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arxiv: 1906.08525 · v1 · pith:YEHC5VUPnew · submitted 2019-06-20 · 🧮 math.PR · math.AP· math.OC

Mean-Field Backward-Forward SDE with Jumps and Storage problem in Smart Grids

Pith reviewed 2026-05-25 19:17 UTC · model grok-4.3

classification 🧮 math.PR math.APmath.OC
keywords mean-field SDEsforward-backward SDEsstochastic jumpssmart gridsenergy storageexistence and uniquenessstochastic differential equationsmean-field games
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The pith

Existence and uniqueness are proved for coupled mean-field forward-backward SDEs with jumps, applied to electricity storage under unpredictable production.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper establishes existence and uniqueness for solutions to a system of coupled mean-field forward-backward stochastic differential equations that include jumps. It then applies this result to a storage optimization problem in smart grids, extending earlier models to cases where electricity production cannot be predicted in advance because of factors such as changing meteorological forecasts. The central object is the mean-field interaction among many agents whose states and controls are linked through the empirical distribution, with jumps capturing abrupt shifts. A reader would care because the framework supplies a rigorous way to solve dynamic optimization problems that involve both forward evolution and backward optimization under uncertainty and interaction.

Core claim

We prove the existence and uniqueness of the solution of a coupled Mean-Field Forward-Backward SDE system with Jumps. Then, we give an application in the field of storage problem in smart grids, studied in [4] in the case where the production of electricity is not predictable due, for example, to the changes in meteorological forecasts.

What carries the argument

Coupled mean-field forward-backward SDE system with jumps, whose unique solution is obtained via a fixed-point argument under suitable coefficient conditions.

If this is right

  • The storage problem in smart grids admits an optimal strategy even when production is driven by unpredictable jumps.
  • The mean-field limit of many interacting storage units can be replaced by the unique solution of the FBSDE system.
  • Backward components of the system yield the adjoint processes needed for optimality conditions under forecast uncertainty.
  • The result extends the deterministic-production case of reference [4] by incorporating Poisson-type jumps.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar FBSDE techniques could be used to model mean-field interactions in other resource-allocation problems with sudden shocks, such as inventory management under supply disruptions.
  • Numerical schemes that approximate the fixed-point map could be tested on small-scale smart-grid simulations to check convergence rates.
  • The framework suggests that mean-field games with jumps may be solvable without solving the full N-player system when N is large.

Load-bearing premise

The drift, diffusion, and jump coefficients must satisfy Lipschitz continuity, linear growth, and integrability conditions that make the map from candidate solutions to the FBSDE a contraction.

What would settle it

An explicit set of coefficients and jump measures that meet the Lipschitz and growth conditions yet produce either no solution or at least two distinct solutions to the coupled system.

read the original abstract

In this paper, we prove the existence and uniqueness of the solution of a coupled Mean-Field Forward-Backward SDE system with Jumps. Then, we give an application in the field of storage problem in smart grids, studied in [4] in the case where the production of electricity is not predictable due, for example, to the changes in meteorological forecasts.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The paper proves existence and uniqueness of solutions to a coupled mean-field forward-backward SDE system with jumps via a fixed-point argument, then applies the result to a storage optimization problem in smart grids where electricity production is unpredictable (e.g., due to meteorological changes), extending the deterministic-production case studied in reference [4].

Significance. If the existence-uniqueness theorem holds under a complete, verifiable set of assumptions, the work would extend the theory of mean-field FBSDEs to include jumps and supply a stochastic-control framework for renewable-energy storage, with potential practical value for grid management under uncertainty.

major comments (2)
  1. [Abstract] Abstract: the existence-uniqueness claim is stated without any explicit list of the Lipschitz, linear-growth, or moment conditions on the drift, diffusion, and jump integrands (with respect to both the state variable and the law variable). These conditions are load-bearing for any contraction-mapping argument in mean-field FBSDEs with jumps and must be stated before the smart-grid application can be checked.
  2. [Existence proof (presumed §3)] The fixed-point map for the coupled system must incorporate the mean-field dependence inside the jump term; without the precise contraction estimate (including the uniform bound on the measure-Lipschitz constant and the finite-moment assumption on the jump measure), it is impossible to confirm that the map is a contraction on the chosen Banach space for the storage model.
minor comments (1)
  1. [Title] The title uses 'Backward-Forward' while the abstract uses 'Forward-Backward'; consistent ordering would remove a minor source of confusion.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the careful reading and constructive suggestions. We address the major comments point by point below.

read point-by-point responses
  1. Referee: [Abstract] Abstract: the existence-uniqueness claim is stated without any explicit list of the Lipschitz, linear-growth, or moment conditions on the drift, diffusion, and jump integrands (with respect to both the state variable and the law variable). These conditions are load-bearing for any contraction-mapping argument in mean-field FBSDEs with jumps and must be stated before the smart-grid application can be checked.

    Authors: We agree that the abstract would be improved by a concise reference to the standing assumptions. In the revised version we will update the abstract to mention the Lipschitz continuity, linear-growth, and moment conditions imposed on the coefficients with respect to both the state and the measure variables. revision: yes

  2. Referee: [Existence proof (presumed §3)] The fixed-point map for the coupled system must incorporate the mean-field dependence inside the jump term; without the precise contraction estimate (including the uniform bound on the measure-Lipschitz constant and the finite-moment assumption on the jump measure), it is impossible to confirm that the map is a contraction on the chosen Banach space for the storage model.

