Search Results (6)

With the growing significance of hydrogen in the global energy transition, research on its pricing mechanisms has become increasingly crucial. Focusing on hydrogen markets predominantly supplied by electrolytic production, this study proposes a nodal marginal hydrogen price decomposition algorithm that explicitly incorporates the time-delay dynamics inherent in hydrogen transmission. A four-dimensional price formation framework is established, comprising the energy component, network loss component, congestion component, and time-delay component. To address the nonconvex optimization challenges arising in the market-clearing model, an improved second-order cone programming method is introduced. This method effectively reduces computational complexity through the reconstruction of time-coupled constraints and reformulation of the Weymouth equation. On this basis, the analytical expression of the nodal marginal hydrogen price is rigorously derived, elucidating how transmission dynamics influence each price component. Empirical studies using a modified Belgian 20-node system demonstrate that the proposed pricing mechanism dynamically adapts to load variations, with hydrogen prices exhibiting a strong correlation with electricity cost fluctuations. The results validate the efficacy and superiority of the proposed approach in hydrogen energy market applications. This study provides a theoretical foundation for designing efficient and transparent pricing mechanisms in emerging hydrogen markets. Full article

The demand for thermal power generation from natural gas has increased globally due to its cleaner burning properties compared to other fossil fuels. Optimizing the gas flow through the network to meet this demand is challenging due to the nonconvex Weymouth equation constraining gas flow and nodal pressures in pipelines. Traditional methods for addressing this nonconvexity lead to significant approximation errors or high operational costs. This study poses the Weymouth constraint as a Mathematical Programming with Complementarity Constraints (MPCC) for an optimal gas flow problem. The complementarity constraints reformulate the discontinuous sign function using binary-behaving continuous variables. This MPCC-based approach avoids solving mixed-integer programming problems while enhancing the accuracy of conventional linear and second-order approximations. Testing the approach on various interconnected systems, including Colombia’s national gas transportation grid, demonstrated significant reductions in Weymouth approximation errors, thereby supporting effective optimization for interconnected networks. Full article

Environmental demands around the world have led to an increasing interest in natural gas due to its advantages over other hydrocarbons used in power generation, which has led to the search for the best way to solve the transportation problem associated with this resource. In this paper, we propose a methodology that allows us to address the non-convexity related to the Weymouth equation that makes the optimization problem so difficult. The mentioned equation, in charge of relating the flows through the pipelines and the pressures at the nodes, is characterized by having a discontinuity in the form of a sign function. The proposal of this work is based on the use of Mathematical Programs with Complementarity Constraints (MPCC) to achieve a good approximation since it allows make certain continuous variables to behave as discrete variables in such a way that it is possible to avoid having to pose a mixed integer programming problem and this one. This approach showed a smaller approximation error (or at least equal) with other approximations used in the state of the art when tested in three different networks: one of 8 nodes, one of 48 nodes tested in other related works, and one of 63 nodes representing the Colombian natural gas transportation system. Full article

Under the background that the high penetration of renewable energy generation, which mainly consists of wind power, will have a significant impact on electric power systems due to the volatility and uncertainty of renewable energy, energy systems with gas–electric coupling and interconnections have been widely studied to accommodate renewable energy generation. This paper proposes a two-stage chance-constrained coordinated operation model of an integrated gas–electric system and fully considers the uncertainty and high penetration of wind power. The Taylor series expansion method is used to linearize the Weymouth gas flow equation of a natural gas system and finally obtains a mixed integer linear programming model. Case studies show the effectiveness of the integrated energy system for peak shaving, valley filling, and promoting wind power accommodation. The proposed model ensures the consumption of wind power generation and also reduces the operation cost by about 0.7%. Full article

Coordinated multi-carrier energy systems with natural gas and electricity energies provide specific opportunities to improve energy efficiency and flexibility of the energy supply. The interdependency of electricity and natural gas networks faces multiple challenges from power and gas flow in corresponding feeders and pipes and connection points between two infrastructures’ points of view. However, the energy hub concepts as the fundamental concept of multi-carrier energy systems with multiple conversion, storage, and generation facilities can be considered as a connection point between electricity and gas grids. Hence, this paper proposes an optimal operation of coordinated gas and electricity distribution networks by considering interconnected energy hubs. The proposed energy hub is equipped with combined heat and power units, a boiler, battery energy storage, a heat pump, and a gas-fired unit to meet the heating and electrical load demands. The proposed model is formulated as a two-stage scenario-based stochastic model aiming to minimize total operational cost considering wind energy, electrical load, and real-time power price uncertainties. The proposed integrated energy system can participate in real-time and day-ahead power markets, as well as the gas market, to purchase its required energy. The AC-power flow and Weymouth equation are extended to describe power and gas flow in feeders and gas pipelines, respectively. Therefore, a realistic model for the integrated electricity and gas grids considering coupling constraints is satisfied. The proposed model is tested on the integrated energy system and consists of a 33-bus electrical network and a 6-node gas grid with multiple interconnected energy hubs, where the numerical results reveal the effectiveness of the proposed model. Full article

This paper proposes and implements a long-term deterministic capacity expansion model for the co-optimization of electric and natural gas infrastructures. It determines the required investments in generation units, transmission lines and pipelines for meeting future demands, while representing electricity and natural gas flows using DC Power Flow and Weymouth equations, respectively. A Mixed Integer Nonlinear Programming (MINLP) problem is developed, from which a linearized version is derived. A 26 node integrated gas-electric system for the Eastern Region of the United States is used to demonstrate the model’s capabilities. Results show that the model provides an accurate operational representation of the integrated system, and, therefore, enhances the expansion planning process. Full article