The EU Directive 2018/2001 recognized wastewater as a renewable heat source. Wastewater from domestic, industrial and commercial developments maintains considerable amounts of thermal energy after discharging into the sewer system. It is possible to recover this heat by using technologies like heat exchangers and heat pumps; and to reuse it to satisfy heating demands. This paper presents a review of the literature on wastewater heat recovery (WWHR) and its potential at different scales within the sewer system, including the component level, building level, sewer pipe network level, and wastewater treatment plant (WWTP) level. A systematic review is provided of the benefits and challenges of WWHR across each of these levels taking into consideration technical, economic and environmental aspects. This study analyzes important attributes of WWHR such as temperature and flow dynamics of the sewer system, impacts of WWHR on the environment, and legal regulations involved. Existing gaps in the WWHR field are also identified. It is concluded that WWHR has a significant potential to supply clean energy at a scale ranging from buildings to large communities and districts. Further attention to WWHR is needed from the research community, policymakers and other stakeholders to realize the full potential of this valuable renewable heat source.

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In this work, an algorithm for the scheduling of household appliances to reduce the energy cost and the peak-power consumption is proposed. The system architecture of a home energy management system (HEMS) is presented to operate the appliances. The dynamics of thermal and non-thermal appliances is represented into state-space model to formulate the scheduling task into a mixed-integer-linear-programming (MILP) optimization problem. Model predictive control (MPC) strategy is used to operate the appliances in real-time. The HEMS schedules the appliances in dynamic manner without any a priori knowledge of the load-consumption pattern. At the same time, the HEMS responds to the real-time electricity market and the external environmental conditions (solar radiation, ambient temperature, etc.). Simulation results exhibit the benefits of the proposed HEMS by showing the reduction of up to 70% in electricity cost and up to 57% in peak power consumption.