## 1 Introduction  
The quest for provision of affordable, clean, and reliable electricity supply is the key aspiration of many nations globally. These aspirations are portrayed by the commitment of most countries to the formulation and chartering of strategic policies that are targeted towards attaining 100% green energy transition in the near future [1]. Many countries have embarked on different sustainable energy pathways; for example Germany [2] and Sweden [3] aims to attain 100% renewable energy by 2050 while Hawaii in the United States has set 2045 as a target [4]. Several African countries have also taken significant steps and shown visible commitment towards massive green energy uptakes mainly by wind and solar energy. Countries such as Kenya [5], Ghana [6], Mauritius [7], Nigeria [8], Egypt, and South Africa [9] are currently making efforts in the integration of renewable energy technologies on both small and large scale. However, the incorporation of variable renewable energy resources (VREs) such as wind and solar energy increases the flexibility needs of a power system. Hence, to achieve an acceptable level of power system operation reliability, dynamic and vibrant control strategies need to be devised to balance the demand and supply using efficient flexibility mechanism [10]. Flexibility providers are, usually, adaptable resources needed to address the short-term mismatches between the instantaneous generated power and the load demand [11]. Most of the classical power system planning strategies comprises of segregated optimization models for power system design. These models generally comprise of three features which are component sizing to determine the optimal capacity configuration, unit commitment model to determine the optimal operation strategy, and electricity market strategies to evaluate optimal point-to-point energy transactions [12]. However, the segregated approach is not sufficient for achieving an optimally reliable system design; this is because the operational efficiency of power system relies highly on the time-based dispatchability and controllability of the system generating resources. Furthermore, with the increasing penetration of VREs, the controllability and dispatchability of power system generation sources becomes more complex. Hence, the planning for the transition towards a high VREs-based energy system requires an integrated system planning that involves the cost of component sizing and system flexibility [13]. A comprehensive investigation of the economic viability of different kinds of flexibility providers available for power systems is discussed in [14]. The cost of flexibility is defined as the additional cost required to integrate additional adaptable resources to address the intermittency of VREs integration. There are many sources of flexibility provider options; these includes system interconnection, demand-side management, supply-side management, storage technologies, etc. [15]. From the generation planning perspective, flexibility is investigated based on the ramping capability of the generators, the minimum possible attainable generation, increased cycles of shutdowns and startups for hybrid configuration as outlined in [16]. The idea of hybrid-energy system has also shown some significant growing interest as a valuable and efficient flexibility provider towards 100% VREs generation as shown in much recent research. The authors in [14] performed and provided a comprehensive framework for techno-economic flexibility analysis based on MILP optimization model by combining complimentary distribution generation alternatives such as thermal storage, heat pump, and cogeneration. The importance of the appropriate selection of complementary generating technologies coupled with energy storage system (ESS), with an improved optimal operation strategy, as a cost-effective path towards ensuring power system flexibility is highlighted in [17]. Electricity storage has played a valuable and significant central role in power system in many aspects [18].