Using energy storage to defer infrastructure investment



Electricity utilities are faced with a number of challenges relating to network infrastructure expansion. The common challenges are funding constraints, inability to obtain servitudes/right of way (ROW) in time, demand growth uncertainty and life extension of existing infrastructure. Energy storage systems (ESS) represent opportunities to reschedule large investment in the network infrastructure.

Fig. 1: Flow chart describing the process followed in the case study.

ESS can absorb excess energy during off-peak times and inject the stored energy when needed during the system peak. The storage devices can also support the grid in case of power system contingencies.

In some networks, the peak demand occurs only for a short period of time during the day (low load factor supplies), but the grid is planned and designed to accommodate the peak demand. In such instances, ESS is a feasible alternative to the traditional approach of increasing capacity to meet the peak demand. The ESS units are modular and can be deployed with little effort in the network. Hence, they can be used to alleviate grid congestions until a network strengthening plan can be implemented.

Optimal sizing and placement of the ESS in the power system is an important aspect to maximise the benefits of the ESS in the system. Sub-optimal placing and sizing of ESS can cause thermal and voltage problems in the network [1]. According to literature, the widely used methods to optimise the size and location of the ESS in the network are based on optimisation techniques. Optimisation techniques are well-suited for optimising the size of the ESS, but their capability regarding choosing the optimal placement of the ESS in the network is not very clear.

We propose using power-voltage (P-V) curves and modal analysis to optimise the location of the ESS on the network, especially in interconnected systems. The proposed method is based on knowledge from the location optimisation of reactive power compensation devices and distributed generators in a constrained network. This method is most relevant to networks experiencing thermal overloading and/or low voltage conditions. The study focuses on using ESS as an intermediate solution to address network constraints until capital and/or servitude challenges are resolved.

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Contact Jamila Kombe, Eskom, Tel 011 800-3300, kombej@eskom.co.za

 

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