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A simulation-assessment-optimization approach towards energy self-sufficiency and carbon reduction in regional-scale sewage systems

https://doi.org/10.1016/j.resconrec.2022.106595Get rights and content

Highlights

  • An integrated renewable energy management approach was proposed for sewage system.

  • Uncertainty and nonlinearity were considered in a decision-making framework.

  • Configurations of renewable energy facilities were optimized for energy self-sufficiency.

  • Sensitivity to market price and carbon trading potential were analyzed.

Abstract

Utilizing renewable energy is a practical pathway for realizing energy self-sufficiency and offsetting carbon emissions in wastewater treatment plants (WWTPs). The holistic optimization of hybrid renewable energy of multiple WWTPs overweighs individual WWTPs studies by providing global optimal solutions and cost-effective resources management schemes with expended spatial scales. Few studies have focused on the overall optimal utilization and management of hybrid renewable energy from WWTPs on a regional scale. This study aims to explore how to optimize the configuration of renewable energy facilities for multiple WWTPs to achieve the cost-effective use of renewable energy for the overall system. Uncertainty associated with PV power generation and the size effects of WWTPs were considered in the general framework to enhance the reliability and cost effectiveness of the utilization of renewable energy. The developed approach was then applied to the hybrid renewable energy management of a city-scale WWTP system comprising 31 plants in Guangzhou, China. Results indicated that the energy self-sufficiency of sewage systems can be realized by recovering renewable energy. The levelized cost of energy generation in the overall system was approximately 0.19 CNY/kW·h, and the overall reduction in greenhouse gas (GHG) emissions was approximately 129.5 t CO2-eq/d. The overall optimization reduced the total cost by approximately 3% than did the traditional individual WWTP studies. The thermal energy recovered from wastewater could further reduce the operational costs of WWTPs through carbon credit trading. The developed approach can also be applied to other areas of the world to promote sustainable wastewater treatment and strengthen the utilization of renewable energy.

Introduction

Sewage treatment is energy intensive (Campana et al., 2021). Energy consumption and greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) have recently attracted considerable attention (Niu et al., 2019). The energy consumption of WWTPs ranges from 0.3 to 0.8 kW·h/m3 (Hao et al., 2015; Hernández-Sancho et al., 2011). It has been reported that 1% of the total electrical energy countrywide is consumed by WWTPs, resulting in large carbon emissions (Molinos-Senante et al., 2018). However, the energy and resources in wastewater have long been ignored. The energy contained in sewage is approximately nine times that required for its treatment (Hao et al., 2015). Theoretically, the energy requirements of a conventional sewage treatment plant can be met through effective use of the internal energy of wastewater (Yang et al., 2020). There is an urgent need to integrate renewable energy as an energy resource for WWTPs to achieve energy self-sufficiency and carbon reduction (Hu et al., 2020; Wang et al., 2020). Furthermore, renewable energy facilities are confronted with financial pressure and uncertain information (Campana et al., 2021; Li et al., 2020; Sifakis et al., 2021). Thus, it is desirable to develop effective tools to support energy self-sufficiency and carbon reduction in WWTPs.

WWTP energy self-sufficiency usually refers to utilizing energy embedded in wastewater and waste to generate 100% or more of the energy required for operation without an external energy supply (Gu et al., 2017). Energy and nutrient recovery from sewage, solar, and wind energy collected from plants are two promising energy sources for sewage systems (Borzooei et al., 2019; Budych-Gorzna et al., 2016; Ji et al., 2021; Khiewwijit et al., 2015; Nakkasunchi et al., 2021; Niu et al., 2019; Simon-Várhelyi et al., 2020). Raw wastewater contains various types of recoverable renewable energy sources. Many advanced technologies have been developed and proven to be practical for energy recovery in WWTPs (Fetanat et al., 2021; Lee et al., 2017; Yan et al., 2020). For instance, chemical energy can be recovered and converted into electrical energy via anaerobic digestion and sludge incineration (McCarty et al., 2011; Seiple et al., 2017; Shen et al., 2015; Yang et al., 2020). Thermal energy can be obtained using wastewater source heat pumps (WSHPs) (Hepbasli et al., 2014; Huber et al., 2020) and other technologies (Bousquet et al., 2017; Gómez-Coma et al., 2020). On the other hand, energy collection from natural resources can provide a sustainable energy supply. Photovoltaic (PV) power generation is the most common method for collecting solar energy from the large surface of sewage treatment facilities (Bey et al., 2021; Gu et al., 2017; Mo and Zhang, 2013; Strazzabosco et al., 2019). In general, the power generated by anaerobic digestion and PV and thermal energy reclaimed from wastewater are available renewable energy sources in WWTPs (Hao et al., 2015). It is desirable to manage renewable energy capabilities so as to meet energy demands of plants with enhanced reliability.

