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In recent times, the virtual power plant (VPP) is gaining more attention in power system engineering due to its tremendous potential in enhancing sustainable urbanism, in which, it supplies clean energy from distributed generators. Electricity is deemed a basic requirement for future automotive and ultra-modern technologies. The deficiency of traditional energy resources and their complex generation process make the production cost of electricity increase dramatically. Moreover, traditional power distribution systems are encountering issues in distributing electrical energy to fulfill customer demands. Therefore, this paper proposes a novel power management system named 'the hybrid genetic local binary knowledge (HGLBK) algorithm' to manage power distribution in the transmission lines and to optimize the total operation cost of the network. The hybrid optimization algorithm effectively controls the load by supplying the surplus power load to the adjacent feeders thereby optimally selecting and placing the distributed energy resource (DER). The proposed concept is implemented at Kayathar, Tamil Nadu in India, and their real-time data are utilized for modeling the VPP. The proposed VPP concept is implemented in the IEEE-9 bus system and the performance of VPP is simulated using the MATLAB software. The performance of the proposed HGLBK algorithm is assessed by comparing its effectiveness with the existing approaches. [ABSTRACT FROM AUTHOR]

Rural and remote regions of developing economies face a serious scarcity of reliable energy supply. Focus on providing electricity through renewable and off grid energy resources is becoming increasingly popular. Off the grid or decentralized renewable energy typically considers either solar or small hydro power to fill the supply deficit and increase in demand with time is generally ignored. This paper proposes a hybrid technology mix of various renewable energy options for two remote villages located in Darma valley of Uttarakhand state in the Indian Himalayan Region. Since the villages are at an average height of 3500 m amsl, they are inaccessible during winters due to heavy snowfall. Therefore, decentralized energy could be the most cost effective solution to provide electricity. This paper estimates the energy demand of these villages and identifies the most optimum off the grid solutions, and compares it with grid connected electricity supply using hybrid optimization model for electric renewables. Micro hydro energy generation was found to be the most cost effective and techno-economically viable solution. This paper also evaluates the barriers faced by remote Himalayan villages so as to achieve reliable application of the results of this study. [ABSTRACT FROM AUTHOR]

This paper mainly dealt with the technical and economic feasibility of an off-grid hybrid power generation system for a remote rural Turtuk village of Ladakh, located in the northern part of India. The study showed that the proposed configured renewable integrated hybrid system, using Hybrid Optimization of Multiple Energy Resources (HOMER) software, efficiently met the energy demand, exhibiting optimum performance with low investment. The proposed PV(115 kW)/Wind(1 kW)/Battery(164 strings of 6 V each)/DG(50 kW) hybrid system was a highly commendable, feasible solution preferred from a total of 133,156 available solutions resulting from HOMER simulations. The net present cost and energy cost of the proposed configuration were $278,176 and $0.29/kWh, respectively. The proposed hybrid configuration fulfilled local load, with 95.97% reduced dominant harmful carbon dioxide emission, as compared to the sole us of a diesel generator power supply system. The technical performance of the hybrid system was ensured, with advantages including the highest renewable penetration and least unmet load. Furthermore, the analysis exclusively evaluated the impact of the system's economic parameters (namely, its expected inflation rate, nominal discount rate, and project lifetime) on the net present cost and cost of energy of the system using a noble single fix duo vary approach. [ABSTRACT FROM AUTHOR]

This paper presents a novel approach to designing and optimizing a Solar-Wind Hybrid Energy System (SWHS) for an Electric Vehicle Charging Station (EVCS) and a university shopping complex in India. Objectives include addressing sustainable energy challenges, ensuring reliability, and minimizing the Levelized Power Supply Price (LPSP). Key contributions encompass a two-stage framework for optimal SWHS configuration, consideration of uncertainties in renewable energy generation, and the use of the Ebola Optimization Search Algorithm (ESOA). The first stage models SWHS components, formulates an objective function, and addresses reliability to minimize LPSP. The second stage employs ESOA, inspired by Ebola spread, exploring both local and global search spaces. Simulation results and a load profile analysis validate the proposed framework and ESOA's performance, observing a significant improvement of 15% in LPSP and a 10% increase in system reliability. The study provides insights into optimal Distributed Generation (DG) sizing in SWHS, ensuring reliable and cost-effective power supply for EVCS and commercial applications, contributing to the renewable energy system design and optimization field. The analysis indicates an enhanced system reliability by 10 % and a notable reduction in LPSP by 15 %. [ABSTRACT FROM AUTHOR]

