Abstract
We consider a distribution grid used to charge electric vehicles (EVs) such that voltage drops stay bounded. We model this as a class of resource-sharing networks, known as bandwidth-sharing networks in the communication network literature. We focus on resource-sharing networks that are driven by a class of greedy control rules that can be implemented in a decentralized fashion. For a large number of such control rules, we can characterize the performance of the system by a fluid approximation. This leads to a set of dynamic equations that take into account the stochastic behavior of EVs. We show that the invariant point of these equations is unique and can be computed by solving a specific AC optimal-power-flow problem (ACOPF), which admits an exact convex relaxation. We illustrate our findings with a case study using the SCE 47-bus network and several special cases that allow for explicit computations.
| Original language | English |
|---|---|
| Article number | 8709819 |
| Pages (from-to) | 1050-1061 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Control of Network Systems |
| Volume | 6 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Sep 2019 |
Keywords
- AC power flow model
- distribution network
- electric vehicle charging
- fluid approximation
- linearized Distflow
- queueing theory
- stochastic processes
Cite this
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A stochastic resource-sharing network for electric vehicle charging. / Aveklouris, Angelos (Corresponding author); Vlasiou, Maria; Zwart, Bert.
In: IEEE Transactions on Control of Network Systems, Vol. 6, No. 3, 8709819, 09.2019, p. 1050-1061.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - A stochastic resource-sharing network for electric vehicle charging
AU - Aveklouris, Angelos
AU - Vlasiou, Maria
AU - Zwart, Bert
PY - 2019/9
Y1 - 2019/9
N2 - We consider a distribution grid used to charge electric vehicles (EVs) such that voltage drops stay bounded. We model this as a class of resource-sharing networks, known as bandwidth-sharing networks in the communication network literature. We focus on resource-sharing networks that are driven by a class of greedy control rules that can be implemented in a decentralized fashion. For a large number of such control rules, we can characterize the performance of the system by a fluid approximation. This leads to a set of dynamic equations that take into account the stochastic behavior of EVs. We show that the invariant point of these equations is unique and can be computed by solving a specific AC optimal-power-flow problem (ACOPF), which admits an exact convex relaxation. We illustrate our findings with a case study using the SCE 47-bus network and several special cases that allow for explicit computations.
AB - We consider a distribution grid used to charge electric vehicles (EVs) such that voltage drops stay bounded. We model this as a class of resource-sharing networks, known as bandwidth-sharing networks in the communication network literature. We focus on resource-sharing networks that are driven by a class of greedy control rules that can be implemented in a decentralized fashion. For a large number of such control rules, we can characterize the performance of the system by a fluid approximation. This leads to a set of dynamic equations that take into account the stochastic behavior of EVs. We show that the invariant point of these equations is unique and can be computed by solving a specific AC optimal-power-flow problem (ACOPF), which admits an exact convex relaxation. We illustrate our findings with a case study using the SCE 47-bus network and several special cases that allow for explicit computations.
KW - AC power flow model
KW - distribution network
KW - electric vehicle charging
KW - fluid approximation
KW - linearized Distflow
KW - queueing theory
KW - stochastic processes
UR - http://www.scopus.com/inward/record.url?scp=85073490981&partnerID=8YFLogxK
U2 - 10.1109/TCNS.2019.2915651
DO - 10.1109/TCNS.2019.2915651
M3 - Article
VL - 6
SP - 1050
EP - 1061
JO - IEEE Transactions on Control of Network Systems
JF - IEEE Transactions on Control of Network Systems
SN - 2325-5870
IS - 3
M1 - 8709819
ER -