Search results

Priorities of decarbonizing the mining sector together with an availability of cost-effective technological solutions lead renewable energy (RE) to become an attractive energy source for the mining industry. Several pilot projects are run as hybrid systems, providing additional capacity to traditional energy systems. The purpose of this paper is to develop a mathematical model as a decision-making tool. The decision refers to a replacement of the fossil fuel system contains by the hybrid system in the sense of no return.

Four systems are considered. System one contains only a diesel plant. System two consists of a hybrid energy system with a photovoltaic (PV) part and a genset as back-up. System three includes a conventional natural gas combined cycle (CGCC) plant. Finally, system four covers a hybrid energy system with a PV part and CGCC turbine. The mathematical model is based upon the well-known concept of levelized cost of electricity.

The scenarios account for the degradation rate of PV modules, the PV yields of mines in different locations and the greenhouse gas emissions impact. The results show the break-even times of each scenario and the years of no return for the four systems in each scenario.

The solution of the model is performed for two case-studies. Case study 1 compares the diesel and hybrid PV-diesel systems. Case study 2 compares the CGCC and hybrid PV-natural gas systems.

This model can be generalized to all mining settings, with specific practical implications for off-grid mines.

The results of this paper bring a valuable contribution to carbon dioxide emissions reduction.

The paper aims to enhance the attention of decision-makers on fossil fuel and RE technologies increase the attractiveness of RE in powering mining operations.

This study aims to analyze the effects of variations in annual real interest rates in the assessment of the techno-economic feasibility of a hybrid renewable energy system (HRES) for an off-grid community.

Hybrid Optimization of Multiple Energy Resources (HOMER) software is used to propose an HRES for Abadam community in northern Nigeria. The HRES was designed to meet the basic needs of the community over a 25-year project lifespan. Based on the available energy resources in the community, photovoltaic (PV), wind turbine, diesel generator and battery were suggested for integration to serve the load requirements.

When the annual real interest rates were taken as 10 and 8 per cent, the total amount of total energy fraction from PV, wind turbine and the diesel generator is 28, 57 and 15 per cent, respectively. At these interest rates, wind turbines contributed more energy across all months than other energy resources. The energy resource distribution for 0, 2,4 and 6 per cent annual real interest rates have a similar pattern, but PV contributed a majority of the energy.

This study has used annual real interest and inflation rates dynamic behavior to determine optimal HRES for remote communities. Hence, its analysis will equip decision-makers with the necessary information for accurate planning.

The results of this study can be used to plan and design HRES infrastructure for off-grid communities around the world.

Renewable generation is a main component of most hybrid generation systems. However, randomness on its generation is a characteristic to be considered due to its direct impact on reliability and performance of these systems. For this reason, renewable generation usually is accompanied with other generation elements to improve their general performance. The purpose of this paper is to analyze the power generation system, composed of solar, wind and diesel generation and power outsourcing option from the grid as means of reserve source. A multi-objective optimization for the design of hybrid generation system is proposed, particularly using the cost of energy, two different reliability indexes and the percentage of renewable energy as objectives. Further, the uncertainty of renewable sources and demand is modeled with a new technique that permits to evaluate the reliability quickly.

The multi-state model of the generators and the load is modeled with the Universal Generating Function (UGF) to estimate the reliability indexes for the whole system. Then an evolutionary algorithm NSGA-II (Non-dominated Sorting Genetic Algorithm) is used to solve the multi-objective optimization model.

The use of UGF methodology reduces the computation time, providing effective results. The validation of reliability assessment of hybrid generation systems using the UGF is carried out taking as a benchmark the results obtained with the Monte Carlo simulation. The proposed multi-objective algorithm gives as a result different generators combinations that outline hybrid systems, where some of them could be preferred over others depending on its results for each independent objective. Also it allows us to observe the changes produced on the resulting solutions due to the impact of the power fluctuation of the renewable generators.

The main contributions of this paper are: an extended multi state model that includes different types of renewable energies, with emphasis on modeling of solar energy; demonstrate the performance improvement of UGF against SMC regarding the computational time required for this case; test the impact of different multi-states numbers for the representation of the elements; depict through multi-objective optimization, the impact of combining different energies on the cost and reliability of the resultant systems.

The application of hybrid renewable energy system (HRES) can mitigate inadequate access to clean, stable and sustainable energy among households in sub-Saharan Africa (SSA). Available studies on HRES seem to concentrate only on its techno-economic and environmental viability. In so doing, these studies do not seem to underline the likely challenges that follow the acquisition of HRES by especially low-income households. The ensuing reality is, of course, a limitation in the use of HRES in homes with low incomes. It is therefore imperative to analyze how a household with low income can afford this kind of energy system. The purpose of this study, therefore, lies in presenting a techno-economic, environmental and affordability analysis of how HRES is acquired.