According to the Tamil Nadu Energy Development Agency (TEDA) in the 2019-20 academic year, the wind power plant produces 23% of the biomass power supply in the Indian electrical commodities. To maintain the power withstanding capability needed for future electrical commodities, a yearly power shutdown program is implemented. An additional wind power plant unit will be erected and create more electricity, thereby balancing India's commercial electricity needs. Even in a nonstationary working environment, continuous monitoring and analyzing the efficiency of wind turbines is a more difficult task. Consequently, in this paper, a health index calculation for wind power plants is proposed utilizing neurofuzzy (NF) modeling. Wind generator efficiency can be measured mathematically by recording three crucial primitivistic such as observed rotation speed, generation wound temperature, and gearbox heat. Fuzzy rules are used to design the parameters of the neural network (NN), and the accumulated signal is compared using the nonlinear extrapolation approach to determine the wind generator's behavior and evaluate the hazards. During the experimental study, two windows of 24 hours and 60 hours are used, where the deviation signal required for the hazard induction is investigated. The proposed approach can accurately calculate the wind generator's health state. As a result of an improved health operating and management (HOM) system, the amount of power generated by industrials and domestic appliances has increased dramatically. [ABSTRACT FROM AUTHOR]

The rapid growth of electric vehicles in India necessitates more power to energize such vehicles. Furthermore, the transport industry emits greenhouse gases, particularly SO2, CO2. The national grid has to supply an enormous amount of power on a daily basis due to the surplus power required to charge these electric vehicles. This paper presents the various hybrid energy system configurations to meet the power requirements of the electric vehicle charging station (EVCS) situated in the northwest region of Delhi, India. The three configurations are: (a) solar photovoltaic/diesel generator/battery-based EVCS, (b) solar photovoltaic/battery-based EVCS, and (c) grid-and-solar photovoltaic-based EVCS. The meta-heuristic techniques are implemented to analyze the technological, financial, and environmental feasibility of the three possible configurations. The optimization algorithm intends to reduce the total net present cost and levelized cost of energy while keeping the value of lack of power supply probability within limits. To confirm the solution quality obtained using modified salp swarm algorithm (MSSA), the popularly used HOMER software, salp swarm algorithm (SSA), and the gray wolf optimization are applied to the same problem, and their outcomes are equated to those attained by the MSSA. MSSA exhibits superior accuracy and robustness based on simulation outcomes. The MSSA performs much better in terms of computation time followed by the SSA and gray wolf optimization. MSSA results in reduced levelized cost of energy values in all three configurations, i.e., USD 0.482/kWh, USD 0.684/kWh, and USD 0.119/kWh in configurations 1, 2, and 3, respectively. Our findings will be useful for researchers in determining the best method for the sizing of energy system components. [ABSTRACT FROM AUTHOR]

To make developed country, recent year India shift towards the research area for the development to lead the research. The main task of power system is to supply their customer a continuity power supply at ever, but in action it's not take place; because of the whole power system is the big network which includes different types of loads, at the instant of common compiling sensitive loads connected in which voltage distortion in supply side or load side is highly repellent. Voltage dip is the most frequent arising power quality issues mainly occurs in distribution system since it main causes disturbance for domestic and industrial equipment. In this paper the simulink model of DVR for reduction of voltage sag and its control by reference frame theory algorithm has carried in MATLAB simulink to enhance the power quality issues. [ABSTRACT FROM AUTHOR]

