Open AccessIntegrating storage in planning of LV distribution networks with PV production
Author(s) -
Hadjsaid Ahmed,
AlvarezHerault MarieCecile,
Debusschere Vincent,
Caire Raphaël
Publication year - 2020
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.6533
Subject(s) - randomness , production (economics) , computer science , remuneration , function (biology) , network topology , reliability (semiconductor) , order (exchange) , operations research , point (geometry) , reliability engineering , engineering , computer network , mathematics , economics , power (physics) , statistics , physics , finance , quantum mechanics , evolutionary biology , biology , macroeconomics , geometry
This article studies the issues of storage in the planning of low voltage (LV ) networks. An algorithm of advanced automation function is developed to illustrate the maximum economic value of storage, from the distribution system operator (DSO) point of view, in the long‐term planning of LV networks, compared to a conventional reinforcement method. In order to model the randomness that characterises the new actors of the network (distributed production and storage), a stochastic planning study with uncertainties concerning the connection nodes of the batteries and the photovoltaic production in the network is conducted. The results show that compared to reinforcement, storage can present an economic benefit for the DSO, based on a limited but crucial set of elements: cost of remuneration for using storage, topology, and constraints on the network, and characteristics of the equipment presenting the constraints. For the third‐party storage facility owner, the presented benefits constitute the maximal envelop within which a cost benefit analysis should be restricted to be economically viable, as likely to be used to provide services to the DSO. These points are illustrated with two real networks in order to validate the proposed planning tool.