A novel approach for electric load curve holistic modelling and simulation

Barbier, Thibaut; Girard, Robin; Neirac, François-Pascal; Kong, Nicolas; Kariniotakis, Georges

doi:10.1049/cp.2014.1704

Cited by 8 publications

(7 citation statements)

References 3 publications

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“…Electric load profiles were simulated using a load simulator as described in [30] for each low voltage substation load profile. Residential and commercial load profiles are simulated with statistically accurate representations of surface area, electric heating and number of individuals that align with the INSEE household inventory database of France.…”

Section: Generation and Load Profilesmentioning

confidence: 99%

Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

2018

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. Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm. Applied Energy, Elsevier, 2018Elsevier, , 219, pp.385-393. <10.1016Elsevier, /j.apenergy.2017 .008>. Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm Etta Grover-Silva 1,2 , Robin Girard 1 , George Kariniotakis 1 AbstractThe high variability and uncertainty introduced into modern electrical distribution systems due to decentralized renewable energy generators requires new solutions for grid management and power quality assurance. One of these possible solutions includes grid integrated energy storage. The appropriate size and placement of decentralized storage is highly dependent on purpose of the battery system and expected operational strategy. However, battery operational strategies are difficult to simulate simultaneously during a sizing and placement planning calculation. The motivation of this paper is to propose an algorithm that is capable of integrating sizing, placement and operational strategies of batteries into an Optimal Power Flow (OPF) distribution grid planning tool. The choice of the OPF approach permits to account for grid constraints which is more adapted for grid-connected storage devices compared to other approaches in the state of the art that are based only on an email balance analysis. This paper presents an alternating current (AC) multi-temporal OPF algorithm that uses a convex relaxation of the power flow equations to guarantee exact and optimal solutions with high algorithmic performance. The algorithm is unique and innovative due to the fact that it combines the simultaneous optimization of placement and sizing of storage devices taking into account load curves, photovoltaic (PV) production profiles, and distribution grid power quality constraints. The choice to invest in battery capacity is highly sensitive to the price of battery systems. The investment in battery systems solely for reducing losses an operational costs was proven not to be cost effective, however when battery systems are allowed to buy and sell electricity based on variable market prices they become cost effective. The assumptions used for this study shows that current battery system prices are too high to be cost effective even when allowing battery system market participation.Keywords: Optimal power flow, storage, smart grids, renewable energy, distribution grid planning Nomenclature Parameters η st Charging and discharging efficiency of the battery system P pv,j,t Ideal PV production for node j at time step t S pv,j,t PV maximum apparent power flow at node j V j Voltage maximum at node n V j Voltage minimum at node n c inv stInvestment costs of the battery system for the nominal capacity in e/MWh-day Operations and maintenance costs of using the battery system for the power use in e/MWh-day c e,tPrice of electricity at time step t I max Total capital cost limit of project P ld,j,t Active power load at n...

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Section: Generation and Load Profilesmentioning

confidence: 99%

Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

2018

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“…The MOSAIC method uses a bottom-up load curve simulator developed by Mines Paris Tech [5]. The first step to perform a simulation is to be able to correctly model the current and the future study area.…”

Section: Simulation Of the Electric Load Curve Of An Areamentioning

confidence: 99%

“…It allows simulating in a bottom up way with a short computation time: few minutes to simulate the electricity demand of thousands of customers for one year at one hour time step. A complete description of the structure of the model is described in [5].…”

Section: Electric Load Curve Simulationmentioning

confidence: 99%

Long-term forecast of local electrical demand and evaluation of future impacts on the electricity distribution network

Kong¹,

Bocquel²,

Barbier

et al. 2017

CIRED - Open Access Proceedings Journal

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Enedis (France's main electricity DSO) and Mines Paris Tech are working on a new method called MOSAIC that aims at assessing the impact of long term local development projects on the electrical grid. The MOSAIC method uses a bottom-up simulation tool able to determine the current and future consumption and production load curve of an area. The consumption and production simulators are based on a multi-level data model that makes it possible to run a simulation even if some data are missing. The simulation parameters are calibrated by comparing the simulated load curves with observations on MV feeders (for the consumption simulator) and on 100 renewable energy producers (PV and WP). Once the simulators are calibrated for the current situation, the load curve of each development scenario of the area is estimated (the evolution scenarios are proposed by the local government, based on infeed growing, building projects …). Enedis and Mines Paris Tech are now working on linking the load curve simulators with more traditional electrical study tools. From the simulated load curve, we estimate the most likely maximal power of the grid infrastructures and use these values in the load flow tool called ERABLE to evaluate the impact of the scenarios on the grid. Initial tests were successful and this method will be further developed in 2017 on ten experimentation projects in France. Each project will help to develop new functionalities such as integrating Demand Response or electrical vehicle infrastructures.

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“…A map of the grid topology can be found below. Consumption load profiles were simulated using an aggregation load simulator as described in [20] for each low voltage substation and medium voltage consumer. This load simulator takes into account a mix of residential and commercial customers.…”

Section: Case Studymentioning

confidence: 99%

Multi-temporal optimal power flow for assessing the renewable generation hosting capacity of an active distribution system

Grover-Silva

Girard

Kariniotakis

2016

2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)

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Abstract-The detailed modeling of distribution grids is expected to be critical to understand the current functionality limits and necessary retrofits to satisfy integration of massive amounts of distributed generation, energy storage devices and the electric consumption demand of the future. Due to the highly dimensional non-convex characteristics of the power flow equations, convex relaxations have been used to ensure an efficient calculation time. However, these relaxations have been proven to be inexact during periods of high RES injection. In this paper additional linear constraints were introduced in the power flow formulation to guaranty an exact relaxation. This convex relaxation is then applied within a multi-temporal algorithm in order to evaluate the benefits of storage grid integration. The case study of a French medium voltage feeder is studied to evaluate the maximum capacity of the grid to host RES sources and the advantages of storage systems in reducing curtailment of RES.

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A novel approach for electric load curve holistic modelling and simulation

Cited by 8 publications

References 3 publications

Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

Optimal sizing and placement of distribution grid connected battery systems through an SOCP optimal power flow algorithm

Long-term forecast of local electrical demand and evaluation of future impacts on the electricity distribution network

Multi-temporal optimal power flow for assessing the renewable generation hosting capacity of an active distribution system

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