Reference no: EM132879316
Tasks to be Completed
The following tasks are to be completed on the chosen design problem:
• Provide an introduction to the problem selected, the aims and objects of this study and state the relevance in industry.
• Carry out a literature survey on the theory and application relevant to the selected problem.
• Formulate the selected problem verbally and mathematically in the form of an optimisation problem. Elaborate on the identification of design qualities, selection of design objective(s), design variables, type of constraints and type of the optimisation problem.
• Select an apporpriate optimization method (Genetic Algorithm, Particle Swarm or Simulated Annealing) for solving the optimi-sation problem. Justify the rationale behind the selected method and discuss the selected constraint handling method, fitness definition, and objective evaluation.
• Implement the problem formulation in the optimization code and briefly discuss the implementation in the main body. Provide the MATLAB code in Appendix A.
• Solve the optimisation problem and prove the optimality of the solution. Investigate effect of changes in the controlling parameters.
• Identify all sources of uncertainties in the selected design optimisation problem.
• Quantify/Approximate the level and distribution of uncertainties for each uncertain parameter identified above.
• Write a Monte Carlo code to investigate the effect of uncertainties on the performance and the robustness of the optimal solution found above. Provide the MATLAB code in Appendix B.
• Conclude the report with the major findings.
Referencing Style
You are to write your coursework using the Cite Them Right version of the IEEE referencing system.
Design Optimisation Problems
Select ONE of the options below and follow the instructions given on the brief.
1. Optimal sizing of a standalone Wind-PV-Battery-Diesel hybrid renewable energy system
For an arbitrary site with known load and resource profile, find optimum size of each component (including inverter/converter) leading to minimum levelised cost of energy subject to a series of constraints including a number of arbitrary end-user requirements.
2. Design optimisation of a flat finned heat exchanger
For an arbitrary capacity (heat transfer rate in W), ambient temperature and maximum allowable temperature, find the optimal material and size for the finned heat sink below leading to minimum cost.
3. Design optimisation of an adaptive passive beam vibration absorber
For an arbitrary set of data (beam length, cross-section and material), find the optimal configuration and characteristics of a string-mass absorber that maximises the absorber operation range.
4. Design optimisation of a nanofluid flat solar collector
Find the optimum configuration (tube type, tube size, tube surface roughness, type of nanoparticle, size of nanoparticle, mass flow rate, tube distribution configuration, glazing type and size, insulation size and type) of a nanofluid flat solar collector which maximises the efficiency per unit area.
5. Design optimisation of hybrid photovoltaic-thermal collectors
Find the optimum configuration (see figure below) of a hybrid photovoltaic-thermal collector integrated in a domestic hot water heating system with the objective of cost.
6. Select your own optimization problem.
Attachment:- Design Optimisation Problems.rar