Abstract
Energy storage systems will play a key role for individual users in the future smart grid. They serve two purposes: (i) handling the intermittent nature of renewable energy resources for a more reliable and efficient system; and (ii) preventing the impact of blackouts on users and allowing for more independence from the grid, while saving money through load-shifting. In this paper we investigate the latter scenario by looking at a neighbourhood of 25 households whose demand is satisfied by one utility company. Assuming the users possess lithium-ion batteries, we answer the question of how each household can make the best use of their individual storage system given a real-time pricing policy. To this end, each user is modelled as a player of a non-cooperative scheduling game. The novelty of the game lies in the advanced battery model, which incorporates charging and discharging characteristics of lithium-ion batteries. The action set for each player comprises day-ahead schedules of their respective battery usage. We analyse different user behaviour and are able to obtain a realistic and applicable understanding of the potential of these systems. As a result, we show the correlation between the efficiency of the battery and the outcome of the game.
Highlights
Demand-side management (DSM) usually refers to the control of energy consumption by the utility company at the customer side
For a quantitative analysis of the load-shifting phenomenon, and since our aim is to reduce consumption during peak times, we look at the peak-to-average ratio (PAR) of the aggregated load for each individual day; i.e., max(t)∈T L(t)
We proposed an advanced battery model for a DSM program: residential customers play a battery scheduling game to decrease their own costs which eventually reduce the PAR value of the aggregated neighbourhood load
Summary
Demand-side management (DSM) usually refers to the control of energy consumption by the utility company at the customer side. It relies on the two-way communication and energy transmission capabilities of the future smart grid [1]. The utility company can indirectly incentivise the users to shift these loads themselves by time-of-use tariffs. Within these tariff schemes, the price per energy unit changes depending on the aggregated load of all users (cf [5,6,7]). Both ways can lead to a reduction of the peak-to-average ratio (PAR) in load, which in turn increases the stability and power quality of the grid [4]
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