Given the steady growth in the use of electric vehicles in India, and the need to locate charging stations in various places to fulfill the corresponding demand, this paper focuses on an applicable Electricity Tariff Policy Framework in the context of power supply to Electric Vehicle Charging Stations(EVCSs). The framework is conceptualized by a theoretical foundation, an operational/functional foundation, and a transactional foundation. The theoretical foundation incorporates justice risk across the Energy Lifecycle stages by classifying the relevant international, regional, and national issues within the legal layers of Energy Law while examining the core ideas of the 'Energy Trilemma'. The paper identifies two basic dimensions, (a) the target sets of end-users, and (b) EVCSs settings and the applicable tariff schemes, as the foundation of the framework. The operational/functional foundation consists of techno-economic and social criteria, and the transactional foundation involves the consideration of different target sets of end-users. The proposed framework will benefit policymakers in general and those, especially in India. Adaptation and use of the framework in other countries should consider their basic economic, geographic and political structures. • Identification of basic dimensions of the ETPF in the context of EVCSs. • Justifications for developing a dynamic and adaptive ETPF applicable to EVCSs. • Relevance of justice risk in the electric mobility system. • Tariff Framework for Power supply to Electric Vehicle Charging Stations in India. [ABSTRACT FROM AUTHOR]

Clean energy transition via utilizing biomass resources has been projected as an important climate change mitigation strategy. A vital characteristic of biomass is its localized nature; therefore, bioenergy utilization should follow decentralized planning. Agrarian countries like India can take benefit of its large agricultural biomass waste pool to produce clean renewable energy. However, prior knowledge of spatio-temporal distribution, competing uses, and biomass characteristics are necessary for successful bioenergy planning. This paper assesses biomass resource and its power generation potential at different agro-climatic zone levels in the state of Rajasthan, India considering crop residue biomass (25 different crop residues from 14 crops) and livestock manure (from cattle, buffalo, and poultry). Uncertainties associated with the availability of biomass and the power generation potential are assessed for each agro-climatic zone under different scenarios. Greenhouse gases (GHGs) emissions from biomass-based power generations are also estimated and compared with biomass-equivalent coal power plants. It is observed that the annual biomass power potential of Rajasthan is 3056 MW (2496 MW from crop residues and 560 MW from livestock manure). Scenario analysis suggests that the potential varies from 2445 to 6045 MW under different biomass availability and power plant operating conditions. Annual GHGs emissions due to biomass power generation is 5053 kt CO 2 eq. Replacing coal-based power with biomass power would result in annual GHGs savings of 11412 kt CO 2 eq. The paper also discusses various carriers and barriers viz. logistics, institutional, financial and technical in setting up decentralized bioenergy plants. Outcomes of the present study are expected to assist renewable energy planners in India. • Biomass resources and their power potential are assessed for Rajasthan, India. •Biomass power potential for different selected scenario ranges from 2445-6045 MW. •GHG emissions from biomass power is assessed and compared with fossil fuels. •Spatio-temporal variability, low density and logistics are limitations of biomass. •Favourable policies, technologies and market can help to promote bioenergy sector. [ABSTRACT FROM AUTHOR]

Abstract Biomass has often been regarded as a promising renewable energy resource to mitigate climate change. However, what will be the impact on global surface temperature if biomass replace fossil fuel remain unclear. This paper, through a case study in Uttar Pradesh, India address this issue by assessing biomass resource potential to reduce fossil fuel demand and mitigate climate change. Impact of biomass power related GHG emissions on global surface temperature is estimated using the Absolute Global Temperature change Potential (AGTP) climate metric. Uttar Pradesh can produce 71 Mt surplus biomass annually, equivalent to 7298 MW power. Power density of biomass range between 0.10 and 0.25 Wm-2. Significant amount of GHG emissions reduction is possible if biomass replace fossil fuel as a power source in the region. Annual GHG emissions associated with 1 MWh of power derived from coal, natural gas and biomass would cause 4.10 × 10−7, 2.40 × 10−7 and 1.25 × 10−7 mK rise in global surface temperature, 100 years after an initial emission, indicating potential of biomass power to mitigate climate change. Variation in spatio-temporal distribution and low power density could be delimiting factors in large-scale deployment of biomass power. Graphical abstract Image 1 Highlights • Biomass resources and power potentials are assessed for Uttar Pradesh, India. • GHG emissions from biomass power is assessed and compared with fossil fuels. • Climatic impact of power generation is assessed via novel climate metric. • Biomass power can mitigate climate change by replacing fossil fuels. • Spatio-temporal variability and low power density are limitations of biomass. [ABSTRACT FROM AUTHOR]

