• Energy Research

Abstract Heat is a major contributor to total energy demand of process industries. Therefore, integrating solar heat into processes is a suitable alternative for fossil fuels. However, there are several challenges in design and optimization of solar heat integration. In this paper, the proper distribution of solar heat among direct heating solar heat exchangers and different temperature levels of heat storage is analytically solved for. As a result, a new concept is developed which can help design and operate solar heat integrated systems with heat storage. In the case study, the effect of collector area and efficiency, minimum solar temperature difference, storage size, and heat loss rate on the solar fraction are evaluated. Results show that while there is virtually no difference in solar fraction when 1000 collectors are installed, it ranges from 17 to 47% with 6000 collectors when thermal storage is possible and different collector efficiencies are included. In addition, the effect of storage type and size becomes significant only when enough number of collectors are installed to provide adequate excess heat during the sunny hours. The highest observed difference in solar fraction over the considered range of storage type and size was 1.5%.

Abstract Similar to other energy systems, economic analysis of cogeneration systems is one of the most important steps in their design procedure. In this paper, a novel method is suggested for economic optimization of cogeneration systems. This method provides an opportunity to consider uncertainties in various economic parameters. Accordingly, by providing the probability distribution function of the net present value or payback time, this method offers further insights in economic evaluations of cogeneration systems. As a common practice for demonstrating novel methodologies in design and optimization of cogeneration systems, the proposed method of this study is applied to a well-known cogeneration case in the literature. In a coupled scheme, Monte Carlo approach is applied with net present value method to optimize the system. Accordingly, the obtained result is the probability distribution function of the net present value of the maximum profit. The results verify that compared to previously used methods which did not consider uncertainties in economic parameters, this probability distribution function provides a more general point of view on the profitability of the system. Therefore, by showing economic risks, these considerations make investments in this cogeneration system far more interesting.

Abstract Today, process industries are responsible for a large portion of world's energy demand. Accordingly, in this section, replacing fossil fuels with renewables can have a great effect on total energy consumption and CO 2 emission of the world. Using Heat Integration concepts, a general procedure for integration of solar heat into processes is generated. This procedure provides a tool for designers to find the best integration scenario and solar fraction targets. Also, it can help economic optimization of Solar Heat Integration by calculating the solar fraction targets for a certain amount of capital investment. Then, a new index for evaluation of existing designs is presented. Finally, the case of an organic distillation plant was investigated for Solar Heat Integration. Using the proposed procedure, the best place for solar heat exchangers on the process heat exchanger network and the solar fraction target was found. Annual simulations suggested that with current collector technologies, a payback period of 7–9 years is reachable. It was predicted that with further developments in collector technologies and more restrictions on CO 2 emission, Solar Heat Integration for this case will eventually be profitable.

Due to the current financial constraints in the energy industry, investors need realistic risk evaluation and economic analysis in energy investment projects. On the other hand, energy system operators are continuously facing a wide range of challenges when dealing with asset management practices of the system components. In this paper, a novel method is proposed for the availability assessment of energy systems. This method provides an opportunity to predict system real behavior patterns in simulated time. According to the designed procedure, two new parameters for availability assessment are defined as the Failure Moment (FM) and the Repair Moment (RM). FM and RM of the components are estimated by the Monte Carlo method based on the time-varying failure rate and repair rate, respectively. This process is continued for all selected components in the system lifetime. As a common practice for demonstrating novel methodologies, the proposed method of this study is applied to the Combined Cycle Gas Turbine Power Plants. The results show that realistic availability evaluation for energy systems with the Monte Carlo method can cause a 4.4% reduction in nominal fuel consumption (16.79 kg/s as an average fuel flow rate vs. 17.562 kg/s as nominal amount) and a 5.05% reduction in nominal power generation. Therefore, this consideration makes the investment analysis more accurate and the decision to invest more interesting.