Sustainable Biomethane Integration into Latvia’s Natural Gas Network

Risk-constrained non-probabilistic scheduling of coordinated power-to-gas conversion facility and natural gas storage in power and gas based energy systems

Greece’s path toward climate neutrality, aligned with the European Green Deal and REPowerEU strategies, relies on the rapid expansion of renewable energy sources combined with the development of energy storage capacity to ensure system resilience and reduce dependence on natural gas. This study uses the LEAP-NEMO model to assess the role of seasonal hydrogen storage in achieving national energy and climate targets. The results confirm that hydrogen storage allows for a higher penetration of renewable energy sources, thereby reducing curtailments and contributing to the early phasing out of natural gas from the country’s energy mix. However, its low round-trip efficiency and limited short-term response make it unsuitable for short-term balancing, highlighting the need for complementary storage technologies. Furthermore, reduced dependence on gas imports enhances energy security, allowing Greece to meet demand with competitive domestic resources, mitigating exposure to the high volatility of global market. The novelty of this work lies in the updated analysis of the Greek electricity system through an energy model framework, applied for the first time in the country, and in the demonstration of the role of hydrogen as a factor for the future scaling-up of renewable energy sources.

A “lifeline out of the <scp>COVID</scp>‐19 crisis”? An ecofeminist critique of the European Green Deal

The variability in the generation dispatch of the natural gas generation units will lead to fluctuation in natural gas demand profile that could further jeopardize the security of the natural gas network. The coordinated operation of electricity and natural gas infrastructure systems would help to improve the security and reliability measures in both infrastructure systems and mitigate the risk of demand curtailment. The electricity and natural gas network operation problems are non-convex mixed-integer nonlinear programming problems that are hard to solve in polynomial time. The non-convex feasible regions are formed by the Weymouth constraint and the introduced binary commitment decision variables in the natural gas and electricity network operation problems, respectively. This paper utilized a sparse semidefinite programming (SDP) relaxation to procure the optimal solution for the coordinated operation of electricity and natural gas networks. The presented algorithm leverages the sparseness of the natural gas network to construct several small matrices of lifting variables that are used to form a tight and traceable SDP relaxation. A set of valid constraints that tighten the relaxation ensures the exactness of the solution procured from the relaxed problem. The effectiveness of the presented approach is shown in case studies.

The variability in the generation dispatch of the natural gas generation units will lead to fluctuation in natural gas demand profile that could further jeopardize the security of the natural gas network. The coordinated operation of electricity and natural gas infrastructure systems would help to improve the security and reliability measures in both infrastructure systems and mitigate the risk of demand curtailment. The electricity and natural gas network operation problems are non-convex mixed-integer nonlinear programming problems that are hard to solve in polynomial time. The non-convex feasible regions are formed by the Weymouth constraint and the introduced binary commitment decision variables in the natural gas and electricity network operation problems, respectively. This paper utilized a sparse semidefinite programming (SDP) relaxation to procure the optimal solution for the coordinated operation of electricity and natural gas networks. The presented algorithm leverages the sparseness of the natural gas network to construct several small matrices of lifting variables that are used to form a tight and traceable SDP relaxation. A set of valid constraints that tighten the relaxation ensures the exactness of the solution procured from the relaxed problem. The effectiveness of the presented approach is shown in case studies.

This paper addresses the coordinated operation of the electricity and natural gas networks considering the line pack flexibility in the natural gas pipelines. The problem is formulated as a mixed integer linear programming problem. The objective is to minimize the operation cost of the electricity and natural gas networks considering the price of the natural gas supply. Benders decomposition is used to solve the formulated problem. The master problem minimizes the startup and shutdown costs as well as the operation cost of the thermal units other than the gas-fired generation units in the electricity network. The first subproblem validates the feasibility of the decisions made in the master problem in the electricity network. And if there is any violation, feasibility Benders cut is generated and added to the master problem. The second subproblem ensures the feasibility of the decisions of the master problem in the natural gas transportation network considering the line pack constraints. The last subproblem ensures the optimality of the natural gas network operation problem considering the demand of the gas-fired generation units and line pack. The nonlinear line pack and flow constraints in the feasibility and optimality subproblems of natural gas transportation network are linearized using Newton-Raphson technique. The presented case study shows the effectiveness of the proposed approach. It is shown that leveraging the stored gas in the natural gas pipelines would further reduce the total operation cost.