Abstract Distribution transformer is a most important component of the distribution system to provide uninterrupted power supply to the consumers and it should be highly reliable. Distribution transformer failure affects the reliability and power quality of the supply system. This paper presents distribution transformer failure analysis to find out causes of failures responsible for very high rate of failure in a state owned electric utility Punjab State Power Corporation Limited (PSPCL) in India. Detailed failure analysis is conducted on 348 distribution transformers failed from 2010 to 2015 in a city based sub division area. Failure analysis is carried out in accordance with IEEE standards and summarized the results statistically in the first part. In second part, the failure modes, effect and criticality analysis (FMECA) is used to analyse distribution transformer failure modes, causes of failure and effects of failure. Further, criticality analysis is performed and a risk priority number is assigned based upon the severity classification, probability of occurrence and probability of detection to identify most critical parts of transformer. FMECA leads to identify preventive actions to be taken to reduce the risk of the transformer in future by eliminating the causes of failure, reducing severity and probability of occurrence. Highlights • Analysis of distribution transformer failure in conjunction with a real time data of failure in public sector utility. • Failed transformers are analysed for month wise, year wise, age wise, component wise failure and causes of failure. • Failure Modes, effect and criticality analysis (FMECA) to identify most critical components of transformer. • Compensatory provision are provided to save the distribution transformer from premature failure. [ABSTRACT FROM AUTHOR]

Using a dynamic model from 2005 to 2015, this study assessed China’s energy supply security in the provinces along “the Belt and Road”. Energy supply security was conceptualized across four dimensions: availability, affordability, acceptability, and energy technology and efficiency. A dynamic model was used to calculate the dynamic weights for each indicator and to examine the variation laws. It was found that the acceptability dimension indicator weights had rapidly increased, indicating that energy supply security had been widely accepted. Smooth weights were found for the availability dimension indicators, indicating that the resources needed to protect basic energy supplies were available. A synthetical energy supply security evaluation index was also analyzed for each “Belt and Road” province using a “quadratic weighting” method, which showed that the index was different in the same provinces in different years and different for different provinces in the same year. For 14 “Belt and Road” provinces, the overall energy supply security was found to have a “V” shape and a general dynamic upward trend, with the trends in the northwest and southeast provinces and along the whole “Belt and Road” found to be consistent. The energy supply security differences between these provinces were analyzed deeply in this paper; it will help us to understand the strengths and weaknesses of energy supply security levels in these provinces. The result will make it easier to cooperate with other provinces or countries along the “Belt and Road” in energy supply. [ABSTRACT FROM AUTHOR]

Solar photovoltaic (SPV) installations are growing in the distribution network due to the continuously decreasing prices of solar photovoltaic panels. Installing the SPV Plant on the distribution feeder supplying to the agricultural pumps is a challenging task due to the varying agricultural load pattern of the Agricultural Feeder (AG Feeder). Supply of power and demand creates potential challenges in the low voltage (LV) distribution system. This paper presents a case study of a 2 MW SPV connected to an agricultural feeder in India. Performance analysis has been carried out using field measurement data. The key parameters such as PV Penetration and Capacity Utilization Factor (CUF) are calculated for analysis. Parameters such as Grid Dependency of the load and PV Contribution have been introduced in this paper, which relates to the SPV system behavior more aptly. It is recommended that the Time of Day (ToD) metering with the lowest cost during the solar generation hours will make agricultural consumers shift their demand matching with solar generation hours. Extensive analysis of agricultural feeder connected SPV power plant indicates that the power supply has improved for the feeder during winter and summer months. [ABSTRACT FROM AUTHOR]

