Synthesis Of Energy Supply Systems Research Articles

Tackling thermal integration in the synthesis of polygeneration systems for buildings

A novel methodology is proposed for the synthesis of polygeneration systems in tertiary sector buildings with detailed thermal integration. The methodology involves a systematic approach that combines Pinch Analysis, mathematical programming, and the definition of a superstructure with thermal flexibility whereby mass flows can exchange heat in various temperature intervals. With the detailed characterization of the thermal energy flows associated with the thermal energy technologies and services to be supplied to the building, the optimization procedure provides a more realistic system configuration, ensures that thermodynamic principles are satisfied, and allows for synergies and potential benefits to emerge. The methodology is first introduced through a simple example of a gas engine-based energy system, highlighting the necessity of a detailed characterization of the hot and cold flows regarding their quantity and quality levels. Then, the approach is applied to the case study of a Brazilian university hospital that requires electricity, steam, hot water, and chilled water. The optimization is formulated as a multi-period mixed integer linear programming model that minimizes the total annual cost of installing and operating the system using local-based data. The results show the technical and economic interest of deploying cogeneration gas engines to cover electricity and thermal energy services. Besides, a strong synergy is observed between the cogeneration gas engine and the single-effect absorption chiller. Thus, it is demonstrated how a preliminary analysis of thermal integration opportunities must be an integral part of the optimal synthesis of energy supply systems.

SPREAD – Exploring the decision space in energy systems synthesis

A method is presented to systematically analyze the decision space in the synthesis of energy supply systems. Commonly, synthesis problems are solved by mathematical optimization yielding a single optimal design. However, optimization is based on a model which never represents reality to perfection. Thus, the designer will be forced to revise parts of the optimal solution. We therefore support the design process by automatically identifying important features of good solutions. For this purpose, we analyze near-optimal solutions. To explore the decision space, we minimize and maximize both the number and the capacity of units while keeping the costs within a specified range. From this analysis, we derive insight into correlations between decisions. To support the decision maker, we represent the range of good design decisions and their correlations in the flowsheet of the energy system. The method is illustrated for the synthesis of an energy system in the pharmaceutical industry.

The optimum is not enough: A near-optimal solution paradigm for energy systems synthesis

An optimisation-based decision support methodology is presented for the synthesis of energy supply systems on the conceptual level. Previous work in this field has tended to focus on the generation of the single optimal solution. However, given that mathematical models never perfectly represent the real world and that planners are often not aware of all practical constraints, the mathematically optimal solution usually only approximates the real-world optimum, and thus has only limited significance. The presented approach therefore exploits the near-optimal solution space for more rational synthesis decisions. For this purpose, integer-cut constraints are employed to systematically generate a set of near-optimal solutions alongside the optimal solution. In place of the traditional analysis of the single optimal solution, we analyse the generated solution set to identify common features (the “must-haves”) and differences (the “real choices”) among the good solutions, and features not observed in any of the generated solutions (the “must-avoids”). This approach provides valuable insights into the synthesis problem and opens up a wide range of rational decision options.The proposed concept is applied to three different real-world problems at the industrial, district, and urban scale. For all three test cases, many near-optimal solutions are identified with different equipment configurations but similar objective function values. Thus, a ranking of the identified solutions strictly based on a single objective value is not productive. Instead, we show that the near-optimal solutions analysis supports the decision process to identify a wider basis of system options, which may be consulted upon to reach rational synthesis decisions.

Optimal synthesis of energy supply systems for remote open pit mines

The primary motivation underlying the proposal of polygeneration systems for mine sites is to increase the efficient use of natural resources by combining different technologies and energy resources while satisfying energy service demands. For many mineral producers, particularly in Canada's mining extremes of climate and depth, energy in support of mineral production can be the second largest cost center after labor. A generic methodology is proposed for the design of energy supply systems in mine sites, based on a search for the minimum discounted cost of energy supplied for all feasible different plant configurations. These configurations can be represented within a connectivity matrix which corresponds to a network representation. A Mixed Integer Programming formulation is set out for the multiperiod synthesis and operational planning problem. This is characterized by i) binary variables for the selection of technologies, ii) integer variables for the determination of the number of units installed, and iii) by continuous variables for the representation of energy and economic flows. Through the integration of particular energy supply strategies matching specific mine circumstances (on-grid, remote, degree days, etc) and consideration of technologies that improve energy efficiency, hitherto not considered new technologies and demand management systems or new perspectives on optimal mine site energy supply can be investigated. Some of these investigations identify the economic conditions through which biomass energy feedstocks should be used, for direct heat production, for gasification and providing for Fischer–Tropsch syndiesel manufacture. As well as integrating demand from mobile diesel-fueled plant into an optimization procedure this analysis shows how the techniques can be used to explore economic conditions of threshold prices for biomass (purpose-grown biomass and peat are considered herein) and trucked-in diesel. The methodology also allows for electricity and syngas storage and diesel and biomass bunkering. Within the paper the energy demands for a remote, open pit mining operation located in Northern Ontario are considered as a case study to illustrate the technique and investigations. As expected, for mines close to electricity, natural gas, and diesel distribution infrastructures, the optimal choice is to connect. When a constraint is applied specifying that connection is not possible, as would be for the case exemplified, the optimal choice includes some of the more exotic options for mine site energy supply.

Structural Synthesis of Energy Supply Systems by Multiobjective Optimization Approach

Based on multiobjective optimization approach, a planning method is proposed for structural synthesis of energy supply systems, by which types, numbers and capacities of systems equipment can be determined rationally from economic, energy saving and environmental viewpoints. Assuming a super-structure system for an office building, the economically optimal system is synthesized with the hybrid structure of electric and gas-consumed equipments. Through the trade-off analysis, it is also clarified that by permitting the total cost increase up to 4%, 22% primary energy and 18% CO2 emission reductions can be achieved, where high efficiency electric-consumed equipments are installed preferentially.