Targeting the optimal integration of steam networks: Mathematical tools and methodology

An Optimisation Approach for Long-Term Industrial Investment Planning

The industrial sector has a large presence in world energy consumption and CO2 emissions, which has made it one of the focal points for energy and resource efficiency studies. However, large investments are required to retrofit existing industrial plants, which remains the largest barrier to implementing energy saving solutions. Process integration methods can be used to identify the best investments to improve the efficiency of plants, yet their timing remains to be answered using an optimisation approach. Even more critically, such decisions must also account for future investments to avoid stranded or regretted investments. This paper presents a method incorporating investment planning over long time horizons in the framework of process integration. The time horizon is included by formulating the problem using multiple investment periods. Investment planning is conducted using a superstructure approach, which permits both commissioning and decommissioning of units in the beginning of each period. The method is applied to a large case study, with an industrial cluster neighbouring an urban centre to also explore options of heat integration between industries and cities. Compared to the business-as-usual operation, optimal investment planning improves the operating cost of the system by 27% without budget constraints and 16–26% with constraints on budget and investment periods, which is reflected as an increase in net present value and a decrease in CO2 emissions. In all cases, the operating cost benefits pay off the investment in less than two years. The present work is efficient in finding energy saving solutions based on the interest of industries. This method adds additional perspectives in the decision-making process and is adaptable to various time horizons, budgets and economic constraints.

Incorporating Location Aspects in Process Integration Methodology

The large potential for waste resource and heat recovery in industry has been motivating research toward increasing efficiency. Process integration methods have proven to be effective tools in improving industrial sites while decreasing their resource and energy consumption; however, location aspects and their impact are generally overlooked. This paper presents a method based on process integration, which considers the location of plants. The impact of the locations is included within the mixed integer linear programming framework in the form of heat losses, temperature and pressure drop, and piping cost. The objective function is selected as minimisation of the total cost of the system excluding piping cost and ϵ -constraints are applied on the piping cost to systematically generate multiple solutions. The method is applied to a case study with industrial plants from different sectors. First, the interaction between two plants and their utility integration are illustrated, depending on the piping cost limit which results in the heat pump and boiler on one site being gradually replaced by excess heat recovered from the other plant. Then, the optimisation of the whole system is carried out, as a large-scale application. At low piping cost allowances, heat is shared through high pressure steam in above-ground pipes, while at higher piping cost limits the system switches toward lower pressure steam sharing in underground pipes. Compared to the business-as-usual operation of the sites, the optimal solution obtained with the proposed method leads to 20% reduction in the overall cost of the system, including the piping cost. Further reduction in the cost is possible using a state of the art method but the technical and economic feasibility is not guaranteed. Thus, the present work provides a tool to find optimal industrial symbiosis solutions under different investment limits on the infrastructure between plants.

A Review of Evaluation, Optimization and Synthesis of Energy Systems: Methodology and Application to Thermal Power Plants

To reach optimal/better conceptual designs of energy systems, key design variables should be optimized/adapted with system layouts, which may contribute significantly to system improvement. Layout improvement can be proposed by combining system analysis with engineers’ judgments; however, optimal flowsheet synthesis is not trivial and can be best addressed by mathematical programming. In addition, multiple objectives are always involved for decision makers. Therefore, this paper reviews progressively the methodologies of system evaluation, optimization, and synthesis for the conceptual design of energy systems, and highlights the applications to thermal power plants, which are still supposed to play a significant role in the near future. For system evaluation, both conventional and advanced exergy-based analysis methods, including (advanced) exergoeconomics are deeply discussed and compared methodologically with recent developments. The advanced analysis is highlighted for further revealing the source, avoidability, and interactions among exergy destruction or cost of different components. For optimization and layout synthesis, after a general description of typical optimization problems and the solving methods, the superstructure-based and -free concepts are introduced and intensively compared by emphasizing the automatic generation and identification of structural alternatives. The theoretical basis of the most commonly-used multi-objective techniques and recent developments are given to offer high-quality Pareto front for decision makers, with an emphasis on evolutionary algorithms. Finally, the selected analysis and synthesis methods for layout improvement are compared and future perspectives are concluded with the emphasis on considering additional constraints for real-world designs and retrofits, possible methodology development for evaluation and synthesis, and the importance of good modeling practice.