By considering the weight penalty of batteries on payload and total vehicle weight, this paper shows that almost all forms of land-based transport may be served by battery electric vehicles (BEV) with acceptable cost and driving range. Only long-distance road freight is unsuitable for battery electrification. The paper models the future Indian electricity grid supplied entirely by low-carbon forms of generation to quantify the additional solar PV power required to supply energy for transport. Hydrogen produced by water electrolysis for use as a fuel for road freight provides an inter-seasonal energy store that accommodates variations in renewable energy supply. The advantages and disadvantages are considered of midday electric vehicle charging vs. overnight charging considering the temporal variations in supply of renewable energy and demand for transport services. There appears to be little to choose between these two options in terms of total system costs. The result is an energy scenario for decarbonized surface transport in India, based on renewable energy, that is possible, realistically achievable, and affordable in a time frame of year 2050. [ABSTRACT FROM AUTHOR]

Abstract: This paper deals the policy and planning issues for utilization of ethanol and biodiesel in automotive diesel engines in Indian context in view of environmental benefits, energy self-sufficiency and boosting of the rural economy as well as measures related to implementation and barriers. The main focus of this paper is on transport and refinery scenario, land availability for production of biodiesel and potential sources for biodiesel and ethanol. The availability of ethanol and estimations for its consumption as transport fuel are made and necessary remedial measures to increase the availability of ethanol in the country in future are suggested. [Copyright &y& Elsevier]

This research aims to bridge the gaps to produce sustainable energy cost-effectively and technically efficient. The paper explores the techno-economic-environmental viability of photovoltaic (PV)/biomass energy potential for a rural village, Sidhwanbet, Punjab, India. The data investigation was performed by HOMER Pro v3.14 software. A hybrid renewable energy system (HRES) was designed, simulated and modelled to ensure the continuous energy supply for 770 households. The proposed optimal HRES consists of a PV module, biomass generator, converter and battery with the static specification and further improved by optimization. The optimal HRES out of the best five configurations was elected with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) based on net present cost (NPC), cost of energy generation (COE), operating cost (ƠƇ), initial capital cost (ƗƇƇ), energy generation (ĖƓ), and a renewable fraction (Ȓϯ). The selected optimal HRES has been analyzed for economic, renewable energy and environmental aspects. The sensitivity study had performed while considering the discount and inflation rate. A simulation was performed for a 10-kW biomass generator, 1.1 kW solar array, five lithium-ion batteries, and a 3.96 kW converter. Results revealed that the PV's payback period (PBP) was 1.58 years, less than the useful life of optimal HRES. The cost of constructing an HRES for 25 years was equivalent to $21087, including initial cost, operating, replacement, and project costs. Thus, 35.6% of the necessary electricity is generated with PV and 64.4% biomass under optimal conditions for a 100% renewable energy integration. The CO 2 /year emission performance of optimal HRES is much better than Grid-only and PV-diesel generators. This technique may be used in rural regions in every other developing nation. [Display omitted] • Study of hybrid PV/Biomass/Battery energy for India rural area. • Design and optimization for off-grid electricity generation system using HOMER. • Technically and financially viable optimal configuration costs 0.0362 $/kWh. • System performance economically and environmentally analyzed by sensitivity analysis. • HRES reduced GHG compared to conventional grid and PV-biogas generator only. [ABSTRACT FROM AUTHOR]

