Energetic, Cost, and Comfort Performance of a Nearly-Zero Energy Building Including Rule-Based Control of Four Sources of Energy Flexibility

Abstract

A focal point of ongoing research is matching the energy demand in the built environment to the energy supply from onsite generation, to maximize the self-consumption, and from the energy grids, to lower energy costs and reduce peak loads on the system. Energy flexibility addresses this task by modulating the energy demand in a building according to dynamic criteria such as electricity prices or onsite generation. This study addresses the potential of building performance simulation with real time rule-based control that provides energy flexibility based on onsite generation and hourly electricity prices, prioritizing energy matching, and reducing costs. The novelty relies on investigating four sources of energy flexibility simultaneously: shiftable machine loads, charging/discharging of batteries, hot-water storage tanks, and the building’s mass. The energy matching and flexibility actions provided a decrease of up to 4% in annual energy costs, yet risk increasing the cost by 9% when the savings are offset by the increase in the energy demand. As well, the method for price categorization strongly influences the cost performance of the flexibility actions. The outcomes of this study provide insight to energy flexibility sources in nearly-zero energy buildings and how their outcomes are affected by price thresholds.

Energy Flexibility and towards Resilience in New and Old Residential Houses in Cold Climates: A Techno-Economic Analysis

“…Similarly, it has been found that 14% of the energy demand and cost can be reduced in commercial buildings by implementing energy flexibility for heating and cooling [15]. An experimental study shows that the energy flexibility action can reduce the energy cost by 4% depending on the flexibility options available [16]. Integrating solar energy and energy storage such as phase change materials [17], batteries or tanks [16] can also be used for better flexibility.…”

“…An experimental study shows that the energy flexibility action can reduce the energy cost by 4% depending on the flexibility options available [16]. Integrating solar energy and energy storage such as phase change materials [17], batteries or tanks [16] can also be used for better flexibility. All the studies show that further analysis is needed to identify the benefits of energy flexibility in terms of cost and flexibility.…”

“…The rest of the price signals are normal prices. A similar approach is proposed by the authors of [16,43]. Using the price signals and percentiles, different activation cases are generated to identify the flexibility actions to be taken in the old and new buildings.…”

Deep Reinforcement Learning for Autonomous Water Heater Control

“…Perera and Skeie [14] presented a set of rule-based controllers that set setpoint and setback temperatures based on predefined occupancy schedules. Delgado et al [15] provided a rule-based controller for maximizing self-consumption and reducing costs. Rule-based approaches, however, do not take any future information (e.g., future price, future hot water usage) into account, and therefore their efficacy is limited [16].…”