    Authors: The fixed-point map constructed in Section 3 already incorporates the mean-field dependence inside the jump coefficient. The contraction is obtained on the chosen Banach space by combining the uniform bound on the measure-Lipschitz constant with the finite-moment assumption on the jump measure. To make this transparent, we will add an explicit display of the contraction constant and the relevant bounds in the revised proof. revision: yes

Circularity Check

0 steps flagged

No circularity: direct existence-uniqueness proof under standard assumptions

full rationale

The paper's central claim is a mathematical existence-uniqueness theorem for a coupled mean-field FBSDE with jumps, proved via fixed-point/contraction mapping. This is a self-contained analytic argument that does not reduce any quantity to a fitted input, self-citation chain, or ansatz smuggled from prior work by the same authors. The smart-grid application is presented separately and references external work [4] only for context, without making the FBSDE theorem depend on it. No load-bearing step matches any of the enumerated circularity patterns.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only review supplies no explicit free parameters, axioms, or invented entities; the existence proof must rest on unstated Lipschitz/growth conditions typical for FBSDE theory.

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Reference graph

Works this paper leans on

18 extracted references · 18 canonical work pages · 1 internal anchor

  1. [1]

    Backward-forward stochastic differential equations

    Antonelli, F., et al. Backward-forward stochastic differential equations. The Annals of Applied Probability 3 , 3 (1993), 777–793

  2. [2]

    Mean-field backward stochastic differential equations: a limit approach

    Buckdahn, R., Djehiche, B., Li, J., Peng, S., et al. Mean-field backward stochastic differential equations: a limit approach. The Annals of Probability 37 , 4 (2009), 1524–1565

  3. [3]

    Mean-field backward stochastic differential equations and related partial differential equations

    Buckdahn, R., Li, J., and Peng, S. Mean-field backward stochastic differential equations and related partial differential equations. Stochastic Processes and their Applications 119, 10 (2009), 3133–3154

  4. [4]

    An Extended Mean Field Game for Storage in Smart Grids

    Clemence, A., Imen, B. T., and Anis, M. Grid with distributed generation and storage. arXiv preprint arXiv:1710.08991 (2017)

  5. [5]

    M., Tembine, H., and Debbah, M

    Couillet, R., Perlaza, S. M., Tembine, H., and Debbah, M. A mean field game analysis of electric vehicles in the smart grid. In 2012 Proceedings IEEE INFOCOM Workshops (2012), IEEE, pp. 79–84. 30

  6. [6]

    Distributed control of micro-storage devices with mean field games

    De Paola, A., Angeli, D., and Strbac, G. Distributed control of micro-storage devices with mean field games. IEEE Transactions on Smart Grid 7 , 2 (2015), 1119– 1127

  7. [7]

    Graber, P. J. Linear quadratic mean field type control and mean field games with common noise, with application to production of an exhaustible resource. Applied Mathematic Optimization 74 (2016)

  8. [8]

    Backward–forward sdes and stochastic differential games

    Hamadene, S. Backward–forward sdes and stochastic differential games. Stochastic processes and their applications 77 , 1 (1998), 1–15

  9. [9]

    Solution of forward-backward stochastic differential equations

    Hu, Y., and Peng, S. Solution of forward-backward stochastic differential equations. Probability Theory and Related Fields 103 , 2 (1995), 273–283

  10. [10]

    Foundations of kinetic theory

    Kac, M. Foundations of kinetic theory. In Proceedings of The third Berkeley sympo- sium on mathematical statistics and probability (1956), vol. 3, University of California Press Berkeley and Los Angeles, California, pp. 171–197

  11. [11]

    Mean field games

    Lasry, J.-M., and Lions, P.-L. Mean field games. Japanese journal of mathematics 2, 1 (2007), 229–260

  12. [12]

    Solving forward-backward stochastic differen- tial equations explicitlya four step scheme

    Ma, J., Protter, P., and Yong, J. Solving forward-backward stochastic differen- tial equations explicitlya four step scheme. Probability theory and related fields 98 , 3 (1994), 339–359

  13. [13]

    A class of markov processes associated with nonlinear parabolic equations

    McKean Jr, H. A class of markov processes associated with nonlinear parabolic equations. Proceedings of the National Academy of Sciences of the United States of America 56, 6 (1966), 1907

  14. [15]

    Fully coupled forward-backward stochastic differential equa- tions and applications to optimal control

    Peng, S., and Wu, Z. Fully coupled forward-backward stochastic differential equa- tions and applications to optimal control. SIAM Journal on Control and Optimization 37, 3 (1999), 825–843

  15. [16]

    Fully coupled fbsde with brownian motion and poisson process in stopping time duration

    Wu, Z. Fully coupled fbsde with brownian motion and poisson process in stopping time duration. Journal of the Australian Mathematical Society 74 , 2 (2003), 249–266

  16. [17]

    Finding adapted solutions of forward–backward stochastic differential equa- tions: method of continuation

    Yong, J. Finding adapted solutions of forward–backward stochastic differential equa- tions: method of continuation. Probability Theory and Related Fields 107 , 4 (1997), 537–572

  17. [18]

    Forward-backward stochastic differential equations with brownian motion and poisson process

    Zhen, W. Forward-backward stochastic differential equations with brownian motion and poisson process. Acta Mathematicae Applicatae Sinica 15 , 4 (1999), 433–443

  18. [19]

    Linear-quadratic nonzero-sum differential game of backward stochastic differential equations

    Zhiyong, Y., and Shaolin, J. Linear-quadratic nonzero-sum differential game of backward stochastic differential equations. In 2008 27th Chinese Control Conference (2008), IEEE, pp. 562–566. 31