With the negative climate impact of fossil fuel power generation and the requirement of global policy to shift towards a green mix of energy production, the investment in renewable energy is an opportunity in developing countries. However, poor economy associated with limited income, funds availability, and regulations governing project funding and development are key factors that challenge investors in the energy sector. Given the various power generation resources, including renewables, it is necessary to evaluate the possible power generation investment options from an economic perspective. To realize this objective, solar PV, wind and diesel power generations are economically compared, considering the incremental rate of return and incremental benefit to cost ratio techniques. The alternative investment options of distributed generation technologies are evaluated for Maharashtra, India under different depreciation methods, and the effect of the latter on selecting the best investment candidate is investigated. The paper also conducts sensitivity analysis to examine the impact of capital cost, operation and maintenance cost, and fuel cost variations on the selection decision considering a comparison of the different general projects' cash flow structures discussed in the literature. The economic aspects of selecting a project among possible alternatives for an investment in the power sector are analyzed, and the presented review provides comprehensive comparisons with respect to the literature approaches. The results reveal that, in the benchmark case study, the PV project is rejected and disregarded from further comparisons with other candidate projects since its equity internal rate of return (10.25%) is less than the minimum accepted rate of return, leaving the selection between wind and diesel energy projects. The study reveals that the incremental rates of return under such a comparison are 37.88%, 45.94% and 37.50% when MACRS, declining balance and straight line depreciations techniques are applied, respectively. Thus, the wind energy project is the favored option in this case. For the economic assessment of other case studies, the application of both sensitivity analysis on the capital cost and operation and maintenance cost and literature approaches to structure the projects reveal that wind energy for Maharashtra, India is a more attractive and feasible option compared to other distribution generation projects, while diesel is only considered to be a good option when its fuel cost is reduced by 5%. Finally, the paper highlights policy implications that can influence the decision to move towards investment in distributed generation technologies as a future research direction. [ABSTRACT FROM AUTHOR]

Globally, all countries have producing different levels of carbon emissions and also facing both the problems of climate change and global warming due high carbon emissions in the atmosphere. Therefore, it is important to cutting carbon emissions in the atmosphere. This is only possible by switching to cleaner fuels, use of innovation technologies and development of carbon capture storages. These can substantially help the nations to reaching carbon neutrality. Given this background, t his paper examines the effect of disaggregated energy consumption, technological innovations, capital on economic output and CO 2 emissions in India for the period of 1990–2018. Based on empirical analysis, our long-run elasticities indicate that disaggregated energy consumption and technological innovations have a positive impact on economic growth, while renewable energy consumption and technological innovations have a positive impact on CO 2 emissions. It implies that more use of energy consumption producing significant amount of CO 2 emissions and by using renewable energy consumption and technological innovations (i.e. carbon capture storages) can significantly lowering CO 2 emissions, which is clearly indicating that India has moving towards carbon neutrality. The causality analysis further indicates a unidirectional causal relationship running from disaggregated energy usage to economic growth and carbon emissions. These empirical findings suggest that the increased consumption of renewable power does not lead to rise carbon emissions, which, in turn, ensures sustainable economic growth. • Examines the disaggregated energy consumption, technological innovations, capital on economic output and CO 2 emissions. • Time series data from 1990 to 2018 was used to analyze the empirical results. • Disaggregated energy consumption and technological innovations have a positive impact on economic growth. • Renewable energy consumption and technological innovations have a positive impact on CO 2 emissions. • Suggest that increased in consumption of renewable power does not lead to rise carbon emissions. [ABSTRACT FROM AUTHOR]

In the context of energy security, rural development and climate change, India actively promotes the cultivation of Jatropha curcas, a biodiesel feedstock which has been identified as suitable for achieving the Indian target of 20% biofuel blending by 2017. In this paper, we present results concerning the range of environmental impacts of different Jatropha curcas cultivation systems.Moreover, nine agronomic trials in Andhra Pradesh are analysed, in which the yield was measured as a function of different inputs such as water, fertilizer, pesticides, and arbuscular mycorrhizal fungi. Further, the environmental impact of the whole Jatropha curcas biodiesel value chain is benchmarked with fossil diesel, following the ISO 14040/44 life cycle assessment procedure. Overall, this study shows that the use of Jatropha curcas biodiesel generally reduces the global warming potential and the nonrenewable energy demand as compared to fossil diesel. On the other hand, the environmental impacts on acidification, ecotoxicity, eutrophication, and water depletion all showed increases. Key for reducing the environmental impact of Jatropha curcas biodiesel is the resource efficiency during crop cultivation (especially mineral fertilizer application) and the optimal site selection of the Jatropha curcas plantations. [ABSTRACT FROM AUTHOR]