To arrive at a grounded analysis, a typical household in SSA is used as an example. The analysis focused on the pattern of energy use, and this is obtained by visiting an active site to evaluate the comprehensive load profile. In the course of analysis, an optimal techno-economic design and sizing of a hybrid PV, wind and battery were undertaken. Additionally, an acquisition analysis was done based on loan amortization.

The interesting result is that a combination of the photovoltaic-gasoline-battery system is the most cost-effective energy system with a net present cost of $2,682. The system combination can lead to an emission reduction of approximately 98.3 per cent, compared to the use of gasoline generating sets, common mostly in SSA. If an amortized loan is used to purchase the energy system, and the payment plan is varied such that the frequency of payments is made quarterly, annually, semi-annually, bi-monthly, semi-monthly and bi-weekly, it will be observed that low-income household can conveniently acquire a HRES.

The result presented a framework by which a low-income household can purchase and install HRES. To facilitate this, it is recommended that low-income households should be given interest-friendly loans, so as to enhance the acquisition of HRES.

This paper aims to propose a comprehensive methodology for setting up rural electrifications for indigenous villages with minimum budgets and the lowest possible cost of electricity (COE). The electricity accessibility of rural area in Malaysia is not fully covered and the cost of extending the grid to these areas can be high as RM 2.7m per km. Lack of vigorous policies and economic attraction of the rural areas are also the main barriers to rural electrification. Electricity is an essential element of economic activities and the lack of electricity exacerbates poverty and contributes to its perpetuation. Therefore, a hybrid standalone power system can be an alternative solution for the rural electrification. A hybrid standalone power system is studied to investigate the potential of the implementation and the budget required.

A site survey has been carried out in a village in Peninsular Malaysia, namely, Kampung Ulu Lawin Selatan. A standalone hybrid system is modeled in HOMER Pro software and the data collected from the selected site are used to obtain the system configuration with the lowest COE. The load following and cycle charging energy dispatch methods are compared to identify the optimal system configuration that yields the lowest COE. The diesel generator-only system is chosen as a benchmark for comparisons.

The results show that the hybrid system constituted from the diesel generator, photovoltaic (PV), micro-hydro and energy storage using the load following energy dispatch method yields the lowest COE of RM 0.519 per kWh. The COE of the hybrid system is 378 per cent lower than that of the diesel generator-only system. The lead-acid energy storage system (ESS) is able to reduce 40 per cent of COE as compared to the system without ESS.

The results indicate that the COE of the diesel-micro hydro-PV-ESS system with load following dispatch strategy is RM 0.519 per kWh, and this value is 35 per cent higher than the average electricity price in Malaysia. However, it is important to note that the costs of extending the grid to the rural area are not taken into account. If this cost is considered into the electricity price, then the standalone hybrid power system proposed by this study is still a competitive alternative for rural electrification.

Earlier most of the research groups have designed and developed hybrid renewable energy system models with technological, scientific and industrial advancement for the energy systems, but slight attention has been paid towards the grid-connected sustainable urban residential energy systems (SUR_eS) for metropolitan cities. The current research wishes to design, model and analyze grid-connected energy system for residential applications for sustainable urban residential energy system. The works aims to explore the potential of the augmented energy system for grid-connected energy system.

The proposed grid-connected SUR_eS are validated for a sample location at New Delhi (India) with a hybrid optimization model for electric renewable (HOMER) software to define and understand the various load profile. It presents the sensitivity analysis approach to validate the design of the proposed energy system.

The obtained results reports the key barriers, proposed model and scenarios for sustainable urban energy system development.

Similar approaches can be replicated to design and develop an independent, self-sustainable cleaner and environmental-friendly energy system in the future scenario for the extension of complex grid infrastructures.

It will assist the stakeholder in solving the complex urban sustainability issues raised due to the shortage of energy.

It will offer a clean and environment friendly sustainable energy resources with reduced carbon emissions. It will benefit sustainable energy resources with a mix of challenges and opportunities, to suggest an approach for implementation of efficient energy policies to optimize the existing and forthcoming energy systems.

The current research offers a design and model to analyze grid-connected energy system sustainable urban residential applications. It explores the potential of the augmented energy system. The proposed model are validated for a sample location with HOMER simulation software to define and understand various scenarios of the multiple load profile. The work presents the sensitivity analysis approach to validate the proposed energy system.

This study is a targeted review of some of the major changes in European regulation that guided energy policy decisions in the Iberian Peninsula and how they may have aggravated the problem of lack of flexibility. This study aims to assess some of the proposed short-term solutions to address this issue considering the underlying root causes and suggests a different course of action, that in turn, could help alleviate future market strains.

