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Optimal energy-efficiency retrofit and maintenance planning for existing buildings considering green building policy complianceFan, Yuling January 2017 (has links)
Reducing global energy consumption is a common challenge faced by the human race due to the energy shortage and growing energy demands. The building sector bears a large responsibility for the total energy consumption throughout the world. In particular, it was concluded that existing buildings, which are usually old and energy-inefficient, are the main reason for the high energy consumption of the building sector, in view of the low replacement rate (about 1%-3% per year) of existing buildings by new energy-efficient buildings. Therefore, improving the energy efficiency of existing buildings is a feasible and effective way to reduce energy consumption and mitigate the environmental impact of the building sector. The high energy intensity and requirements of a green building policy are the main motivation of this study, which focuses on finding cost-effective solutions to green building retrofit and maintenance planning to reduce energy consumption and ensure policy compliance. As about 50% of the total energy usage of a general building is caused by its envelope system, this study first proposes a multi-objective optimization approach for building envelope retrofit planning in Chapter 2. The purpose is to maximize the energy savings and economic benefits of an investment by improving the energy efficiency of existing buildings with the optimal retrofit plans obtained from the proposed approach. In the model formulation, important indicators for decision makers to evaluate an investment, including energy savings, net present value and the payback period, are taken into consideration. In addition, a photovoltaic (PV) power supply system is considered to reduce the energy demand of buildings because of the adequate solar resource in South Africa. The performance degradation of the PV system and corresponding maintenance cost are built into the optimization process for an accurate estimation of the energy savings and payback period of the investment so that decision makers are able to make informed decisions. The proposed model also gives decision makers a convenient way to interact with the optimization process to obtain a desired optimal retrofit plan according to their preferences over different objectives. In addition to the envelope system, the indoor systems of a general building also account for a large proportion of the total energy demand of a building. In the literature, research related to building retrofit planning methods aiming at saving energy examines either the indoor appliances or the envelope components. No study on systematic retrofit plan for the whole building, including both the envelope system and the indoor systems, has been reported so far. In addition, a systematic whole-building retrofit plan taking into account the green building policy, which in South Africa is the energy performance certificate (EPC) rating system, is urgently needed to help decision makers to ensure that the retrofit is financially beneficial and the resulting building complies with the green building policy requirements. This has not been investigated in the literature. Therefore, Chapter 4 of this thesis fills the above-mentioned gaps and presents a model that can determine an optimal retrofit plan for the whole building, considering both the envelope system and indoor systems, aiming at maximizing energy savings in the most cost-effective way and achieving a good rating from the EPC rating system to comply with the green building policy in South Africa. As reaching the best energy level from the EPC rating system for a building usually requires a high amount of investment, resulting in a long payback period, which is not attractive for decision makers in view of the vulnerable economic situation of South Africa, the proposed model treats the retrofit plan as a multi-year project, improving efficiency targets in consecutive years. That is to say, the model breaks down the once-off long-term project into smaller projects over multiple financial years with shorter payback periods. In that way, the financial concerns of the investors are alleviated. In addition, a tax incentive program to encourage energy saving investments in South Africa is considered in the optimization problem to explore the economic benefits of the retrofit projects fully. Considering both the envelope system and indoor systems, many systems and items that can be retrofitted and massive retrofit options available for them result in a large number of discrete decision variables for the optimization problem. The inherent non-linearity and multi-objective nature of the optimization problem and other factors such as the requirements of the EPC system make it difficult to solve the building retrofit problem. The complexity of the problem is further increased when the target buildings have many floors. In addition, there is a large number of parameters that need to be obtained in the building retrofit optimization problem. This requires a detailed energy audit of the buildings to be retrofitted, which is an expensive bottom-up modeling exercise. To address these challenges, two simplified methods to reduce the complexity of finding the optimal whole-building retrofit plans are proposed in Chapter 4. Lastly, an optimal maintenance planning strategy is presented in Chapter 5 to ensure the sustainability of the retrofit. It is natural that the performance of all the retrofitted items will degrade over time and consequently the energy savings achieved by the retrofit will diminish. The maintenance plan is therefore studied to restore the energy performance of the buildings after retrofit in a cost-effective way. Maintenance planning for the indoor systems is not considered in this study because it has been thoroughly investigated in the literature. In addition, a maintenance plan for the PV system involved in the retrofit of this study is investigated in Chapter 2. / Thesis (PhD)--University of Pretoria, 2017. / Electrical, Electronic and Computer Engineering / PhD / Unrestricted
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