Abstract: Sensitivity analysis is a technique that evaluates the model response to changes in input assumptions. Due to uncertain prices of primary fuels in the world market, Government regulations for sustainability and various other technical parameters there is a need to analyze the techno-economic parameters which play an important role in policy formulations. This paper examines the variations in technical as well as economic parameters that can mostly affect the energy policy of India. MARKAL energy simulation model has been used to analyze the uncertainty in all techno-economic parameters. Various ranges of input parameters are adopted from previous studies. The results show that at lower discount rate coal is the least preferred technology and correspondingly carbon emission reduction. With increased gas and nuclear fuel prices they disappear from the allocations of energy mix. [Copyright &y& Elsevier]

The hydrological interdependence of plants in cascaded hydroelectric system means that operation of any plant has an effect on water levels and storage at other plants in the system. Hydro-logically efficient operation of power plants in such cascaded system requires that water resources should be managed efficiently, so that it can dispatched to predicted demand considering all physical and operational constraints. Meta-heuristic optimization techniques particularly Particle Swarm Optimization (PSO) and its variants have been successfully used to solve such problem. In this paper Time Varying Acceleration coefficients PSO (TVAC_PSO) has been used to determine the optimal generation schedule of real operated cascaded hydroelectric system located at Narmada river in state Madhya Pradesh, India. Results thus obtained from TVAC_PSO are compared with Novel Self Adaptive Inertia Weight PSO (NSAIW_PSO) and found to give better solution. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, energy metrics (energy pay back time, electricity production factor and life cycle conversion efficiency) of hybrid photovoltaic (PV) modules have been analyzed and presented for the composite climate of New Delhi, India. For this purpose, it is necessary to calculate (1) the energy consumption in making different components of the PV modules and (2) the annual energy (electrical and thermal) available from the hybrid-PV modules. A set of mathematical relations have been reformulated for computation of the energy metrics. The manufacturing energy, material production energy, energy use and distribution energy of the system have been taken into account, to determine the embodied energy for the hybrid-PV modules. The embodied energy and annual energy outputs have been used for evaluation of the energy metrics. For hybrid PV module, it has been observed that the EPBT gets significantly reduced by taking into account the increase in annual energy availability of the thermal energy in addition to the electrical energy. The values of EPF and LCCE of hybrid PV module become higher as expected. [Copyright &y& Elsevier]

This paper uses the data from seven wind farms at Muppandal, Tamil Nadu, India, collected for three years from April 2002 to March 2005 for the estimation of energy yield from wind farms. The model is developed with the help of neural network methodology, and it involves three input variables-wind speed, relative humidity, and generation hours-and one output variable, which give the energy output from wind farms. The modeling is done using MATLAB software. The most appropriate neural network configuration after trial and error is found to be 3-5-1 (3 input layer neurons, 5 hidden layer neurons, 1 output layer neuron). The mean square error for the estimated values with respect to the measured data is 7.6 × 10-3. The results demonstrate that this work is an efficient energy yield estimation tool for wind farms. [ABSTRACT FROM AUTHOR]

