Optimal Management of a Hybrid Renewable Energy System Coupled with a Membrane Bioreactor Using Enviro-Economic and Power Pinch Analyses for Sustainable Climate Change Adaption

This study proposed an optimal hybrid renewable energy system (HRES) to sustainably meet the dynamic electricity demand of a membrane bioreactor. The model-based HRES consists of solar photovoltaic panels, wind turbines, and battery banks with grid connectivity. Three scenarios, 101 sub-scenarios, and three management cases were defined to optimally design the system using a novel dual-scale optimization approach. At the system scale, the power-pinch analysis was applied to minimize both the size of components and the outsourced needed electricity (NE) from Vietnam’s electrical grid. At a local-scale, economic and environmental models were integrated, and the system was graphically optimized using a novel objective function, combined enviro-economic costs (CEECs). The results showed that the optimal CEECs were $850,710/year,$1,030,628/year, and $1,693,476/year for the management cases under good, moderate, and unhealthy air qualities, respectively. The smallest CEEC was obtained when 47% of the demand load of the membrane bioreactor was met using the HRES and the rest was supplied by the grid, resulting in 6,800,769 kg/year of CO2 emissions

Wastewater Treatment System Optimization for Sustainable Operation of the SHARON–Anammox Process under Varying Carbon/Nitrogen Loadings

Partial nitritation (PN) coupled with the anaerobic ammonium oxidation (Anammox) process has improved ammonium removal in wastewater treatment plants (WWTPs). The operation conditions of this process, i.e., the dissolved oxygen (DO) and the influent ammonium and nitrite concentrations, drive the process to an equilibrium to suppress nitrite-oxidizing bacteria and achieve a proper nitrite over ammonium (NO2/NH4) ratio. This study aimed to implement a set of control strategies in a WWTP model BSM2-SHAMX, combining PN in a single reactor system for high-activity ammonia removal over nitrite (SHARON) to an Anammox reactor, using proportional–integrative–derivative (PID) control and model predictive control (MPC) in a cascade. For correct coupling, the PN should maintain an output NO2/NH4 ratio between 1 and 1.3, suitable for the Anammox process. In the cascade controller feedback loop, the primary control loop controls the NO2/NH4 ratio through the DO concentration from the secondary control loop, which guarantees better effluent nitrogen removal. The performance of the plant was assessed by evaluating the control strategies with different influent carbon/nitrogen (C/N) loadings. The study results showed that the MPC controllers provided better results, with an improvement of 36% in the operational cost compared to the base case with a cost around 26,000 EUR/d, and better nitrogen removal surpassing 90% removal, 10% more than the base case

Integrated hydrogen supply networks for waste biogas upgrading and hybrid carbon-hydrogen pinch analysis under hydrogen demand uncertainty

This study aims to develop integrated hydrogen supply networks (IHSNs) by combining a natural gas hydrogen supply network and a sludge-biogas-biomethane-hydrogen supply network which is an environmentally benign hydrogen production system. Sludge from wastewater treatment plants is converted into biogas by anaerobic digestion, biomethane is generated using amine technology, which is one of the biogas upgrading technologies, and finally, hydrogen is produced by steam reforming. Multi-objective two-stage stochastic mixed integer linear programming is used to simultaneously optimize the total annual cost and the total environmental cost under hydrogen demand uncertainty. An ɛ-constraint method is employed to solve the multi-objective function, and Pareto analysis is performed to compare the results from the economic cost and the environmental cost. Then, hybrid carbon-hydrogen pinch analysis is suggested to investigate two distinct hydrogen supply networks in IHSNs, and is verified by the results and a sensitivity analysis based on supplementary wind power. Gyeongsang-do where is one of the five provinces in the Republic of Korea is applied for a case study to validate the proposed model and the results illustrate the feasibility of IHSNs.11sciescopu

An Efficient Burst Detection and Isolation Monitoring System for Water Distribution Networks Using Multivariate Statistical Techniques

Detection and isolation of burst locations in water distribution networks (WDN) are challenging problems in urban management because burst events cause considerable economic, social, and environmental losses. In the present study, a novel monitoring and sensor placement approach is proposed for rapid and robust burst detection. Accordingly, a hybrid principal component analysis (PCA) and standardized exponential weighted moving average (EWMA) system is proposed for WDN monitoring and management. In addition, the optimal sensor configuration is obtained using PCA, k-means clustering, and a sensitivity analysis considering the diurnal patterns and the noises of pressure and flowrate data in the WDN. The proposed system is applied to a branched WDN, and the results are compared to those obtained with conventional monitoring systems. The results show that the proposed system detected the burst occurrence regardless of noise size with a detection rate of 93%. Compared to conventional systems, the isolation ratio improved by 10%, indicating that the bursts were isolated more accurately. In addition, the corresponding sensor configuration was 40% less expensive than the conventional systems