units emit carbon dioxide, a power-to-gas (P2G) facility is considered in this paper to capture CO 2 emissions, upon which the environmental and economic perspectives of the system can be developed. The captured carbon dioxide can be used inside the CHP-based MG or sold to the natural gas network. Additionally, the presence of uncertainties in the loads, renewable energy resources (wind and PV), and electricity market potentially affect the flexibility and optimal function of the system, for which the joint chance constraint (JCC) approach as a scenario-based optimization method is applied for assessment of uncertain parameters. Based on the results, using the P2G facility can increase nearly 10 % of operation costs, while the emission is reduced by 50 %. Also, the applied JCC approach leads to reach the increased cost by 25 %, which shown the conservativeness behavior of the system's operator.

Power to Methane Technology for Energy Storage

Power to gas (P2G) is a technology that converts electricity into gases like H2 and O2 and is expected to meet future high-capacity energy storage needs. In this paper, we present an electric-gas system coupled with electricity and gas as well as an operational analysis to solve the energy dispatch problem in P2G technology. This paper introduces the principle of P2G technology and analyzes the advantages as well as the disadvantages of the technology. P2G technology allows for long-term, seasonal energy storage and a large amount of energy storage. However, the technology has low conversion efficiency and the risk of methane leakage when applied. A coupled electric-gas system consisting of gas-fired units and P2G facilities converts rich electricity into methane for transportation and transient storage with natural gas pipeline. Besides, natural gas power generation is economical and environmentally friendly, and the gas generator sets are responsive, which can better deepen the coupling between the power system and the natural gas system in the framework of the energy internet. This paper illustrates with examples that the P2G coupling technology has a good application prospect, and it has some implications for the future application of P2G technology.

Bi-Level Optimization Dispatch of Integrated-Energy Systems With P2G and Carbon Capture

The power-to-gas (P2G) technology transforms the unidirectional coupling of power network and natural gas network into bidirectional coupling, and its operational characteristics provide an effective way for wind and solar energy accommodation. The paper proposes a bi-level optimal dispatch model for the integrated energy system with carbon capture system and P2G facility. The upper model is an optimal allocation model for coal-fired units, and the lower model is an economic dispatch model for the integrated energy system. Moreover, the upper model is solved by transforming the model into a mixed-integer linear programming problem and calling CPLEX, and the lower model is a multi-objective planning problem, which is solved by improving the small-habitat particle swarm algorithm. Finally, the simulation is validated by the MATLAB platform, and the results show that the simultaneous consideration of carbon capture system and P2G facility improves the economics of the integrated energy system and the capacity of wind and solar energy accommodation.

Bi-level strategic bidding model for P2G facilities considering a carbon emission trading scheme-embedded LMP and wind power uncertainty

As an emerging energy storage technology for renewable power utilization, power-to-gas (P2G) requires efficient bidding strategies to increase profit. This paper proposes a bi-level strategic bidding model for P2G with the consideration of a carbon emission trading scheme (CETS), an embedded locational marginal price (LMP) and wind power uncertainty, where the upper level model aims to maximize the profit of P2G facilities and the lower level model carries out the market clearing process. Under a CETS, a P2G facility purchases electricity power according to the LMP and is assumed to sell synthetic natural gas (SNG) and carbon emission permits for revenue. The electricity market clearing process is represented by a stochastic low carbon economic dispatch (ED) model considering the CETS, P2G and wind power uncertainty. On this basis, the formulation of a CETS embedded LMP (CETS-LMP) is presented and analyzed here. The bi-level model is reformulated and converted into mixed-integer linear programming (MILP) using strong duality theory. Case studies performed on a modified PJM 5-bus system and an IEEE 118-bus system verify the effectiveness of the proposed model and demonstrate that considering the CETS can increase the profit of P2G facilities and reduce carbon emission.

