Emerging Tools for Energy System Design Increasing Economic and Environmental Sustainability

Analysis of the influence of the stay-at-home order on the electricity consumption in Chinese university dormitory buildings during the COVID-19 pandemic

During the COVID-19 pandemic, strict stay-at-home orders have been implemented in many Chinese universities in virus-hit regions. While changes in electricity consumption in the residential sector caused by COVID-19 have been thoroughly analysed, there is a lack of insight into the impact of the stay-at-home order on electricity consumption in university dormitory buildings. Based on questionnaire survey results, this study adopted the statistical Kaplan-Meier survival analysis to analyse the energy-use behaviours of university students in dormitories during the COVID-19 pandemic. The electricity load profiles of the dormitory buildings before and during the implementation of the stay-at-home order were generated and compared to quantitatively analyse the influence of COVID-19 pandemic on the energy-use behaviours of university students, and the proposed load forecasting method was validated by comparing the forecasting results with monitoring data on electricity consumption. The results showed that: 1) during the implementation of the stay-at-home order, electricity consumption in the university dormitory buildings increased by 41.05%; 2) due to the increased use of illuminating lamps, laptops, and public direct drinking machines, the daily electricity consumption increased most significantly from 13:00 to 18:00, with an increase rate of 97.15%; and 3) the morning peak shifted backward and the evening peak shifted forward, demonstrating the effect of implementing the stay-at-home order on reshaping load profiles.

Simulation and Analysis Approaches to Microgrid Systems Design: Emerging Trends and Sustainability Framework Application

Energy systems modelling and design are a critical aspect of planning and development among researchers, electricity planners, infrastructure developers, utilities, decision-makers, and other relevant stakeholders. However, to achieve a sustainable energy supply, the energy planning approach needs to integrate some key dimensions. Importantly, these dimensions are necessary to guide the simulation and evaluation. It is against this backdrop that this paper focuses on the simulation and analysis approaches for sustainable planning, design, and development of microgrids based on clean energy resources. The paper first provides a comprehensive review of the existing simulation tools and approaches used for designing energy generation technologies. It then discusses and compares the traditional strategies and the emerging trends in energy systems simulation based on the software employed, the type of problem to be solved, input parameters provided, and the expected output. The paper introduces a practical simulation framework for sustainable energy planning, which is based on the social-technical-economic-environmental-policy (STEEP) model. The STEEP represents a holistic sustainability model that considers the key energy systems planning dimensions compared to the traditional techno-economic model used in several existing simulation tools and analyses. The paper provides insights into data-driven analysis and energy modelling software development applications.

A mixed-integer linear programming approach for circular economy-led closed-loop supply chains in green reverse logistics network design under uncertainty

Purpose

To maximize the network total profit by calculating the difference between costs and revenue (first objective function). To maximize the positive impact on the environment by integrating GSCM factors in RL (second objective function). To calculate the efficiency of disassembly centers by SDEA method, which are selected as suppliers and maximize the total efficiency (third objective function). To evaluate the resources and total efficiency of the proposed model to facilitate the allocation resource process, to increase resource efficiency and to improve the efficiency of disassembly centers by Inverse DEA.

Design/methodology/approach

The design of a closed-loop logistics network for after-sales service for mobile phones and digital cameras has been developed by the mixed-integer linear programming method (MILP). Development of MILP method has been performed by simultaneously considering three main objectives including: total network profit, green supply chain factors (environmental sustainability) and maximizing the efficiency of disassembly centers. The proposed model of study is a six-level, multi-objective, single-period and multi-product that focuses on electrical waste. The efficiency of product return centers is calculated by SDEA method and the most efficient centers are selected.

Findings

The results of using the model in a case mining showed that, due to the use of green factors in network design, environmental pollution and undesirable disposal of some electronic waste were reduced. Also, with the reduction of waste disposal, valuable materials entered the market cycle and the network profit increased.

Originality/value

(1) Design a closed-loop reverse logistics network for after-sales services; (2) Introduce a multi-objective multi-echelon mixed integer linear programming model; (3) Sensitivity analysis use Inverse-DEA method to increase the efficiency of inefficient units; (4) Use the GSC factors and DEA method in reverse logistics network.

Impacts of COVID-19 on energy demand and consumption: Challenges, lessons and emerging opportunities

COVID-19 has caused great challenges to the energy industry. Potential new practices and social forms being facilitated by the pandemics are having impacts on energy demand and consumption. Spatial and temporal heterogeneities of impacts appear gradually due to the dynamics of pandemics and mitigation measures. This paper overviews the impacts and challenges of COVID-19 pandemics on energy demand and consumption and highlights energy-related lessons and emerging opportunities. The discussion on energy-related issues is divided into four main sections: emergency situation and its impacts, environmental impacts and stabilising energy demand, recovering energy demand, and lessons and emerging opportunities. The changes in energy requirements are compared and analysed from multiple perspectives according to available data and information. In general, although the overall energy demand declines, the spatial and temporal variations are complicated. The energy intensity has presented apparent changes, the extra energy for COVID-19 fighting is non-negligible for stabilising energy demand, and the energy recovery in different regions presents significant differences. A crucial issue has been to allocate and find energy-related emerging opportunities for the post pandemics. This study could offer a direction in opening new avenues for increasing energy efficiency and promoting energy saving.