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.

https://www.mdpi.com/1996-1073/15/23/9126/pdf?version=1669904074

Economic Feasibility of a Renewable Integrated Hybrid Power Generation System for a Rural Village of Ladakh

The rapid development of solar and wind power, with their inherent uncertainties and intermittency, pose huge challenges to system stability. In this paper, a grid-connected hybrid power system that fully utilizes the complementarity characteristics in hydro, solar and wind power sources is proposed, which is capable of realizing an economic, managerial, social and environmental equilibrium in daily generation scheduling. A multi-objective optimization model is then proposed to determine the best possible solutions under nine typical scheduling scenarios, with ɛ-constraint method and fuzzy satisfying approach applied. A real case from the large-scale demonstration project in Qinghai, China clearly proved that the grid-connected hydro–solar–wind power system can provide significant comprehensive benefits. Specifically, on sunny days of normal season, the highest economic benefits can reach 1205820 ×104CNY, consumer surplus is up to 6760 ×104CNY, and the carbon emissions are as low as 159 ×103tonnes. Meanwhile, hydropower, preferred as a flexible renewable power source, can effectively conduct the peak regulation, making the residual loads deviation lowest of 740.447 MWh. Future studies can focus on the long-term perspectives, further analyze the storage technology, demand response and carbon taxes. 

Multi-objective generation scheduling towards grid-connected hydro–solar–wind power system based the coordination of economy, management, society, environment: A case study from China

This article presents a novel enhanced block-sparse adaptive Bayesian algorithm (EBSABA) to fully control proportional-integral (PI) controllers of superconducting magnetic energy storage (SMES) units. The main goal is to smooth the real power output from grid-tied wind farms (WFs) and enhance its power quality, which represents a significant concern in the industry. In this regard, two WFs are tied to the network and each one is equipped with a SMES unit. The proposed algorithm takes into consideration the effect of actuating error signal and its magnitude to online update the PI controller gains. The proposed control strategy is applied to all power electronic circuit converters. To obtain a realistic work, practical measured data of wind speed that recorded from Hokkaido Island are incorporated into the analyses. Moreover, a three-drive train model represents a turbine model. A practical 10 MW SMES unit is connected at the WFs terminals. The effectiveness of proposed SMES units is verified by comparing its results with those obtained by using the least mean square-PI SMES units and optimal PI SMES units by genetic algorithm under wind speed variability and uncertainty. The real power can be smoothened by more than 10% using the proposed system at some intervals. The validity of the study is tested by the simulation results that are carried out by PSCAD environment. The controlled SMES units can further improve the power quality of WFs. 

Enhanced block-sparse adaptive Bayesian algorithm based control strategy of superconducting magnetic energy storage units for wind farms power ripple minimization

Wasserstein metric-based two-stage distributionally robust optimization model for optimal daily peak shaving dispatch of cascade hydroplants under renewable energy uncertainties

Hydrogen production using solar energy is an important way to obtain hydrogen energy. However, the inherent intermittent and random characteristics of solar energy reduce the efficiency of hydrogen production. Therefore, it is necessary to add an energy storage system to the photovoltaic power hydrogen production system. This paper establishes a model of a photovoltaic power generation hydrogen system and optimizes the capacity configuration. Firstly, the mathematical model is modeled and analyzed, and the system is modeled using Matlab/Simulink; secondly, the principle of optimal configuration of energy storage capacity is analyzed to determine the optimization strategy, we propose the storage capacity configuration algorithm based on the low-pass filtering principle, and optimal time constant selection; finally, a case study is conducted, whose photovoltaic installed capacity of 30 MW, verifying the effectiveness of the proposed algorithm, analyzing the relationship between energy storage capacity and smoothing effect. The results show that as the cut-off frequency decreases, the energy storage capacity increases and the smoothing effect is more obvious. The proposed algorithm can effectively reduce the 1 h maximum power variation of PV power generation. In which the maximum power variation of PV generation 1 h before smoothing is 4.31 MW. We set four different sets of time constants, the maximum power variation of PV generation 1 h after smoothing is reduced to 0.751, 0.389, 0.078, and 0.04 MW, respectively.

/pdf/modeling-of-hydrogen-production-system-for-photovoltaic-2klvgi6k.pdf

Modeling of hydrogen production system for photovoltaic power generation and capacity optimization of energy storage system

Optimal design of hydro-wind-PV multi-energy complementary systems considering smooth power output

The use of renewable energy sources, such as wind, photovoltaics (PV), and hydropower, to supply facility agriculture may effectively mitigate food and environmental pollution problems and ensure continuity of the energy supply. The operating conditions of a hybrid system are complex, so the operating strategy is very important for system configuration and scheduling purposes. In the current study, first, a hybrid wind/PV/small-hydropower/facility-agricultural system was constructed. Then, the chaotic particle swarm method was applied to optimize hybrid system operation, and a scheduling strategy of the hybrid system was proposed. Finally, combined with an example, according to wind and PV power output and load curves, supply-to-load curves for wind, PV, and small hydropower were obtained. The operational strategy proposed in this study maximizes the utilization of wind and solar resources and rationally allocates hydropower resources. The aforementioned operational strategy provides a basis for hybrid system capacity allocation and scheduling.

/pdf/research-on-the-operational-strategy-of-the-hybrid-wind-pv-8jlec6x7.pdf

Huawei Li

Papers

Optimal design of hydro-wind-PV multi-energy complementary systems considering smooth power output

Modeling of hydrogen production system for photovoltaic power generation and capacity optimization of energy storage system

Research on the Operational Strategy of the Hybrid Wind/PV/Small-Hydropower/Facility-Agriculture System Based on a Microgrid