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Modern day societies and economies are becoming increasingly vulnerable to the continued erosion of the stocks and flows of essential ecosystem services. Thus, the management of complex socio-economic systems to effectively provide these essential services has become a global priority policy and academic research area. Understanding how underlying processes and functions contribute towards the provision of final ecosystem services can facilitate improved dissemination of credible, legitimate and salient information to decision-makers. This paper presents an ecosystem service value chain analysis framework that applies basic system dynamics modelling in the form of causal loop diagrams to facilitate an alternative analysis of ecosystem service value chains. A scoping application of the framework is applied to a case study for flood attenuation services in the Baviaanskloof catchment in South Africa. The framework enables the identification of forward linkages and ripple effects in individual value chains of final ecosystem services as well as the identification and assessment of challenges and opportunities within individual causal pathways. Ultimately, providing the potential to advance strategies for improving the efficiency and effectiveness of final ecosystem service provision. [ABSTRACT FROM AUTHOR]

• The output power is conducted using 3D-PV model. • A new fusion of improved bi-archive multi-objective optimization algorithm is proposed. • A new hybrid MCDM method is considered to choose the most desirable configuration. • An accurate hybrid numerical method is used for validation of the proposed method. • Performance of optimum designs are evaluated for both cases: Malaysia and South Africa. Photovoltaic (PV) and Wind turbine (WT) systems are the most promising options for rural energy delivery. In the literature, numerous studies have simply considered only on economic efficiency, while maximizing dependability by a constant value for the given demand load. Moreover, a single set Pareto optimal front (PF) has been attained for the multi-objective optimization problem. Furthermore, the primary challenge of various the off-grid multiple renewable energy sources is excessive energy loss, resulting over/under sizing and a highly total cost for the system. Therefore, this paper presents a unique improved bi-archive approach to develop the diversity and convergence independently in order to find four optimum sets of PF solutions. In addition, a new integration based on best worst method (BWM) and preference ranking organization for enrichment evaluations (PROMETHEE II) method along with group decision making (GDM) mechanism are addressed to sort and rank the optimal sets PF solutions with full consistency ratios of the three experts opinions and high degree of stability in ranking configurations. The theoretical results based on actual hourly meteorological data in Malaysia and South Africa indicated that the suggested improved two-archive-BWM- PROMETHEE II-GDM method is not only able to construct a uniform set of Pareto optimal solutions with fast convergence and high diversity, but can also rank and select the most desired design for the PV/WT/Battery system. The optimum configurations of the two cases studies are composed of a single WT, 105 PV modules, and 69 batteries storages at zero LLP, 60185 ($) of LLC, and 13548018 (KWh) of P dump for Malaysia case study, meanwhile it composes of 16 WTs, 80 PV modules, and 69 batteries storage at zero of LLP, 66073 ($) of LCC, and 31371 (KWh) of P dump. The proposed standalone hybrid renewable energy sources system is verified and assessed in a comparison with existing hybrid methods in terms of increasing the reliability, lowering overall cost, and reducing wasted energy. [ABSTRACT FROM AUTHOR]