Model-predictive cascade mitigation in electric power systems with storage and renewables, Part I: Theory and implementation

Almassalkhi, Mads; Hiskens, Ian A.

doi:10.1109/pesgm.2015.7285680

Cited by 32 publications

(53 citation statements)

References 20 publications

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“…Receding Horizon Control (RHC) overcomes this shortcoming by recomputing the optimal decisions during each time-instant. To deal with this complexity, convex relaxation techniques have been used in the literature with the underlying assumption that the line resistance is lesser than the reactance [21]. Usually, this assumption does not hold for distribution and microgrids wherein the line resistance is usually high.…”

Section: Rhc Based Optimal Power Flow Formulationmentioning

confidence: 99%

A Cyber-Physical Systems Approach for Implementing the Receding Horizon Optimal Power Flow in Smart Grids

Maffei

Srinivasan

Meola

et al. 2018

IEEE Trans. Sustain. Comput.

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Abstract-Two Major challenges in securing reliable Optimal Power Flow (OPF) operations are: (i) fluctuations induced due to renewable generators and energy demand, and (ii) interaction and interoperability among the different entities. Addressing these issues requires handling both physical (e.g., power flows) and cyber aspects (computing and communication) of the energy grids, i.e, a cyber-physical systems (CPS) approach is necessitated. First, this investigation proposes a receding horizon control (RHC) based approach for solving OPF to deal with the uncertainties. It uses forecasts on renewable generation and demand and an optimization model solving a predictive control problem to secure energy balance while meeting the network constraints. Second, to handle the interoperability issues, a middleware using common information model (CIM) for exchanging information among applications and the associated profiles are presented. CIM profiles modelling various components and aspects of the RHC based OPF is proposed. In addition, a middleware architecture and services to collect information is discussed. The proposed CPS approach is illustrated in a distribution grid in Steinkjer, Norway having 85 nodes, 700 customers, 3 hydrogenerators, and various industrial loads. Our results demonstrate the benefits of CPS approach to implement OPF addressing also the interoperability issues.

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Section: Rhc Based Optimal Power Flow Formulationmentioning

confidence: 99%

A Cyber-Physical Systems Approach for Implementing the Receding Horizon Optimal Power Flow in Smart Grids

Maffei

Srinivasan

Meola

et al. 2018

IEEE Trans. Sustain. Comput.

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“…However, in some cases, the decisions might use simultaneous charging and discharging of battery units in order to absorb power from the system without affecting its state of charge (SoC) [36]. In order to avoid the simultaneous charging and discharging of battery system, as discussed in [36], the binary variables St Char and St DisChar are introduced and redefine the constant (20) as (21) to (23). In this way, it can guarantee a correct behavior while keeping the model as a MILCQP model: St…”

Section: First-stage Constrainsmentioning

confidence: 99%

Combined Two-Stage Stochastic Programming and Receding Horizon Control Strategy for Microgrid Energy Management Considering Uncertainty

Zang

Zeng

et al. 2016

Energies

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Microgrids (MGs) are presented as a cornerstone of smart grids. With the potential to integrate intermittent renewable energy sources (RES) in a flexible and environmental way, the MG concept has gained even more attention. Due to the randomness of RES, load, and electricity price in MG, the forecast errors of MGs will affect the performance of the power scheduling and the operating cost of an MG. In this paper, a combined stochastic programming and receding horizon control (SPRHC) strategy is proposed for microgrid energy management under uncertainty, which combines the advantages of two-stage stochastic programming (SP) and receding horizon control (RHC) strategy. With an SP strategy, a scheduling plan can be derived that minimizes the risk of uncertainty by involving the uncertainty of MG in the optimization model. With an RHC strategy, the uncertainty within the MG can be further compensated through a feedback mechanism with the lately updated forecast information. In our approach, a proper strategy is also proposed to maintain the SP model as a mixed integer linear constrained quadratic programming (MILCQP) problem, which is solvable without resorting to any heuristics algorithms. The results of numerical experiments explicitly demonstrate the superiority of the proposed strategy for both island and grid-connected operating modes of an MG.

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“…Consider an optimal control problem that seeks to adjust active and reactive power injections at generators and loads in order to minimize frequency deviations while also maintaining operational constraints on voltage magnitudes and phases (for example see [23], [24]). The dynamical system under consideration here can be modeled by the DAEs (3) and (4).…”

Section: B Convex Model Predictive Control (Mpc)mentioning

confidence: 99%

Convexity of structure preserving energy functions in power transmission: Novel results and applications

Dvijotham

Chertkov

2015

2015 American Control Conference (ACC)

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It is well-known in the power systems literature that the behavior of the transmission power system (under certain simplifying assumptions) can be used to study the post-fault dynamics of a power system and provide principled estimates on dynamic stability margins. In this paper, we study a special feature of the energy function that has previously received little attention: convexity. We prove that the energy function for structure preserving models of power systems is convex under certain reasonable conditions on phases and voltages. Beyond stability analysis, these convexity results have a number of applications, noticeably, building a provably convergent PF solver, which we discuss in detail in this paper. We also outline potential applications to reformulating Optimum Power Flow (OPF), Model Predictive Control (MPC) and identifying the most probable failure (instanton) as convex optimization problems.

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Model-predictive cascade mitigation in electric power systems with storage and renewables, Part I: Theory and implementation

Cited by 32 publications

References 20 publications

A Cyber-Physical Systems Approach for Implementing the Receding Horizon Optimal Power Flow in Smart Grids

A Cyber-Physical Systems Approach for Implementing the Receding Horizon Optimal Power Flow in Smart Grids

Combined Two-Stage Stochastic Programming and Receding Horizon Control Strategy for Microgrid Energy Management Considering Uncertainty

Convexity of structure preserving energy functions in power transmission: Novel results and applications

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