Optimal energy pricing for integrated natural gas and electric power network with considerations for techno-economic constraints

The interdependence between the natural gas (NG) and electricity networks as two primary energy carriers has attracted significant attention in smart grids. In this paper, a multi-objective framework is proposed for the coordinated operation of NG and electricity networks, addressing the economic, dynamic security of electricity network, as well as the security of the NG network. The proposed electricity network includes thermal generation facilities such as NG-fired generation units as well as the microgrid aggregators as price responsive demands. The $\varepsilon $ -constraint method is employed to solve the proposed multi-objective problem and the index of critical clearing time is employed to assess the dynamic stability of the electricity network. The effectiveness of the proposed framework is addressed in a case study integrating the Belgian gas network and modified IEEE 24-bus test system. The proposed coordinated operation of electricity and NG networks is benchmarked against the independent operation of individual networks.

Over the last decades, electricity generation from natural gas has substantially increased, mostly driven by low natural gas prices due to fracturing and lower extraction costs. The geographic distance between natural gas resources and load centers calls for a holistic tool for joint expansion of power systems and natural gas networks. In this paper, a Dynamic Stochastic Joint Expansion Planning (DSJEP) of power systems and natural gas networks is proposed to minimize the investment and operational costs of power and natural gas systems. Electrical and natural gas storage (ENGS) are considered as an option for decision‐makers in the DSJEP problem. The proposed approach takes into account long‐term uncertainties in natural gas prices and electric and natural gas demands through scenario realizations. In dynamic planning, more scenario needs more time for computation; therefore, scenario reduction is implemented to eschew unnecessary scenarios. The proposed formulation is implemented on a four‐bus electricity system with a five‐node natural gas network. To demonstrate the efficiency and scalability of the proposed approach, it is also tested on the IEEE 118‐bus system with a 14‐node natural gas network. The numerical results demonstrate that ENGS can reduce the total investment cost, up to 52% in the test cases, and operational cost, up to 3%. In this paper, co‐planning of power and natural gas systems considering natural gas and electrical storage is represented. Also, electrical and natural gas load growth uncertainties are taken into account to model the real situations. The purpose of the model is to minimize investing and operational costs.

Electricity and natural gas networks are critical infrastructure for society, but the robustness of coupled networks has not been evaluated, even though both systems have strong interactions. This article proposes a novel graph theory‐based methodology to assess the structural robustness of the coupled natural gas and electricity transmission networks in Spain while considering their interdependencies. Cascading failures were simulated in 22 case studies with different topologies, and the performance against random failures was evaluated. The results show that the investment programme proposed by both network operators ultimately improves the robustness of the interdependent electricity and natural gas infrastructure in Spain compared to the current system.

The interdependencies of power systems and natural gas networks have increased due to the additional installations of more environmental-friendly and fast-ramping natural gas power plants. The natural gas transmission network constraints and the use of natural gas for other types of loads can affect the delivery of natural gas to generation units. These interdependencies will affect the power system security and economics in day-ahead and real-time operations. Hence, it is imperative to analyze the impact of natural gas network constraints on the security-constrained unit commitment (SCUC) problem. In particular, it is important to include natural gas and electricity network transients in the integrated system security because the impacts of any disturbances propagate at two distinctly different speeds in natural gas and electricity networks. Thus, analyzing the transient behavior of the natural gas network on the security of natural gas power plants would be essential as these plants are considered to be very flexible in electricity networks. This paper presents a method for solving the SCUC problem considering the transient behavior of the natural gas transmission network. The applicability of the presented method and the accuracy of the proposed solution are demonstrated for the IEEE 118-bus power system, which is linked with the natural gas transmission system and the results are discussed in this paper.

