4.7 Article

Optimal economic dispatch policy for prosumer with energy storage considering self-consumption demand

Journal

COMPUTERS & INDUSTRIAL ENGINEERING
Volume 176, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2022.108853

Keywords

Prosumer; Energy storage; Distributed energy source; Dynamic programming; Self-consumption demand; Scheduling

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This study analyzed the effects of self-consumption demand on the joint economic dispatch of prosumers with energy storage and distributed energy sources. It identified two possible scenarios depending on whether the generation of distributed energy sources can meet prosumers' self-consumption. The study found the optimal storage scheduling strategy for each scenario and provided decision-making guidance for prosumers with energy storage based on dynamic programming.
This paper analyzed the effects of self-consumption demand on the joint economic dispatch of prosumers (energy consumers who are also producers), particularly for prosumers with both energy storage and distributed energy sources (DERs). Studies in the existing literature on the economic dispatch scheduling policy of energy storage, mostly from the perspective of electricity merchants, do not address the impacts of self-consumption demand. However, due to the intermittent and high levels of uncertainty regarding DERs generation and the dynamic demand of the prosumer, production and consumption are not always simultaneous; there are two possible scenarios in each period depending on whether DERs generation can meet prosumers' self-consumption or not. Incorporating the self-consumption demand will pose modeling challenges since these two scenarios cannot occur simultaneously in each period, and different scenarios require different decisions for prosumers. This paper analyzed the two scenarios separately to find the optimal storage scheduling strategy, and the results were combined to get the optimal global solution. We focused on prosumers' economic decision-making while considering self-consumption demand and the physical constraints of a battery based on dynamic programming. Our study showed that the feasible state of charge (SOC) range of storage can be segmented into several sub-ranges by SOC reference points under the above two scenarios. As a result, a prosumer's optimal scheduling can be uniquely and conveniently selected based on the sub-ranges within which the current SOC falls. The results, therefore, provided multistage decision-making guidance for prosumers with energy storage.

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