Combining buildings and Electrochemical Batteries

Introduction

We have seen that commercial buildings are characterized by a large thermal inertia that can be exploited to modify their power consumption profile. Moreover, we have provided formal methods to quatify this flexibility in a concise manner by approximating the building capabilities by a virtual battery representation. Finally, we have demonstrated the validity of these methods in an experimental settings.

There is still a major issue to be discussed that precludes the direct partecipation of commercial buildings as service providers in current energy market. In fact, typical grid services require to modulate the power injection in a sub-second time range. However, operational constraints of the commercial HVAC equipment do not typically allow to modify the power consumption at a very high-frequency. As a result, additional elements as, for instance, Battery Energy Storage System (BESS) have to be considered.

Purpose of the experiment

In this setting, one would like to answer two main questions:

1) Is the combination of Building and BESS more efficient than having a BESS only, i.e., is there any synergistic behaviour we can exploit between these two elements?

2) Can we quantify what is the impact of the controllable building on the required BESS for the same provided service?

To answer these questions we looked at the particular service of Dispathcing the operation of a distribution feeder which comprises a set of heteroheneous resources. More precisely, the main objective is to track a composite power trajectory, called the \textit{dispatch plan}, which is computed the day before the beginning of operation. During real-time operation, due to the stochasticity of part of the resources in the feeder portfolio, tracking errors need to be absorbed in order to track the committed dispatch plan.

The goal of this study was to compare the performance of the system in the two following scenarios:

the tracking errors are absorbed by modulating the power consumption of a BESS,
the tracking errors are absorbed absorb by aggregately controlling the power injection of a BESS and of a controllable building (ME Building).

Results 14-12-16

Fig 1:Real-time operations for the dispatch tracking.

Upper: The black dashed line represents the dispatch plan for the CB whereas its actual realization is shown using a black solid line. Similarly, for the uncontrollable resources, the dashed orange line represents the day-ahead predicted power profile and the solid line its measured value.

Middle: The black dashed line represents the SOC reference. The experimental realization of the SOC is displayed in orange. The blue line is the simulated SOC in absence of the controllable building as previously explained.

Lower: Temperature variation for the difference zones of the controllable building. Each color corresponds to the measured temperature in a zone. In both the middle and lower plots, the gray area represents the allowed ranges for the plotted quantities.

Fig 2:  Sensitivy analysis between the percentage of controllable load into the feeder portfolio to the required BESS.

The graph clearly displays how even in a situation where only a small fraction of the loads are controllable has a significant impact on in terms of required BESS capacity.

In particular, it can be observed that having a 20% controllable buildings could result in roughly 80% battery reduction.

References:

L. Fabietti, T. T. Gorecki, E. Namor, F. Sossan and M. Paolone et al. Dispatching active distribution networks through electrochemical storage systems and demand side management. 1st IEEE Conference on Control Technology and Applications, Big Island, Hawaii, USA, August 27-30, 2017. Link
L. Fabietti, T. T. Gorecki, E. Namor, F. Sossan and M. Paolone et al. Enhancing the dispatchability of distribution networks through electric energy storage systems and flexible demand: Control architecture and experimental validation, Tech report

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