[en] The paper starts with experience curve analysis in order to find out the future prices of solar photovoltaic (PV) modules. Experience curves for 75-90% progress ratio are extrapolated with the help of estimated future growth rate for PV installation worldwide and current module price data until year 2060. A kWh PV electricity generation cost has been calculated for coming decades with the help of local market parameters and module prices data from extrapolated experience curve. Two different prices for grid electricity - wholesale electricity price and end user electricity price - are separately analyzed. Household electricity consumption profile and PV electricity generation profile for Cologne, Germany, have been analyzed to find out the possibility for PV electricity consumption at the time of its generation. This result is used to calculate the real grid parity year - which lies somewhere between grid parity years calculated for wholesale electricity price and end user electricity price. (author)

[en] 

Background

Many rural electrification projects around the world employ micro hydropower plants (MHPs). These installations provide immediate and direct benefits to the local people. However, the sustainability of their operation in the long run remains a vital issue. Without proper sustainability assessment, the projects may face operational problems. However, to date, only a few empirical studies exist which offer tools to assess sustainability of MHP projects post-implementation. Given that every site has peculiar characteristics that could largely vary from site to site, there is a need to develop a model which could assess and compare the feasibility of the projects from the sustainability point of view before the project is implemented. For this purpose, a thorough sustainability assessment model was developed for an MHP project in a mountainous region of Nepal.

Methods

This paper presents a sustainability assessment model for micro hydropower plants. In order to collect the data necessary to run the model, different sets of questionnaires were prepared for all relevant stakeholders. The developed model was used to assess an overall sustainability of a 26-kW plant at Mahadevsthan in Dhading District of Nepal. At this site, 15 community households, a project management committee member, an operator, and three policy makers/micro hydro experts were interviewed. The indicator system developed here was finalized with the stakeholder’s participation.

Results

A sustainability assessment model for the operation of micro hydropower plants in a remote rural area of Nepal was developed. Our model includes 54 assessment indicators taking into account economic, social, environmental, and technical sustainability dimensions and a scoring system (ranging from 1 to 5, with 5 being the best). It was found that the social dimension shows the best performance with a score of 4.17 for the studied MHP, followed by environmental (3.94), economic (3.74), and technical dimensions (3.04).

Conclusions

The results show that the developed model creates a qualitative and quantitative basis for sustainability assessment of MHPs, allowing easiness for comparison of micro hydro projects, providing an effective decision-making support tool in rural electrification and development sector. The input of all stakeholders in identifying site-specific indicators that are relevant to the sustainability of the projects is crucial for minimizing biases in the assessment framework.

[en] Highlights: • A holistic design optimization integrating technical, economic and environmental factors. • Designed and optimized in TRNSYS/MATLAB. • A case study conducted leading to 31.5% power plant efficiency with 0.13$/kWh LCOE. • Economically feasible only under power outage loss and/or improved electricity tariff. To gain the benefits of solar-biomass cogeneration plant, supplying energy to industry, the design optimization procedure is required to holistically integrate economical, technical and environmental aspects. This entails formulation of a performance criterion that maximizes solar fraction, reduces investment cost, lowers thermal storage loss and puts less pressure on biomass resources. It is also necessary to consider factors influencing the plant’s performance while giving active role to industrial demand. This kind of optimization approach adaptively evolves as influences change and is not static. However, such a criterion is not yet part in many of the existing design optimization schemes. In this work, an alternative optimization approach that addresses the aforementioned issues is proposed. To this end, a molten salt biomass boiler is modeled in MATLAB and integrated to a solar plant model in TRNSYS. The resulting configuration is latter optimized in GenOpt to minimize biomass power utilization index (BPUI) and excess saturated steam generation (ESSG). Demonstrated by a case study, a plant efficiency of 31.5% with 23.5% solar gain is optimally designed resulting in about 0.094$/kWh levelized cost of generation. Furthermore, considering global power outage loss, the hybrid plant could be seen as a preferred industrial source of energy.

[en] Highlights: • Holistic optimization and control approach for solar-augmented industrial process. • Energy based optimization with investment constraints. • Transfer function based continuous heat transfer control. • Validated against a case study of a dyeing industrial process in textile industry. • Control enables 12.4% increase in solar gain and 5.6% reduction in payback period. -- Abstract: Process level integration of solar energy could give an economically feasible solution if the industrial process allows its practical integration. The solar-augmented industrial process behaves as a complex system influenced by uncertainty of solar radiation, variability of demand temperature and process time schedule as well as possibility of thermal stratification in the storage. Addressing these issues to reach the most economical solution has two dimensions to it. First, the solar thermal system needs to be optimally designed. This requires the development of a performance criterion that will deliver maximum solar energy to the industrial process, avoid large variations of energy in the storage, and meet investment constraints. Second, the identified optimal system should be dynamically controlled to enable uniform heat distribution and efficient auxiliary heat utilization. This paper presents a holistic design optimization and control approach for a solar-augmented industrial process to facilitate decision support. The proposed solution is designed and optimized for a dyeing industrial process case study that resulted in a 5.7 year payback period, 56.3% solar fraction, and 252.2 tons equivalent carbon emission reduction. Furthermore by implementing dynamic control, about 12.4% increase in solar gain that led to a 5.6% reduction in payback period is identified.

[en] Highlights: • Ten waste-to-energy treatment paths for biowaste were investigated. • Hydrothermal carbonization (HTC) and anaerobic digestion (AD) were considered. • Energy production and consumption patterns were dynamically modeled. • The global warming potential (GWP) of the treatment paths was determined. • The combination of AD and HTC can reduce the GWP in comparison to AD and composting. Instead of an exclusive composting of the organic fraction of municipal solid waste (OFMSW), anaerobic digestion (AD) has emerged as a widely used upstream process in Germany to additionally harvest energy from this waste stream. However, the energy potential is not fully exploited as only easily biodegradable material undergoes AD. Additionally, a high potential of CH₄ and N₂O emissions during the composting and spreading of compost may result in an overall high global warming potential (GWP) from these treatment paths. In this study, nine alternative or additional treatment options to AD followed by composting were investigated. For all treatment paths, the hydrothermal carbonization (HTC) reflected a central component and was connected to a downstream energy exploitation step by means of gasification or co-combustion. All treatment paths were dynamically modeled with regards to their energetic performance and evaluated against their exergetic efficiency. The datasets on energy consumption and production formed the basis for determining the global warming potential (GWP) according to a life cycle assessment approach. The functional unit was the production and export of exergy. The assessment showed that the incorporation of an HTC step was able to increase the net exergy exploitation by up to 93% in comparison to a treatment path consisting of AD and composting. Simultaneously, the GWP was reduced by 30%. Here, preferential treatment paths combined AD with HTC.