Abstract
With the rapid growth of thermostatically controlled loads, active power fluctuation and peak demand growth within an autonomous micro-grid become serious problems. This paper tries to suppress power fluctuation and shave peak demand for a micro-grid through optimizing domestic electric water heaters (controllable load). In this paper, domestic electric water heater models are first built to optimize power flow within a single water heater. Subsequently, the Monte Carlo method is proposed to simulate power consumption of a cluster of domestic electric water heaters. After that, the temperature state priority list method is presented to suppress power flow and shave peak demand for a given micro-grid. Optimization results show that the proposed temperature state priority list method can reduce peak demand by 12.5%. However, it has a wider active power fluctuation range and needs a longer reaction time compared with the simplified temperature state priority list method. In addition, the optimization results show that by increasing the number of controllable loads participating in load scheduling, active power fluctuation can be reduced and the maximum active power of the given micro-grid can be cut. However, to achieve this, about 1.2% of extra electrical energy needs to be generated by the external grid.
Highlights
In recent years, the rapid growth of residential loads, especially for thermostatically controlled loads, has caused serious problems for power systems’ stable and economical operation [1,2]
To suppress power system active power fluctuation and shave peak demand, this paper proposes a load scheduling strategy shown in Figure 3 based on the temperature state priority list
2000 proposed simplified temperature state priority list method has Figure 9 reveals that the Simplified optimization successfully shifted the controllable load (100 domestic electric water heaters) and has shaved peak demand for the micro-grid
Summary
The rapid growth of residential loads, especially for thermostatically controlled loads, has caused serious problems for power systems’ stable and economical operation [1,2]. To make an effective thermostatically controlled load control strategy, it is important to change domestic users’ power consumption habits with the help of demand response technology [4]. In [6], a thermodynamic model representing the power system load due to hot water consumption from storage water heaters is provided This model makes it possible to predict the effects of load control and is useful for evaluation of the response which could be expected from demand-side management options. In [14], a direct load control strategy for domestic electric water heater is proposed to accommodate wind power generation in Hokkaido, which indicates that the acceptable wind power generation increases almost three times.
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