A Demand-Supply Matching-Based Approach for Mapping Renewable Resources Towards 100% Renewable Grids in 2050

Abstract

Recently, many renewable energy (RE) initiatives around the world are based on general frameworks that accommodate the regional assessment taking into account the mismatch of supply and demand with pre-set goals to reduce energy costs and harmful emissions. Hence, relying entirely on individual assessment and RE deployment scenarios may not be effective. Instead, developing a multifaceted RE assessment framework is vital to achieving these goals. In this study, a regional RE assessment approach is presented taking into account the mismatch of supply and demand with an emphasis on Photovoltaic (PV) and wind turbine systems. The study incorporates mapping of renewable resources optimized capacities for different configurations of PV and wind systems for multiple sites via test case. This approach not only optimizes system size but also provides the appropriate size at which the maximum renewable energy fraction in the regional power generation mix is maximized while reducing energy costs using MATLAB's ParetoSearch algorithm. The performance of the proposed approach is tested in a realistic test site, and the results demonstrate the potential for maximizing the RE share compared to the achievable previously reported fractions. The results indicate the importance of resource mapping based on energydemand matching rather than a quantitative assessment of anchorage sites. In the examined case study , the new assessment approach led to the identification of the best location for installing a hybrid PV / wind system with a storage system capable of achieving a nearly 100% autonomous RE system with Levelized cost of electricity of 0.05 USD/kWh.

Wind Energy Resource Assessment for Cook Islands With Accurate Estimation of Weibull Parameters Using Frequentist and Bayesian Methods

“…During the times of higher temperatures, the upward movement of air continues to reduce the velocity difference at the two heights of 20 m and 34 m AGL due to the bunching of streamlines and acceleration of flow at lower heights, which is clear from the figure. In their work on mapping renewable sources for 100% renewable grids in 2050, Al-Ghussain, et al [58] made their estimates with a wind shear coefficient of 1/7.…”

Effective Energy Management via False Data Detection Scheme for the Interconnected Smart Energy Hub–Microgrid System under Stochastic Framework

“…Thus, there is a universal intention to reduce the harmful environmental impacts of electricity production [4]. Recent investigations have demonstrated that if energy consumption stays at the same rate, fossil fuel reserves will be depleted in the next 50-60 years [5]. For this reason, the necessity for a more efficient method of connection between electricity generation and the consumers is highly apparent.…”

“…Besides, the right-handed part of the power balance equation is defined by load demands located at buses of the networked microgrid system. The power generation related to each unit is expressed in detail by Equations ( 3)- (5). The output power of PV units can be calculated by Equation (3) which complies with relevant PV capacity, the sun irradiation and the power loss consumed by cells.…”

Techno-Economic Assessment of a Grid-Independent Hybrid Power Plant for Co-Supplying a Remote Micro-Community with Electricity and Hydrogen

“…The proposed system to co-generate electricity and hydrogen consists of the components demonstrated in Table 1. In addition, some postulations, which are presented in the table below, should be taken into account in order to attain the purpose of the study [54][55][56][57]. Figure 2 presents the average electric load demanded by the 15 households in the under-study village on a monthly and hourly basis.…”