Hierarchical operation planning based on carbon-constrained locational marginal price for integrated energy system

Coordinated operation of integrated energy system (IES) enables multiple energy carriers work flexibly and effectively to achieve both economic and environmental benefits. However, this process cannot be exploited without equitable and attractive incentives. This paper proposed a novel low carbon operation framework by introducing a carbon constrained locational marginal price (LMP) under carbon trading scheme. The framework is modeled as a hierarchical problem including upper supply layer and lower regional consumption layer. The upper layer aims to minimize total energy supply cost with extra carbon trading results, while the lower layer aims to maximize regional consumer surplus based on the LMP and local carbon credits. Carbon emission flow (CEF) model is employed to trace the carbon flow and calculate the emission at each layer. The strength of P2G facilities in emission mitigation is involved. Furthermore, market risks are measured by applying conditional risk at value (CVaR). Case study is carried out based on a modified IES including modified IEEE-24 electricity system and 19-bus gas system, the simulation results demonstrate the effectiveness of the proposed framework.

Volt-VAR-Pressure Optimization of Integrated Energy Systems With Hydrogen Injection

Volt-VAR optimization (VVO) has been investigated extensively in power systems. However, under the era of integrated energy systems (IES), the growing interdependencies between different energy systems complicate traditional VVO. This is further hardened by incurred gas quality problems due to the hydrogen injection in IES, produced by widely applied power-to-gas (P2G) facilitates that couple between power and gas systems. This paper develops a two-stage volt-VAR-pressure optimization (VVPO) model for PV-penetrated IES to manage the variation of system voltages while managing gas quality indices. In addition to the traditional voltage regulating devices, P2G facilities, which can mitigate fluctuating PV output via converting the surplus generation into hydrogen, are also used for voltage management. A two-stage distributionally robust optimization (DRO) based on moment information is utilized to model PV uncertainty. A semidefinite programming model is formulated and finally solved by the constraint generation algorithm. A 33-bus-20-node IES is used to verify the effectiveness of the proposed VVPO on voltage management, ensured gas quality with high economic efficiency. The proposed VVPO is applicable to injecting other green gases into gas systems while ensuring power quality and enable system operators to provide low-cost but high-quality multi-energy to customers.

Robust Optimal Operation Strategy for a Hybrid Energy System Based on Gas-Fired Unit, Power-to-Gas Facility and Wind Power in Energy Markets

Gas-fired power units (GFUs) are the best technology in recent years due to lower natural gas prices, higher energy transformation performance, and lower CO2 emission, as compared to the conventional power units (CPUs). A permanent storage facility called power-to-gas (P2G) technology can provide adaptation of ever-increasing renewable energy sources (RESs) fluctuations in power system operations, as well as reduce dependency to buy natural gas from the gas network. High investment and utilization expenditures of state-of-the-art P2G technology do not lead to economically effective operation individually. Therefore, in the present paper, an integrated GFUs-P2G-wind power unit (WPU) system is proposed to determine its optimal bidding strategy in the day-ahead energy market. A robust optimization approach is also taken into account to accommodate the proposed bidding strategy within the electricity price uncertainty environment. This problem was studied by using a case study that included a P2G facility, GFU, and WPUs to investigate the effectiveness and capability of the proposed robust bidding strategy in the day-ahead energy market. Simulation results indicate that the obtained profit increase by introducing the integrated energy system, and the P2G facility has a significant effect on participating GFUs, which have gas-consumption limitations in order to achieve maximum profit. Moreover, as it can be said, the amount of purchased natural gas is decreased in the situations, which do not have any gas-consumption limitations. Furthermore, the proposed system’s operation in the robust environment provides more robustness against electricity price deviations, although it leads to lower profit. In addition, deploying P2G technology causes about 1% incrementation in the introduced system profit.

Coordinated Bidding Strategy of Wind Farms and Power-to-Gas Facilities Using a Cooperative Game Approach

Power-to-gas (P2G) technology is an effective way to provide additional flexibility to electricity systems with high penetration of renewable energy. Effective P2G bidding strategies in electricity markets can bring in arbitrage opportunities. This article proposes a coordinated bidding strategy for wind farms and P2G facilities using a cooperative game approach. A coordination framework for optimizing the profit of wind farms and P2G facilities is presented, in which wind power participates in day-ahead, real-time and reserve markets, and the P2G facilities participate in day-ahead and reserve markets for arbitrage. Wind farms strategically purchase reserve to avoid high imbalance penalties. As a coalition, wind farms can provide energy to P2G facilities and receive reserve capacity in return. The coordinated bidding strategy is modeled on stochastic programming to maximize the expected joint profit of wind farms and P2G facilities. Nucleolus and Shapley-value based methods are proposed to allocate profits to each player in the coalition. Numerical results based on real world market data demonstrate that the proposed bidding strategy can increase the profits of both wind farms and P2G facilities. Strategically purchasing reserve can reduce the imbalance penalties of wind farms, and participating in reserve markets of P2G facilities can increase profit.

