Coordination Mechanism for PV Battery Systems with Local Optimizing Energy Management

This publication presents a coordination mechanism for neighboring photovoltaic (PV) battery systems with local optimizing energy management (EM). The aim of this coordination is a high degree of self-sufficiency for the neighborhood while maintaining a high individual degree of self-sufficiency and...

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Main Authors: Manuel Kersic, Thilo Bocklisch, Michael Böttiger, Lisa Gerlach
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/13/3/611
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spelling doaj-beb1e553eb5c4f8a99463c89a713b2982020-11-25T01:12:58ZengMDPI AGEnergies1996-10732020-01-0113361110.3390/en13030611en13030611Coordination Mechanism for PV Battery Systems with Local Optimizing Energy ManagementManuel Kersic0Thilo Bocklisch1Michael Böttiger2Lisa Gerlach3Belectric GmbH, Industriestraße 65, D-01129 Dresden, GermanyChair of Energy Storage Systems, Institute of Power Engineering, Technische Universität Dresden, Helmholtzstraße 9, D-01062 Dresden, GermanyChair of Energy Storage Systems, Institute of Power Engineering, Technische Universität Dresden, Helmholtzstraße 9, D-01062 Dresden, GermanyChair of Energy Storage Systems, Institute of Power Engineering, Technische Universität Dresden, Helmholtzstraße 9, D-01062 Dresden, GermanyThis publication presents a coordination mechanism for neighboring photovoltaic (PV) battery systems with local optimizing energy management (EM). The aim of this coordination is a high degree of self-sufficiency for the neighborhood while maintaining a high individual degree of self-sufficiency and relieving the grid. A financial incentive to increase the energy exchanged within the neighborhood is introduced. The local EM of the individual PV battery system uses model predictive control based on deterministic dynamic programming in order to minimize the individual economic costs and extreme grid power values. By using a coordination algorithm involving a central information processing unit, the neighboring PV battery systems are given information about the sum of the planned consumption and feed-in power profiles of the neighborhood, as well as the neighborhood tariffs. Based on these data, the PV battery systems successively optimize the operation of their batteries until either convergence or a maximum count of iterations is achieved. The operating principle of the distributed EM concept with coordination is demonstrated through a simulation of a residential neighborhood comprising eight households with different load profiles and varying PV peak powers and battery capacities. Its performance is compared with three EM concepts: two distributed concepts without coordination and another one with central optimizing EM representing ideal coordination. The resulting power flow distributions are analyzed, and the benefits and weaknesses of the developed coordination mechanism are discussed based on a number of evaluation criteria.https://www.mdpi.com/1996-1073/13/3/611distributed controlcoordinationlocal trademicrogridenergy managementlithium-ion batteryphotovoltaicoptimizationmodel predictive controldynamic programming
collection DOAJ
language English
format Article
sources DOAJ
author Manuel Kersic
Thilo Bocklisch
Michael Böttiger
Lisa Gerlach
spellingShingle Manuel Kersic
Thilo Bocklisch
Michael Böttiger
Lisa Gerlach
Coordination Mechanism for PV Battery Systems with Local Optimizing Energy Management
Energies
distributed control
coordination
local trade
microgrid
energy management
lithium-ion battery
photovoltaic
optimization
model predictive control
dynamic programming
author_facet Manuel Kersic
Thilo Bocklisch
Michael Böttiger
Lisa Gerlach
author_sort Manuel Kersic
title Coordination Mechanism for PV Battery Systems with Local Optimizing Energy Management
title_short Coordination Mechanism for PV Battery Systems with Local Optimizing Energy Management
title_full Coordination Mechanism for PV Battery Systems with Local Optimizing Energy Management
title_fullStr Coordination Mechanism for PV Battery Systems with Local Optimizing Energy Management
title_full_unstemmed Coordination Mechanism for PV Battery Systems with Local Optimizing Energy Management
title_sort coordination mechanism for pv battery systems with local optimizing energy management
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2020-01-01
description This publication presents a coordination mechanism for neighboring photovoltaic (PV) battery systems with local optimizing energy management (EM). The aim of this coordination is a high degree of self-sufficiency for the neighborhood while maintaining a high individual degree of self-sufficiency and relieving the grid. A financial incentive to increase the energy exchanged within the neighborhood is introduced. The local EM of the individual PV battery system uses model predictive control based on deterministic dynamic programming in order to minimize the individual economic costs and extreme grid power values. By using a coordination algorithm involving a central information processing unit, the neighboring PV battery systems are given information about the sum of the planned consumption and feed-in power profiles of the neighborhood, as well as the neighborhood tariffs. Based on these data, the PV battery systems successively optimize the operation of their batteries until either convergence or a maximum count of iterations is achieved. The operating principle of the distributed EM concept with coordination is demonstrated through a simulation of a residential neighborhood comprising eight households with different load profiles and varying PV peak powers and battery capacities. Its performance is compared with three EM concepts: two distributed concepts without coordination and another one with central optimizing EM representing ideal coordination. The resulting power flow distributions are analyzed, and the benefits and weaknesses of the developed coordination mechanism are discussed based on a number of evaluation criteria.
topic distributed control
coordination
local trade
microgrid
energy management
lithium-ion battery
photovoltaic
optimization
model predictive control
dynamic programming
url https://www.mdpi.com/1996-1073/13/3/611
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