Integrations of renewable energies, particularly solar and wind, are increasing worldwide due to carbon emission reduction efforts and maturing technologies that have driven down the cost of their energy productions. Due to the intermittency of these renewable sources, the battery energy storage system often coexists alongside solar/wind energy systems. Integrating these two aspects into power systems requires the consideration of reliability, social wellbeing and environmental factors, which collectively form a multi-objective optimization problem that this paper aims to solve with the non-dominated sorting genetic algorithm. The proposed method is able to find optimum solutions that are equally beneficial to all factors – Pareto front – without being heavily biased to any one of them. The proposed method is separated into two parts by first optimizing the penetration of solar/wind energy, followed by the optimization of the energy storage capacity in the second part. The fuzzy decision making method is utilized to select a preferred solution from the Pareto front based on the assignment of the membership function values to reflect operator’s preferences. The proposed method was implemented on the IEEE Reliability Test System overlaid with the real sampled weather data. The proposed objectives in the optimization problem are also practical and useful for the expansion of generation systems.

Introduction

The supply of energy is a critical part of sustainable development manifestation [1] and the power generation sector is constantly evolving to become more reliable while maintaining competitive operation costs without adversely impacting the wellbeing of society [2]. The term ‘reliable’ is defined as the ability of the generation system to adequately supply power to meet load demands [3], [4]. Hence, technical, economic and social aspects are the cornerstones of power network developments [5]. One of the strategies to achieve the sustainable production of energy is through the wide scale implementation of renewable energy (RE) sources as most of them have no carbon emission and they are therefore environmental friendly [6]. A main feature of the RE sources is its unlimited supply, but the downside risk is their intermittency property. Due to this, there are considerable concerns that question the ability of such a generation system to fill the energy gap caused by RE units during episodes of their intermittency. Hence, the common practice is to restrict the integration of RE within a certain percentage of system load to maintain system reliability [7]. However, this reduces the reliance on RE which contradicts the aim to minimize fossil fuel usage in power generation [8]. Consequently, technologies that are able to alleviate the intermittency problem of RE sources is needed and, studies have shown that the energy storage systems (ESSs) is able to store the extra energy produced during times of excesses for later usage [9].