Environment-friendly and economical scheduling optimization for integrated energy system considering power-to-gas technology and carbon capture power plant

To mitigate global warming, CO2 emission reduction has become an urgent issue in the energy sector. In China, coal-to-gas, carbon capture and renewable energy utilization are important measures available among various low-carbon plans. However, inadequate gas supply, unclear utilization methods of captured CO2, and curtailment of excessive wind and solar power have hampered the effective implementation of the above measures. To solve this issue, this paper presents a coupling model considering power to gas (P2G) technology and carbon capture power plants (CCPP), and extends it into an integrated energy system (IES) including electricity, thermal and gas, then proposes an economic and environment-friendly scheduling model at a high wind power penetration level. Through the coupling of CCPP and P2G in IES, most of CO2 emitted by the system can be captured and sent to the P2G facility to produce synthesized gas, which provides a new idea of utilizing CO2 rather than storage. The synthetic gas can be provided to the system to reduce the external gas dependency. In addition, the simulation results also show that the ability of the system to absorb renewable energy is significantly enhanced with the presence of CCPP and P2G.

Integrated operation optimization for CCHP micro-grid connected with power-to-gas facility considering risk management and cost allocation

According to the multi-energy coupling characteristics of CCHP (combined cooling, heating and power) micro-grid and P2G (power-to-gas) facility, their integration provides a new perspective to enhance energy efficiency and clean production. In this paper, an integration framework of CCHP-P2G system is proposed by attaching a P2G facility to a CCHP micro-grid. Consequently, the operation optimization models for CCHP, P2G and CCHP-P2G are constructed based on an improved risk explicit interval parameter programming (REIPP) approach. Firstly, the uncertainties of wind power outputs, electricity and natural gas prices are modeled as interval numbers. Secondly, the risk objective functions are formulated with the interval numbers etc. Thirdly, the REIPP based operation optimization models for CCHP, P2G and CCHP-P2G are presented by employing the risk objective functions, which pursue risk minimization while considering operational cost control. Finally, the REIPP based models are further improved by applying fuzzy theory to reflect the impact of different risk attitudes on the operation strategies. Moreover, considering that CCHP and P2G may have different investors, a Shapley-value cost allocation mechanism is proposed based on the solutions from the improved REIPP (IREIPP) based models. Simulations have verified the effectiveness of our proposed integration framework, IREIPP approach and Shapley-value cost allocation mechanism.

Risk-Loss Coordinated Admissibility Assessment of Wind Generation for Integrated Electric-Gas Systems

Due to the widely deployment of gas-fired units and the emerging power-to-gas (P2G) technologies, the interdependencies between power systems and gas systems have been enhanced, yet the impacts on the ability of accommodating the uncertain and variable wind generation are unclear. On one hand, the regulation capability of gas-fired units might be restricted due to pipeline congestion or gas supply shortage; on the other hand, the P2G facilities could operate as interruptible electrical loads to enhance the operational flexibility of the power network. This paper aims to revisit the wind generation admissibility assessment problem in view of integrated electric-gas systems. The overall model is established according to the two-stage robust optimization framework. By introducing the stepwise penalty coefficients for power shortage and surplus, the risk preference of the operator can be reflected. The mixed integer linear programming-based approximation methods is adopted to tackle the computational challenging Weymouth equation in the gas network, which requires an additional column-and-constraint (C&CG) loop to solve the second-stage max-min problem, other than the common one to coordinate the first- and second-stage problems, resulting in a nested C&CG algorithmic structure. The effectiveness of the proposed model and solution methods are validated by the simulation results.

