Grant: Discovery Grants Program - Individual

OBJECTIVE: The research objective is to find optimal contribution among water, land, energy, and food, to balance the nexus between biofuel/hydrogen productions and solar/wind powers with considering both economic and environmental impacts under uncertainty. This objective is addressed using three sub-objectives: (1) sustainability assessment of biomass feedstocks; (2) coordination of various constraints to maximize biofuel production, minimize the overall cost and environmental impact under uncertainty; (3) development of optimal control system to the energy storage system. BACKGROUND: Solar and Wind energies are the most important resources of renewable energies but the lack of stability requires the use of energy storage systems (ESS). This study proposes a novel ESS that stores additional solar and wind renewable energy in hydrogen and biofuels and uses the stored energy when the solar and wind is not available. Hydrogen has high energy storage capacity. Biofuels can be produced from widely available biomass feedstocks. The proposed ESS is not only to eliminate the intermittency of wind and solar, but reduce greenhouse gas emissions. The research focuses on the production of biofuels from agriculture solid waste (ASW) and municipal solid waste (MSW) due to the large and scattered rural areas of western Canada and the increasing problem of municipal landfills. Consequently, the economic cost and environmental impact will be discussed in our proposed ESS under uncertainty. SCIENTIFIC APPROACH: 1). develop a methodology framework for assessing the sustainability level of feedstocks production in a region with combining satellite remote sensing, GIS techniques, and multi-attribute value theory. We distinguish four sustainability categories: land use, economic, environmental, and social, and each category has unique indicators. Each indicator will be weighted by Analytic Hierarchy Process (AHP) which depended on its contribution to biofuel production. 2). develop an inexact multi-objective linear programming (IMLP), where use inexact value (binary or interval) to represent uncertainty, to maximize total profit, including maximizing biofuel production, and minimizing economic cost and environmental impact. 3). develop a model predictive control (MPC) system, working with Extreme Gradient Boosting (Xgboost) and Long-Short-Term Memory (LSTM) neural network, to control the charging and discharging of energy storage systems. SIGNIFICANCE: The proposed project presents government officials with a new perspective on economic development, provides scientists and engineers with novel methods for energy storage control, biofuel conversion, and biomass sustainability assessment. Achieving the proposed goals will have significant positive economic, environmental, and social impacts in terms of reducing greenhouse gas emissions, improving power conversion efficiency, enhancing energy security, protecting the environment, and supporting agriculture.