Optimal sizing approach for islanded microgrids

Abstract

This study proposes a single-objective optimal sizing approach for an islanded microgrid (IMG). The approach determines the optimal component sizes for the IMG, such that the life-cycle cost is minimised while a low loss of power supply probability (LPSP) is ensured. As wind speed and solar irradiation exhibit both diurnal and seasonal variations, the proposed algorithm takes advantages of the typical meteorological year-based chronological simulation and enumerationbased iterative techniques. The mathematical models presented in this study for the IMG components consider the non-linear characteristics as well as the reactive power. The LPSP is also formulated based on the supply-demand balances of both real and reactive powers, and an economic evaluation model is presented. The proposed sizing approach identifies the global minimum, and simultaneously provides the optimal component sizes as well as the power management strategies. This study also presents a number of sensitivity analyses as well as comparisons with a commercial software package.

Quantifying the Benefits of a Solar Home System-Based DC Microgrid for Rural Electrification

“…A recent study on optimal sizing of SHSs while increasing the battery lifetime, decreasing the excess unused energy, and reducing the loss of load probability (LLP)-a system metric quantifying the availability of power supply (described in detail in Section 2.3)-concluded that standalone SHSs are not tenable to be used for tier 4 and tier 5 level electrification [9]. In fact, the lowest LLP attainable by an optimally sized SHSs catering to tier 5 electricity demand was 0.029 [9], while several off-grid projects keep 0.02 as a lower limit of the LLP [11,12]. For off-grid systems, typical LLP values based on the specific application can be 0.01 and 0.0001 for domestic illumination and telecommunications respectively [13].…”

“…When it comes to modelling and simulating off-grid systems, LLP is an application specific or a user-defined constraint. For e.g., in [2], the LLP over a year was constrained to 1.8%, in [11,12] a similar metric had a minimum limit of 2%, while in [9] different LLP thresholds were investigated for SHSs applications.…”

A Heuristic Home Electric Energy Management System Considering Renewable Energy Availability

“…A simplified wind turbine model proposed in [22] is adopted in the present work. The model focuses on the operative behavior of the wind turbine in terms of the generated active power exclusively dependent on the incoming wind profiles.…”

“…In the former case, if energy storage units are available, the surplus energy generated by renewables is stored to be used when necessary; in the latter case, instead of drawing energy from the grid, energy storage units are used to feed the surplus load. A model for the energy storage unit considering not only these scenarios but also its self-discharge characteristic and efficiencies of the inverter and rectifier is proposed in [22]. This model has been adapted in terms of active power to be properly considered in the objective functions defined by Equations (2) and (3).…”

“…The extensive solutions search characteristic of the GAs is exploited to select an optimal solution with the best fitness from a set of non-dominated solutions in the sense of Pareto, i.e., at each iteration of the GA, Pareto front solutions are obtained and a solution with the best fitness is added to a reduced set of solutions; once iterations have finished, a new Pareto test and fitness evaluation is performed to the reduced set of solutions to obtain the best solution, reducing to one the number of solutions available to the user, and as consequence the computational time, which are two of the main goals of the proposal. Moreover, the proposed approach takes advantage of the good results reported in [21,22] to adapt the models of the household appliances, PV/wind energy generation and energy storage units (batteries).…”