This paper presents an approach to determine the vulnerable components in the electricity and natural gas networks of an islanded microgrid that is exposed to deliberate disruptions. The vulnerable components in the microgrid are identified by solving a bi-level optimization problem. The objective of the upper-level problem (the attacker’s objective) is to maximize the expected operation cost of microgrid by capturing the penalties associated with the curtailed electricity and heat demands as a result of the disruption. In the lower-level problem, the adverse effects of disruptions and outages in the electricity and natural gas networks are mitigated by leveraging the available resources in the microgrid (the defender’s objective). The uncertainties in the electricity and heat demand profiles were captured by introducing scenarios with certain probabilities. The formulated bi-level optimization problem provides effective guidelines for the microgrid operator to adopt the reinforcement strategies in the interdependent natural gas and electricity distribution networks and improve the resilience of energy supply. The presented case study shows that as more components are reinforced in the interdependent energy networks, the reinforcement cost is increased and the expected operation cost as a result of disruption is decreased.

A planning approach for reducing the impact of natural gas network on electricity markets

The interactions of the natural gas (NG) network and the electricity system are increased by using gas‐fired generation units, which use NG to produce electricity. There are various uncertainty sources such as the forced outage of generating units or market price fluctuations that affect the economic operation of both NG and electricity systems. This study focuses on the steady‐state formulation of the integrated NG transmission grid and electricity system by considering the uncertainty of electricity market price based on information gap decision theory. The higher and lower costs than the expected cost originated from the fluctuations of electricity market price are modelled by the robustness and opportunity functions, respectively. The objective is to minimise the cost of zone one while satisfying the constraints of two interdependent systems, which can obtain revenue from selling power to its connected zones in short‐term scheduling. The capability of the proposed method is demonstrated by applying it on a 20‐node NG network and IEEE RTS 24‐bus. The proposed short‐term coordination between NG and electricity infrastructures is solved and discussed.

Transporting green hydrogen by existing natural gas networks has become a practical means to accommodate curtailed wind and solar power. Restricted by pipe materials and pressure levels, there is an upper limit on the hydrogen blending ratio of hydrogen-enriched compressed natural gas (HCNG) that can be transported by natural gas pipelines, which affects whether the natural gas network can supply energy safely and reliably. To this end, this paper investigates the effects of the intermittent and fluctuating green hydrogen produced by different types of renewable energy on the dynamic distribution of hydrogen concentration after it is blended into natural gas pipelines. Based on the isothermal steady-state simulation results of the natural gas network, two convection–diffusion models for the dynamic simulation of hydrogen injections are proposed. Finally, the dynamic changes of hydrogen concentration in the pipelines under scenarios of multiple green hydrogen types and multiple injection nodes are simulated on a seven-node natural gas network. The simulation results indicate that, compared with the solar-power-dominated hydrogen production-blending scenario, the hydrogen concentrations in the natural gas pipelines are more uniformly distributed in the wind-power-dominated scenario and the solar–wind power balance scenario. To be specific, in the solar-power-dominated scenario, the hydrogen concentration exceeds the limit for more time whilst the overall hydrogen production is low, and the local hydrogen concentration in the natural gas network exceeds the limit for nearly 50% of the time in a day. By comparison, in the wind-power-dominated scenario, all pipelines can work under safe conditions. The hydrogen concentration overrun time in the solar–wind power balance scenario is also improved compared with the solar-power-dominated scenario, and the limit-exceeding time of the hydrogen concentration in Pipe 5 and Pipe 6 is reduced to 91.24% and 91.99% of the solar-power-dominated scenario. This work can help verify the day-ahead scheduling strategy of the electricity-HCNG integrated energy system (IES) and provide a reference for the design of local hydrogen production-blending systems.