1,721,097 research outputs found
Linear fractional representations and L2-stability analysis of continuous piecewise affine systems
No full textThis letter addresses L2-stability analysis of discrete-time continuous piecewise affine systems described in input-output form by linear combinations of basis piecewise affine functions. The proposed approach exploits an equivalent representation of these systems as the feedback interconnection of a linear system and a diagonal static block with repeated scalar nonlinearity. This representation enables the use of analysis results for systems with repeated nonlinearities based on integral quadratic constraints. This leads to a sufficient condition for L2-stability that can be checked via the solution of a single linear matrix inequality, whose dimension grows linearly with the number of basis piecewise affine functions defining the system. Numerical examples corroborate the proposed approach by providing a comparison with an alternative approach based on the computation of piecewise polynomial storage functions
Optimization and Redistribution Strategies for Italian Renewable Energy Communities
No full textIn this paper we consider the optimal operation of an energy community receiving incentives for energy virtually shared among the community members. A similar incentive scheme for renewable energy communities is adopted in Italy since 2020. The operational problem is formulated as the maxi-mization of the profit of the community over a given time horizon. The profit includes the incentive for the virtual self-consumption. The optimization exploits all available sources of flexibility, such as controllable loads and generators, and battery energy storage systems. Compared to previous work of the authors, the mixed-integer formulation proposed in this paper requires a smaller number of continuous variables. Still, the number of binary variables may be prohibitive when the size of the community grows. For this reason, an equivalent formulation in the form of convex maximization is derived, involving only continuous variables. We show examples where the latter problem can be solved in reasonable time, while the solution process of the mixed integer problem gets stuck. Moreover, a simple strategy to fairly redistribute the community benefits among its members is discussed
Sufficient conditions for robust stability and performance
No full textIn this paper robust stability and performance conditions for the
classical unity-feedback control system and for a more general
feedback configuration are proposed. Uncertainty is represented in
the linear fractional form, where perturbations are assumed
to be norm-bounded, stable and unstructured. Suitable
Hinf control problems are derived for satisfying
both the proposed sufficient conditions. In addition, it is shown
that the first condition puts in a unified framework some
conditions existing in the literature and referring to specific
kinds of perturbations, such as the additive and the
multiplicative ones. Lastly, a property of the family of perturbed
systems whose robust stabilization is guaranteed by the first
condition is derived
Convex relaxations for L2-gain analysis of piecewise affine/polynomial systems
No full textThis paper proposes some sufficient conditions based on the computation of polynomial and piecewise polynomial storage functions for L2-gain analysis of discrete-time piecewise affine or piecewise polynomial systems. The computation of such storage functions is performed by means of convex optimisation techniques via the sum-of-squares decomposition of multivariate polynomials
A survey on switched and piecewise affine system identification
No full textRecent years have witnessed a growing interest on system identification techniques for switched and piecewise affine models. These model classes have become popular not only due to the universal approximation properties of piecewise affine functions, but also because the proposed identification procedures have proven to be effective in problems involving complex nonlinear systems with large data sets. This paper presents a review of recent advances in this research field, including theoretical results, algorithms and applications
Models and Techniques for Electric Load Forecasting in the Presence of Demand Response
No full textDemand-side management has been recently recognized as a strategic concept in smart electricity grids. In this context, active demand (AD) represents a demand response scenario in which households and small commercial consumers participate in grid management through appropriate modifications of their consumption patterns during certain time periods in return of a monetary reward. The participation is mediated by a new player, called aggregator, who designs the consumption pattern modifications to make up standardized products to be sold on the energy market. The presence of this new input to consumers generated by aggregators modifies the load behavior, asking for load forecasting algorithms that explicitly consider the AD effect. In this paper, we propose an approach to load forecasting in the presence of AD, based on gray-box models where the seasonal component of the load is extracted by a suitable preprocessing and AD is considered as an exogenous input to a linear transfer function model. The approach is thought for a distribution system operator that performs technical validation of AD products, and therefore possesses full information about the AD schedule in the network. A comparison of the performance of the proposed approach with techniques not using the information on AD and with approaches based on nonlinear black-box models is performed on a real load time series recorded in an area of the Italian low voltage network
A comparison between classes of perturbations allowed by some robust stability conditions
No full textSome classical robust stability conditions for continuous time
linear time-invariant systems are analyzed by comparing
the families of perturbed systems whose stabilization
through a given compensator is guaranteed by each of them.
Some properties of such families are formally derived, and
some very simple examples are presented in order to clarify
such properties and comparisons
Optimization of energy communities in the Italian incentive system
No full textIn this paper we address the optimal operation of an energy community, which receives an incentive for the self-consumption realized at the community level in each time period. This incentive scheme mimics the one adopted for renewable energy communities in Italy since 2020. The operational problem is formulated as the maximization of the social welfare of the community over a given time horizon. The social welfare includes the incentive. Each entity of the community can encompass loads, generators, and battery energy storage systems. The optimization problem computes the battery charging/discharging policies, and the set points of flexible loads and controllable generators. The resulting problem formulation is non-convex, due to the presence of complementarity constraints. This issue is tackled by deriving an equivalent mixed integer linear programming formulation. A toy example and an application with real consumption, generation, and price data, are reported to illustrate the proposed approach
Sizing distributed energy resources in a renewable energy community with a grid-aware internal market structure
Full text linkThis paper proposes a cooperative approach aimed at distributed energy resources sizing in a renewable energy community, with considerations of the community's optimal operation, impact on the electrical grid and an allocation of the benefits to its members. To this purpose, multiple investment modes are evaluated via a two-step procedure. In the first step, the size of renewable energy sources is determined by solving an optimization problem that maximizes community welfare, considering network and investments. In the second step, an optimization problem maximizing additional community member profit with price regularization is solved. This step shares benefits among community members. The potential of the proposed procedure is illustrated using a benchmark Dickert-LV network. This is a fully cooperative framework where the community operator is ensuring adequate grid operation, operational planning and sizing of new investments
Enhanced neural network-based polytopic model for large-signal black-box modeling of power electronic converters
Full text linkpeer reviewedWe propose a large-signal black-box model of power electronic converters inspired by polytopic models. Small-signal models are identified around different operating points to mimic the converter's local dynamics. The linear models' responses are then weighted using a trained neural network to create a large-signal model. The traditional trial and error weighting function tuning of polytopic models can result in a suboptimal combination of linear models. In this work, we use neural networks to approach an optimal combination. The analysis of the trained neural network can enhance the model's accuracy by suggesting new small-signal models. It also permits removing linear models that do not significantly improve the global model's accuracy while reducing complexity. The methodology is applied to a voltage-regulated DC-DC boost converter and provides accurate models of converter dynamics
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