Several researchers have investigated the management of renewable energy in individual WWTPs. For instance, the most efficient energy-recovery pathway was determined by utilizing a scenario analysis of a WWTP serving 2.5 million people (Liu et al., 2021). The energy recovery potential of middle-scale sewage treatments has been assessed through energy balance and quantitative mass analyses (Di Fraia et al., 2019; Sarpong et al., 2019). Chae and Kang (2013) estimated the ratio of production to consumption for renewable energy under various scenarios. Moreover, regression models have been developed to predict energy production potentials and select energy-recovery methods (Yang et al., 2020). Hao et al. (2015) developed simulation models to explore the correlation between energy consumption and energy recovery potential based on mass and energy balance analyses (Khiewwijit et al., 2015). Although methods based on scenario analyses and energy balance accounting provide an acceptable framework for energy management, global optimal schemes with respect to the size and capacity expansion of renewable facilities have been ignored.

Recent literature has presented a few techniques for the optimal sizing of renewable energy in WWTPs. Nguyen et al. (2020) proposed a multi-objective approach for determining the optimal size of a hybrid renewable energy system to satisfy the energy demands of a WWTP. Wang et al. (2020) presented an integrated energy system and optimal operation model based on the WSHPs and AD-CHP of a sewage treatment system. Movahed and Avami (2020) proposed an optimization approach using the total cost and production of biogas as objective functions. Campana et al. (2021) studied the optimization planning and operation strategy of a hybrid renewable energy system in a WWTP, considering the economic and energy demand balance. Lee et al. (2017) introduced a WWTP-CHP system utilizing a multi-objective genetic algorithm to determine the optimal design factor of a WWTP. Bustamante and Liao (2017) combined PV modules with biogas in a hybrid renewable energy system to realize self-sufficiency using an energy balance analysis of sewage systems. In summary, a literature review on WWTP renewable energy optimization is presented in Table 1.

The aforementioned studies provide a relevant background for this study by focusing on the configurations of renewable energy systems for sewage systems. In contrast to hybrid renewable energy systems, the intermittent and unreliable characteristics of renewable energy render single-source systems unreliable in satisfying the power loads for WWTP operation (Ghasemi and Enayatzare, 2018; Nguyen et al., 2020). Moreover, the energy self-sufficiency analysis of an individual plant can hardly be utilized as a reference for the energy recovery of other WWTPs (Longo et al., 2016). Previous studies have mainly focused on individual WWTPs and have lacked extrapolation. It is challenging for some small-scale WWTPs to realize the effective recovery of renewable energy because of economic limitations and geographical location (Hernandez-Chover et al., 2018; Larsen, 2015; Nakkasunchi et al., 2021). Hybrid renewable energy management (HREM) from the perspective of an individual plant loses the potential for overall optimization at larger scales, which may lead to increased total cost (Henriques et al., 2020). It is urgent to conduct energy self-sufficiency management of WWTPs on a regional-scale, from a systemic perspective.