The evolution of the most important (macro) energy and price-related variables in both Portugal and Spain is assessed using market and grid operator data. In addition, the authors present critical viewpoints on some of the most recent EU and national regulation changes (official document analysis).

The Iberian energy policy and regulatory agenda has successfully promoted a rapid adoption of renewables (main goal), although with insufficient diversification of generation technologies. The compulsory closings of thermal plants and an increased tax (mainly carbon) added pressure toward more environmentally friendly thermal power plants. However, inevitably, this curbed the bidding price competitiveness of these producers in an already challenging market framework. Moving forward, decisions must be based on “a bigger picture” that does not neglect system flexibility and security of supply and understands the specificities of the Iberian market and its generation portfolio.

This work provides an original account of unprecedented spikes in energy prices in 2021, specifically in the Iberian electricity market. This acute situation worries consumers, industry and governments. Underlining the instability of the market prices, for the first time, this study discusses how some of the most important regulatory changes, and their perception and absorption by involved parties, contributed to the current environment. In addition, this study stresses that if flexibility is overlooked, the overall purpose of having an affordable and reliable system is at risk.

Rural areas are one of the effective regions in economy and self-sufficiency field especially in agricultural and livestock section. Planning in the rural section and the effort in solving the problems of farmers lead to increase their interest in farming and manufacturing in the villages and decrease their migration to the cities and metropolitans. Therefore, the present study aimed at feasibility of electricity to a rural household in Iran using off-grid solar-based hybrid system.

In renewable energy projects, a successful evaluation requires suitable criteria so that one can properly analyze the operational behavior of all feasible scenarios. In the present paper, HOMER software has been used for this purpose for a village with no access to electricity grid (Bar Aftab-e Jalaleh, Iran). Due to drastic fluctuation of fossil fuel prices and varied solar radiations in various years because of climate change, sensitivity analysis has been performed using HOMER.

In the optimum status economically, 70% of needed energy is provided by solar cells at the price 0.792 $/kWh. The comparison between the optimum condition economically and the condition that only use fossil fuels revealed that the return on investment will occur after less than 2 years and have remained profitable over 23 years.

The authors hope that the results of this study can be used in planning of the authorities to realize the interests of people in this village.

According to the surveys, despite Iran being the first country in terms of providing solar power to the villages, so far no socio-economic-environmental assessment has been done for a solar cell-based micro-grid in an off-grid mode for a remote village that is deprived of electricity from a national electricity grid. In addition, for the first time in Iran, the effect of the fuel price and solar radiation parameters variability on the performance of system have been investigated.

The main purpose of this controller is to carryout irrigation by the farmers with renewable energy resources.

The proposed design includes the Deep learning based intelligent stand-alone energy management system used for irrigation purpose. The deep algorithm applied here is Radial basis function neural network which tracks the maximum power, maintains the battery as well as load system.

The Radial Basis Function Neural Network algorithm is used for carrying out the training process. In comparison with other conventional algorithms, this algorithm outperforms by higher efficiency and lower tracking time without oscillation.

It is little complex to implement the hardware setup of neural network in terms of training process but the work is under progress.

The practical hardware implementation is under progress.

If controller are implemented in a real-time environment, definitely it helps the human-less farming and irrigation process.

If this system is implemented in real-time environment, every farmer gets benefitted.

The building and construction industry has a significant potential to reduce adverse climate change effects. There are plans to improve the natural resource use and greenhouse gas emissions caused by the buildings by choosing energy-efficient technologies, renewable energy sources and sustainable architectural and constructional elements. This study systematically reviews the patent data for climate change mitigation technologies related to buildings, aiming to detect their relative importance and evaluate each technology in the Y02B network.

The applied approach covers the process of (1) selecting high-impact technology, (2) collecting patent data from the USPTO database, (3) creating a citation frequency matrix using cooperative patent classification codes, (4) linking high-impact patents with analytical network process method, (5) limiting centrality of identifying core technologies from indicators and (6) creating a technology network map with social network analysis.

The study results show that energy-saving control techniques, energy-efficient lighting devices, end-user electricity consumption, management technologies and systems that convert solar energy into electrical energy are core solutions that reduce the effects of climate change. In addition, solutions that will support core technologies and whose effects are expected to increase in the coming years are energy-efficient heating, ventilating and air conditioning systems, smart grid integration, hybrid renewable energy systems, fuel cells, free cooling and heat recovery units and glazing technologies.

Most of the studies on patent analysis have failed to demonstrate any convincing evidence down to the lowest component groups of an entire technology network. The applied approach considers and evaluates each component included in a technology network from a holistic perspective.