Resource estimation and sizing optimization of PV/micro hydro-based hybrid energy system in rural area of Western Himalayan Himachal Pradesh in India

Kumar, Sanjay; Kaur, Tarlochan; Arora, Manoj K.; Upadhyay, Subho

doi:10.1080/15567036.2019.1576075

Cited by 43 publications

(13 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The estimated solar potential using this ANN architecture has been used as an input for sizing of PV system for rural electrification in the Chamba district. 36…”

Section: Resultsmentioning

confidence: 99%

Efficient solar radiation estimation using cohesive artificial neural network technique with optimal synaptic weights

Kumar

Kaur

2019

Proceedings of the Institution of Mechanical Engineers, Part A:

View full text Add to dashboard Cite

Estimation of solar potential is vital for renewable energy applications. In several studies, artificial neural networks have been employed to model solar radiation using various meteorological parameters. The collection and availability of the most appropriate input parameters is important for getting an accurate artificial neural network model. The present study aims to estimate the global solar radiation using different meteorological parameters and identify the significant parameters based on the analysis of synaptic weights in an artificial neural network model using the connection weight approach. Initially, artificial neural network and empirical models is applied to estimate the solar radiation in Chamba region. The artificial neural network architecture 5-48-15-1 resulted in minimum mean absolute percentage error of 12.15%. The mean absolute percentage error values for linear models are found to be 18.95%, 15.39%, and 21.62%, respectively. Thereafter, connection weight approach is applied to find significant parameters. The efficacy of the approach has been shown through a case study related to estimation of solar radiations in the Hamirpur region situated in the state of Himachal Pradesh (India). Five input parameters, namely temperature (T), relative humidity (RH), clearness index (KT), precipitation (PT), and pressure (P), have been considered to estimate solar radiations using a feed-forward neural network. The proposed approach infers that temperature is the most significant parameter followed by humidity and pressure. The clearness index and precipitation has been found to have the least effect on the estimation of solar radiations. Results also indicate that artificial neural network based technique is more accurate compared to empirical model.

show abstract

“…The estimated solar potential using this ANN architecture has been used as an input for sizing of PV system for rural electrification in the Chamba district. 36…”

Section: Resultsmentioning

confidence: 99%

Efficient solar radiation estimation using cohesive artificial neural network technique with optimal synaptic weights

Kumar

Kaur

2019

Proceedings of the Institution of Mechanical Engineers, Part A:

View full text Add to dashboard Cite

show abstract

“…The operational performance of a PV-battery-based microgrid can be enhanced with suitable energy management strategies, and it can also contribute to demand-side management considering grid constraints. In the past few years, several research studies (Kumar et al 2019;Khatib et al 2015;Lang, Ammann, and Girod 2016;Liu et al 2012) have been conducted, and these studies are mainly focused on technical sizing and performance evaluation of grid connected rooftop PV system, off-grid system, and hybrid energy systems for different geographical regions. The study presented in ref (Kumar et al 2019), analyzed an ideal combination of a micro-hydro, photovoltaic, battery, and diesel generator to fulfill the electricity demand of rural village of Chamba District Himachal Pradesh in India however, this work has not included the sensitivity analysis of hybrid system with future energy tariffs.…”

Section: Introductionmentioning

confidence: 99%

“…In the past few years, several research studies (Kumar et al 2019;Khatib et al 2015;Lang, Ammann, and Girod 2016;Liu et al 2012) have been conducted, and these studies are mainly focused on technical sizing and performance evaluation of grid connected rooftop PV system, off-grid system, and hybrid energy systems for different geographical regions. The study presented in ref (Kumar et al 2019), analyzed an ideal combination of a micro-hydro, photovoltaic, battery, and diesel generator to fulfill the electricity demand of rural village of Chamba District Himachal Pradesh in India however, this work has not included the sensitivity analysis of hybrid system with future energy tariffs. An optimization approach is used in ref (Khatib et al 2015), for developing PV, wind and battery-based system for Kuala Terengganu, Malaysia whereas role of energy management strategy during grid outage conditions have not addressed.…”

