Abstract
In this paper, we propose novel techniques to reduce total cost and peak load of factories from a customer point of view. We control energy storage system (ESS) to minimize the total electricity bill under the Korea commercial and industrial (KCI) tariff, which both considers peak load and time of use (ToU). Under the KCI tariff, the average peak load, which is the maximum among all average power consumptions measured every 15 min for the past 12 months, determines the monthly base cost, and thus peak load control is extremely critical. We aim to leverage ESS for both peak load reduction based on load prediction as well as energy arbitrage exploiting ToU. However, load prediction inevitably has uncertainty, which makes ESS operation challenging with KCI tariff. To tackle it, we apply robust optimization to minimize risk in a real environment. Our approach significantly reduces the peak load by 49.9% and the total cost by 10.8% compared to the case that does not consider load uncertainty. In doing this we also consider battery degradation cost and validate the practical use of the proposed techniques.
Highlights
The energy storage system (ESS) has become popular in recent times due to the proliferation of intermittent renewable energies such as wind and solar power [1]
Our results show that both total cost and peak load are reduced significantly by 10.8% and 49.9% respectively compared to the case of deterministic optimization that does not consider load uncertainty
In this paper we propose novel algorithms to minimize the total cost under the Korea commercial and industrial tariff system
Summary
The energy storage system (ESS) has become popular in recent times due to the proliferation of intermittent renewable energies such as wind and solar power [1]. Battery prices have been falling notably in recent years, and this enables consumers to have their own ESS to reduce electricity bill with the development of low cost energy storage devices [2]. From social welfare point of view, installing ESS is encouraged because it is possible to reduce peak load and resolve overload problems threatening operational reliability in a distribution network [3]. In this regard there have been many efforts to minimize electricity bill by using ESS [4,5,6,7,8].
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