Achieving energy self-sufficiency through renewable energy sources is a particularly complex issue for WWTPs. It involves nonlinearity (e.g., size effect) and uncertainty (e.g., availability of solar energy), which complicate the decision-making process. Mathematical programming methods, such as linear and non-linear programming, can solve complex and large-scale linear or nonlinear problems, which has been widely proven in regional planning efforts (Budak Duhbacı et al., 2021; Cai et al., 2019, 2009b). Piecewise linear programming is suitable for addressing technology selection and facility expansion problems that are characterized by size effect (Mansoor et al., 2021). In addition, the availability of solar energy resources is subject to natural variability (Cai et al., 2009a). However, piecewise linear programming cannot address the uncertainty of natural resource availability. Few existing management methods can comprehensively encompass the issues of waste discharge, economic costs, uncertainties, and renewable energy planning within an integrated modeling framework. Therefore, it is extremely urgent to develop a mathematical programming method that can tackle size effect and uncertainty in regional-scale sewage systems.

The goal of this study is to fill the research gaps in the optimal design of renewable energy sources facilities in regional-scale WWTPs and to provide an efficient and cost-effective approach to achieve energy self-sufficiency from a holistic perspective. The main contributions of this study are as follows:

  • a)

    Uncertainty associated with availability of solar energy resources and nonlinearity of size effect of WWTPs were considered to enhance the reliability and cost effectiveness of the utilization of renewable energy.

  • b)

    This study considered multiple WWTPs at a regional scale as a whole for hybrid renewable energy optimization, providing decision makers with an economical solution from a holistic perspective. The proposed integrated energy self-sufficiency (ESS) approach can provide theoretical support for energy self-sufficiency and carbon reduction planning of regional-scale sewage systems.

The rest of this paper is organized as follows. Section 2 details the methods of the proposed integrated framework. A practical example in Guangzhou, China for developing this study is detailed in Section 3. In Section 4, the discussions of results and the potential to reduce the GHG emissions are provided. Finally, conclusions are given in Section 5.

Section snippets

Methodology

Uncertainties and size effect exist in the HREM of regional-scale WWTPs. To address these scientific problems, an integrated approach is developed in this study to assess the energy consumption, energy recovery potential and support the optimal HREM schemes of regional-scale WWTPs.

The proposed approach consists of three steps: (1) establishing non-linear simulation model to obtain energy consumption of each WWTP; (2) developing evaluation model to assess the maximum available capacity of

Study problem

Guangzhou, the capital city of Guangdong province in China, is located at 23°06′N and 113°15′E. Guangzhou is one of the largest cities in Guangdong-Hong Kong-Macao Greater Bay Area (GBA) with a population of 18.7 million. The average daily sunshine duration was about 4.7 h. In recent decades, the economy of Guangzhou has leapt forward and the population continues to grow, leading to a rapid growth of energy demand. However, most conventional energy demands to be imported (e.g. about 94.9 fuel

Sensitivity analysis

The economic cost of the system comprised capital and operation costs. Therefore, a sensitivity analysis of the operational and capital cost changes of different renewable energy facilities was conducted to evaluate the impact on the system. Because of the limited solar peak radiation time under the pt level of 0.01, no PV module was constructed. Therefore, the capital and operational costs of the PV system had no impact on the total cost of the system. The operational cost of WSHPs is a

Conclusions

The ESS approach was developed to address the planning problem of renewable energy generation in regional-scale sewage treatment systems. This approach improves the reliability and cost effectiveness of existing HREM methods and provides a global optimal size and capacity expansion scheme for the system. Furthermore, it could promote renewable energy co-optimization planning for sewage treatment systems within a multi-period and multi-energy recovery process.

  • 1

    Based on multiple non-linear

CRediT authorship contribution statement

Xiao Ma: Conceptualization, Methodology, Data curation, Writing – original draft, Software. Tianyuan Zhang: Investigation, Writing – review & editing. Yulei Xie: Writing – review & editing. Qian Tan: Supervision, Validation, Writing – review & editing.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This research was supported by the National Natural Science Foundation of China (Grant No. 52125902), Program for Guangdong Introducing Innovative and Entrepreneurial Teams (2019ZT08L213) and Key Special Project for Introduced Talents Team of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (GML2019ZD0403). The authors are grateful to the editor and reviewers for their insightful comments and suggestions.

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