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Multi-energy carriers system (MECS), in which diverse energy carriers and different energy systems interact together, has drawn the interest of many researchers in recent years. However, the optimal economic operational model of the MECS is a nonlinear, multi-variable, and multi-period problem, of which it is difficult to find the solution because several different energy flows are integrated in the system. To this end, three interest bodies in the MECS were investigated, which included the energy provider, the energy facilitator, and the energy consumer, and a hierarchical optimal economic operation strategy was then presented. A hybrid optimization strategy combining the swarm intelligence algorithm and interior point method was developed taking advantage of the merits of each method. Case studies were conducted to verify the effectiveness of the proposed hierarchical optimal economic operation strategy, whereby demonstrating that the proposed strategy can achieve rational energy allocation and decrease the energy cost in the MECS compared with traditional energy systems.

National climate protection goals require the emission reduction in municipal energy supply systems. Those systems include energy conversion units like heatings, energy storages, and grids for electricity, gas, and heat. This paper presents a mixed-integer linear optimization model for the integrated and multi-modal planning of such municipal energy systems to reach a defined CO 2 emission limit with the least-cost system design. The exemplary application of the model to a study case with 3900 buildings shows that the flexible hybrid energy system resulting without emission restrictions gradually transforms into an inflexible system solely relying on pellet heaters and photovoltaic units when tightening the emission limit by just a few percentage points. • Integrated and multi-modal design conception for municipal energy supply systems. • Optimization of energy conversion units, storages, and electric, heat, and gas grid. • Binary grid investment decisions, energy storages, and two-stage optimization added. • Economically optimal system combines multi-valent central and decentral supply. • Tightening of emission reduction target can lead to less flexible system design. [ABSTRACT FROM AUTHOR]

• Accommodating electricity from renewable sources leads to volatile natural gas off-take. • Power-to-gas technologies strengthen the link between the power and natural gas system. • We model joint scheduling decisions in the electric power system and natural gas system. • We present a case study of a future Belgian power and natural gas system. The possibly increasing volatile gas off-take from gas-fired power plants to accommodate volatile renewable generation in combination with the integration of power-to-gas (P2G) warrants further study into the operation of a coupled electrical power and natural gas system. Therefore, this paper presents and validates a novel operational model comprising both the electrical power and gas systems. Model improvements include (i) the use of zonal gas loads in addition to nodal loads, (ii) ramp rates for conventional gas production facilities and, (iii) an improved detailed technological model of P2G units, which all increase the realism of the obtained results. Results of several small-scale case studies illustrate the relevance of these model additions. In addition, a case study inspired by the Belgian electrical power and gas systems shows that the Belgian gas network has abundant capacity to integrate a possibly volatile injection of synthetic methane from P2G. This model may be used by electricity and gas transmission system operators to study the interaction between their systems and inform policy makers and regulators. [ABSTRACT FROM AUTHOR]

Multi-energy carriers system (MECS), in which diverse energy carriers and different energy systems interact together, has drawn the interest of many researchers in recent years. However, the optimal economic operational model of the MECS is a nonlinear, multi-variable, and multi-period problem, of which it is difficult to find the solution because several different energy flows are integrated in the system. To this end, three interest bodies in the MECS were investigated, which included the energy provider, the energy facilitator, and the energy consumer, and a hierarchical optimal economic operation strategy was then presented. A hybrid optimization strategy combining the swarm intelligence algorithm and interior point method was developed taking advantage of the merits of each method. Case studies were conducted to verify the effectiveness of the proposed hierarchical optimal economic operation strategy, whereby demonstrating that the proposed strategy can achieve rational energy allocation and decrease the energy cost in the MECS compared with traditional energy systems. [ABSTRACT FROM AUTHOR]