Abstract
This paper proposes a probabilistic optimization method that produces optimal bidding curves to be submitted by an aggregator to the day-ahead electricity market and the intraday market, considering the flexible demand of his customers (based in time dependent resources such as batteries and shiftable demand) and taking into account the possible imbalance costs as well as the uncertainty of forecasts (market prices, demand, and renewable energy sources (RES) generation). The optimization strategy aims to minimize the total cost of the traded energy over a whole day, taking into account the intertemporal constraints. The proposed formulation leads to the solution of different linear optimization problems, following the natural temporal sequence of electricity spot markets. Intertemporal constraints regarding time dependent resources are fulfilled through a scheduling process performed after the day-ahead market clearing. Each of the different problems is of moderate dimension and requires short computation times. The benefits of the proposed strategy are assessed comparing the payments done by an aggregator over a sample period of one year following different deterministic and probabilistic strategies. Results show that probabilistic strategy reports better benefits for aggregators participating in power markets.
Highlights
The smart grid will be the future standard at the distribution level, after generalization of active demand and distributed generation, mainly from renewable energy sources
A method for producing optimal bidding curves for an aggregator participating in day-ahead and intraday markets has been presented
The method consists of different optimization problems which considers flexible consumption through shiftable demand and the use of batteries, and takes into account the uncertainty of the forecasts (RES generation, market prices, and fixed demand) and the likely imbalance costs
Summary
The smart grid will be the future standard at the distribution level, after generalization of active demand and distributed generation, mainly from renewable energy sources. The approach from the aggregator point of view is new and different from traditional producers and retailers regarding the supply-demand balance, the bounds of the possible imbalance incurred by the aggregator, and the uncertainties involved in the problem Considering these differences, the optimal participation of an aggregator in sequential electricity spot markets (only day-ahead and intraday markets are considered), with the objective of minimizing the cost of the traded energy is addressed in this paper. The proposed approach solves separate probabilistic optimization problems, which considers the uncertainty of market prices (day-ahead and intraday), RES generation and fixed demand, and takes into account the possible imbalance costs the aggregator may incur. Conclusions and future work are given at the end of the paper
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