Sustainable planning of the energy-water-food nexus using decision making tools

Abstract

Developing countries struggle to implement suitable electric power and water services, failing to match infrastructure with urban expansion. Integrated modelling of urban water and power systems would facilitate the investment and planning processes, but there is a crucial gap to be filled with regards to extending models to incorporate the food supply in developing contexts. In this paper, a holistic methodology and platform to support the resilient and sustainable planning at city region level for multiple sectors was developed for applications in urban energy systems (UES) and the energy-water-food nexus, combining agent-based modelling - to simulate and forecast resource demands on spatial and temporal scales - with resource network optimization, which incorporates capital expenditures, operational costs, environmental impacts and the opportunity cost of food production foregone (OPF). Via a scenario based approach, innovative water supply and energy deployment policies are presented, which address the provision of clean energy for every citizen and demonstrate the potential effects of climate change. The results highlighted the vulnerability of Ghanas power generation infrastructure and the need for diversification. Feed-in tariffs and investment into supporting infrastructure and agriculture intensification will effectively increase the share of renewable energy and reduce carbon emissions

Optimizing dynamics of integrated food–energy–water systems under the risk of climate change

“…Optimizing the operations of FEWS requires identifying the management objective, constraints to the manager, strategies available to her, utilities corresponding to the operational costs, revenue, as well as the effect of exogenous (or uncontrolled) variables such as environmental variations. Once these are quantified, several approaches can be used to identify the management strategies and outcomes of such implementations on the FEWS operations in long-term, including mathematical programming (Rong et al 2012, Yu and Nagurney 2013, Zhang et al 2018, Bieber et al 2018, life-cycle assessment (Sherwood et al 2017, Wang et al 2017, Bell et al 2018, and scenario planning , Chaudhary et al 2018, Karan et al 2018. Although most of these studies focus on optimizing the crop production or food process life cycle, recent studies have focused on utilizing similar approaches to model and optimize the interconnected sectors.…”

“…Another important factor in integrated FEWS analysis is risk imbued by climate change. A few recent studies have evaluated the effect of climate change on crop production and operation within an integrated FEWS using dynamic forward simulation (Conway et al 2015, Berardy and Chester 2017, Baker et al 2018, Bieber et al 2018. Nevertheless, current efforts that incorporate climate change effects in FEWS analysis mostly rely on management strategy evaluation (Smith 1994), which is also known as scenario planning.…”

The NExus Solutions Tool (NEST) v1.0: an open platform for optimizing multi-scale energy–water–land system transformations

“…Generally, these studies demonstrate that co-optimization, in the sense that decisions for EWL sectors are made simultaneously and incorporate the interlinkages, can identify strategies that avoid tradeoffs and achieve synergies (Buras, 1979;Lall and Mays, 1981;Matsumoto and Mays, 1983;Huang et al, 2017;Kernan et al, 2017;Santhosh et al, 2014;Pereira-Cardenal et al, 2016;Dodder et al, 2016;Oikonomou and Parvania, 2018). Similarly, previous analyses integrated water, energy and food systems across multiple temporal and spatial scales, and quantified the economic benefits that joint water-energy planning can provide by reducing the investment and operational costs of future infrastructure systems (Howells et al, 2013;Dubreuil et al, 2013;Parkinson et al, 2016;Zhang and Vesselinov, 2017;Khan et al, 2018;Bieber et al, 2018;Wang et al, 2018;Li et al, 2019;Vakilifard et al, 2019). Land-use impacts of energy decisions, including bioenergy supply-chain interactions, are also increasingly integrated into long-term energy planning models to provide improved estimates of biomass availability and cost (Mesfun et al, 2018;Akhtari et al, 2018;de Carvalho Köberle, 2018).…”

“…Moreover, the individual resource planning models require specific expertise to develop and run, and it can be time consuming to design and implement a robust database for the model inputs and results, as well as online systems for sharing and merging model changes across different users. Other recent model developments are focusing mainly on water infrastructure (Payet-Burin et al, 2019) or city-scale scenarios (Bieber et al, 2018;McManamay et al, 2019), leaving room for improvement in terms of the sectoral and geographic scope for solutions.…”

Coal-Electric Power Supply Chain Reduction and Operation Strategy under the Cap-and-Trade Model and Green Financial Background

“…The optimal operation strategies are switched when the above two policies are applied, and in the meantime, the variables influence each other [8]. Furthermore, the feed-in tariffs and investment in auxiliary equipment and agriculture intensification effectively expand the portion of renewable energy, and at the same time, it could reduce carbon emissions [9]. On the practical side, a Danish case study did not consider the characteristics of industry sectors other than thinking about the structure of industrial energy, its whole produce procedure, the part of energy consumption, and calculations for fossil fuel reduction [10].This study uses the reverse induction of the Stackelberg model game theory, a productive leading model; it selects the coal enterprise as the starting point, builds two-stage equilibrium, and decides on the quantity and price of carbon reduction in China.…”