Higher penetration of variable renewable energy sources into the grid brings down the plant load factor of thermal power plants. However, during sudden changes in load, the thermal power plants support the grid, though at higher ramping rates and with inefficient operation. Hence, further renewable additions must be backed by battery energy storage systems to limit the ramping rate of a thermal power plant and to avoid deploying diesel generators. In this paper, battery-integrated renewable energy systems that include floating solar, bifacial rooftop, and wind energy systems are evaluated for a designated smart city in India to reduce ramping support by a thermal power plant. Two variants of adaptive-local-attractor-based quantum-behaved particle swarm optimization (ALA-QPSO) are applied for optimal sizing of battery-integrated and hybrid renewable energy sources to minimize the levelized cost of energy (LCoE), battery life cycle loss (LCL), and loss of power supply probability (LPSP). The obtained results are then compared with four variants of differential evolution. The results show that out of 427 MW of the energy potential, an optimal set of hybrid renewable energy sources containing 274 MW of rooftop PV, 99 MW of floating PV, and 60 MW of wind energy systems supported by 131 MWh of batteries results in an LPSP of 0.005%, an LCoE of 0.077 USD/kW, and an LCL of 0.0087. A sensitivity analysis of the results obtained through ALA-QPSO is performed to assess the impact of damage to batteries and unplanned load appreciation, and it is found that the optimal set results in more energy sustainability. [ABSTRACT FROM AUTHOR]

Agriculture residue is a promising resource of energy. It can be seen as a source of power production. In India, there is a huge amount of biomass available, but it cannot be used in proper ways, and with the help of GIS it can be customised. In the present paper, it is estimated that biomass reserves are available for power generation. The biomass produced by the surplus agricultural crops is reflected as a source of fuel for electricity generation. The data taken by satellite are useful for assessment of the areas with the help of satellite images taken in high resolution, which increases the preciseness of estimation. An agriculture cropland map with agricultural statistics has been analyzed in GIS to discover the agricultural straw potential for bioenergy generation. Due to unawareness about the benefits and uses of GIS, the modern farming sector bears a loss of huge bioenergy potential every year. To overcome the above mentioned challenges, the agricultural system needs a major shift from conventional farming to smart farming practices with the help of GIS. Agricultural waste is the best source for bioenergy production, and it can be used as biomass for meeting renewable energy goals in the country. [ABSTRACT FROM AUTHOR]

Reliable access to electricity is still a challenge in many developing countries. Indeed, rural areas in sub-Saharan Africa and developing countries such as India still encounter frequent power outages. Local energy markets (LEMs) have emerged as a low-cost solution enabling prosumers with power supply systems such as solar PV to sell their surplus of energy to other members of the local community. This paper proposes a one-to-one automated negotiation framework for peer-to-peer (P2P) local trading of electricity. Our framework uses an autonomous agent model to capture the preferences of both an electricity seller (consumer) and buyer (small local generator or prosumer), in terms of price and electricity quantities to be traded in different periods throughout a day. We develop a bilateral negotiation framework based on the well-known Rubinstein alternating offers protocol, in which the quantity of electricity and the price for different periods are aggregated into daily packages and negotiated between the buyer and seller agent. The framework is then implemented experimentally, with buyers and sellers adopting different negotiation strategies based on negotiation concession algorithms, such as linear heuristic or Boulware. Results show that this framework and agents modelling allow prosumers to increase their revenue while providing electricity access to the community at low cost. [ABSTRACT FROM AUTHOR]

Abstract: The on-going climate change concerns have stimulated heavy interest in biofuels, and supporters of biofuels hail that they are considered naturally carbon-neutral. Critiques on the other hand cry that the large-scale production of biofuels can not only strain agricultural resources, but also threaten future food security. People who live in the drylands of India are often faced with challenges and constraints of poverty. Foremost among the challenges are the marginal environmental conditions for agriculture, often influenced by low and erratic rainfall, frequent droughts, poor soil condition, unreliable irrigation water supply, and rural migration to urban areas in search of work. In this paper, we have analyzed a case study of community lift irrigation practiced in India and its impact in boosting agricultural productivity and enhancing local food security. The lift-irrigation model practiced in the drylands of India to grow food crops can be adopted for the expansion of biofuel crops that has the potential to eradicate poverty among farming communities if appropriate sustainable development measures are carefully implemented. [Copyright &y& Elsevier]