Section: Introductionmentioning

confidence: 99%

“…The paper (Lang, Ammann, and Girod 2016) analyzed the potential of considering rooftop PV for different consumers considering technological, economical, and geographical factors but dynamics of electricity pricing has not sufficiently covered. In the most of reviewed literatures (Kumar et al 2019;Khatib et al 2015;Lang, Ammann, and Girod 2016;Liu et al 2012), impact of electrical energy pricing dynamics on techno-economic performance of microgrid system and role of energy management techniques for peak demand saving have not sufficiently covered.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Impacts of electricity pricing on techno-economic performance of photovoltaic-battery centered microgrid

Sharma

Kolhe

2021

Energy Sources, Part A: Recovery, Utilization, and Environmenta

View full text Add to dashboard Cite

The energy management technique in a microgrid, plays very crucial role for making it more economic viable during the electricity energy pricing dynamics. It is vital to investigate the impact of electricity energy pricing dynamics on operation and techno-economic performance of a micro-grid for maximizing the local energy participation with grid constraints. This paper has considered, a common PV-battery-based microgrid from Norway for assessing technical and economic performance with electricity energy pricing dynamics. In this work, energy management strategy has presented, for minimization of annual energy generation cost with maximization of battery energy throughput with grid constraints as network demand limits. It has been observed that grid buying price has more impacts on the cost of energy generation (CoE) as compare the grid selling price. While doubling the grid buying price, CoE is increased by 14% whereas doubling the grid selling price, CoE is reduced by 2%. This paper also included sensitivity analysis and analyzed that battery cost has highest impacts on CoE followed by PV cost and then grid tariffs. It has been noticed that doubling the cost of battery, PV and grid (one at a time) has increased CoE by 53, 31, and 27%, respectively. The operational energy management strategies presented in this paper, will certainly contribute for PV-battery-based micro-grid developments and evaluating operational performance under electricity energy pricing dynamics.

show abstract

“…Ming et al [43] developed a nesting model for optimal sizing of PV-hydro hybrid power system by minimizing the water consumption of hydro plant when external load requests are imposed to the hybrid system. Kumar et al [40] optimized sizing of hybrid energy system through Particle Swarm Optimization method.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Run-of-River Small Hydro-PV Hybrid Power Systems

et al. 2019

View full text Add to dashboard Cite

This paper presents the sizing of run-of-river small hydro-PV hybrid power system using the Non-dominated Sorting Genetic Algorithm (NSGA-II). The two objective functions are the total generated energy and the energy production cost of hybrid system. The total energy has been maximized whereas the energy production cost of hybrid system has been minimized. The nominal turbine flow rate ( ), the number of hydropower units ( ), and the number of PV modules () are considered as decision variables in this problem. The Yeripao site in Benin has been considered as case study. The optimal solutions converge to Pareto front which represent the best trade-offs between total generated energy and energy production cost. The results have shown that energy production cost increases with the total generated energy. Thus, minimizing the energy production cost is contradictory with maximizing the total generated energy. Moreover, the sensitivities analysis of and on the total generated energy and on energy production cost have been conducted in this study. It is relevant to note that the optimal solutions are grouped into four categories according to = , , . For each category, the total generated energies, energy production costs and cost per kWh increase with the . For = the lowest values of energy production costs, total generated energies and costs per kWh have been recorded. Moreover, = match with the solutions that present the highest total generated energies and costs. The lowest overall cost per kWh is € 0.363/kWh. The conducted study can be applied to other sites by using their hydro and solar resources characteristics.

show abstract

Resource estimation and sizing optimization of PV/micro hydro-based hybrid energy system in rural area of Western Himalayan Himachal Pradesh in India

Cited by 43 publications

References 16 publications

Efficient solar radiation estimation using cohesive artificial neural network technique with optimal synaptic weights

Efficient solar radiation estimation using cohesive artificial neural network technique with optimal synaptic weights

Impacts of electricity pricing on techno-economic performance of photovoltaic-battery centered microgrid

Multi-Objective Optimization of Run-of-River Small Hydro-PV Hybrid Power Systems

Contact Info

Product

Resources

About