Decentralized Privacy-Preserving Operation of Multi-Area Integrated Electricity and Natural Gas Systems With Renewable Energy Resources

With the proliferation of natural gas combined cycle units, the modern energy infrastructure has evolved into a coupled electricity and natural gas system, which often encompasses multiple large-scale and geographically-diverse energy areas. The similarity in electricity and natural gas consumption profiles in coupled systems gives rise to critical mandates for the coordinated optimization of electricity and natural gas operation. This paper presents a decentralized optimization framework, which considers wind energy and power-to-gas (P2G) technologies in the operation of integrated multi-area electricity and natural gas transmission system (IEGTS). First, a comprehensive optimal dispatch model is established for the multi-area IEGTS in a centralized manner where bi-directional flows of electricity and natural gas among multi-areas are optimized considering the stochastic nature of wind energy. In particular, a linearized transient-state gas flow model under mild assumptions is proposed to represent the dynamic characteristics of the natural gas sector. The centralized optimization problem is decomposed into a set of computationally-tractable subproblems that are solved independently in individual areas. The alternating direction multiplier method is employed to achieve a rapidly convergent solution while preserving the privacy of operation data shared among participating areas. Finally, case studies are carried out on two multi-area IEGTS with multiple wind generation scenarios which demonstrate the computational performance of the proposed method with P2G facilities operating in variable conditions.

Economic dispatch model for wind power integrated system considering the dispatchability of power to gas

Power-to-gas (P2G) technology opens up another perspective for effective, long-term, large-scale energy storage, so that it can promote large-scale wind power integration. Under this background, this study introduces P2G technology into the economic dispatch model of wind power integrated systems. First, an uncertainty interval model of wind power is built based on the probability distribution of wind power prediction error. Then, considering P2G's function of absorbing surplus wind power and undertaking downward spinning reserve, the factors that influence P2G's ability in enhancing the accommodation of wind power are analysed through theoretical derivation. Consequently, the relationship between the maximum wind power integration and the power delivered to the P2G facilities under a given capacity of P2G can be further understood. Moreover, an economic dispatch model incorporating wind power, P2G facilities and battery energy storage systems is established and a feasible region relaxation algorithm is proposed to deal with the non-smooth functions in the proposed model. Case studies are conducted on a modified IEEE 39-bus system. The results verify the correctness of theoretic analysis and show that the proposed model can help to reduce wind power curtailment and enhance the security and economy of the power system.

Optimal Operation Strategy for Integrated Natural Gas Generating Unit and Power-to-Gas Conversion Facilities

A scenario-based stochastic decision-making model is proposed in this paper to determine the optimal strategy for the operation of integrated natural gas generating unit (NGG) and power-to-gas conversion (P2G) facilities in energy and regulation markets. Using the proposed strategy, the coordination of NGG and P2G facilities will provide a higher market payoff than that of independent NGG and P2G participation. The market price uncertainty is simulated in multiple scenarios using the Latin hypercube sampling method and the conditional value-at-risk strategy is adopted for evaluating the financial risks introduced by price uncertainties. The optimal bidding strategy is developed for both P2G and NGG operations and the Shapley-value method is employed to allocate the market payoff among NGG and P2G facilities. A case study which is based on the Pennsylvania, New Jersey, and Maryland market data is employed to verify the effectiveness of the proposed model and examine the characteristics of the proposed bidding strategy for the optimal operation of integrated NGG and P2G facilities.

The effect of electricity markets, and renewable electricity penetration, on the levelised cost of energy of an advanced electro-fuel system incorporating carbon capture and utilisation

Abstract Power-to-Gas (P2G) is a technology that converts electricity to gas and is termed gaseous fuel from non-biological origin. It has been mooted as a means of utilising low-cost or otherwise curtailed electricity to produce an advanced transport fuel, whilst facilitating intermittent renewable electricity through grid balancing measures and decentralised storage of electricity. This paper investigates the interaction of a 10MWe P2G facility with an island electricity grid with limited interconnection, through modelling electricity purchase. Three models are tested; 2016 at 25% renewable electricity penetration and 2030 at both 40% and 60% penetration levels. The relationships between electricity bid price, average cost of electricity and run hours were established whilst the levelised cost of energy (LCOE) was evaluated for the gaseous fuel produced. Bidding for electricity above the average marginal cost of generation in the system (€35–50/MWeh) was found to minimise the LCOE in all three scenarios. The frequency of low-cost and high-costs hours, analogous to balancing issues, increased with increasing shares of variable renewable electricity generation. However, basing P2G systems on low-cost (less than €10/MWeh) hours alone (999 h in 2030 at 60% renewable penetration) is not the path to financial optimisation; it is preferential to increase the run hours to a level that amortises the capital expenditure.