The forecasts of electricity and heating demands are key inputs for the efficient design and oper... more The forecasts of electricity and heating demands are key inputs for the efficient design and operation of energy systems serving urban districts, buildings, and households. Their accuracy may have a considerable effect on the selection of the optimization approach and on the solution quality. In this work, we describe a supervised learning approach based on shallow Artificial Neural Networks to develop an accurate model for predicting the daily hourly energy consumption of an energy district 24 h ahead. Predictive models are generated for each one of the two considered energy types, namely electricity and heating. Single-layer feedforward neural networks are trained with the efficient and robust decomposition algorithm DEC proposed by Grippo et al. on a data set of historical data, including, among others, carefully selected information related to the hourly energy consumption of the energy district and the hourly weather data of the region where the district is located. Three diffe...
2013 Asilomar Conference on Signals, Systems and Computers, 2013
ABSTRACT This paper proposes a new design methodology to partition streaming applications onto a ... more ABSTRACT This paper proposes a new design methodology to partition streaming applications onto a multi clock domain architecture. The objective is to save power by running different parts of the application at the lowest possible clock frequency that will not violate the throughput requirements. The solution involves partitioning the application into an appropriate number of clock domains, and then assigning each of those domains a clock frequency. Two different approaches are illustrated, both based on the post-processing and analysis of the causation trace of a dataflow program. Methodology and initial experimental results are demonstrated in an at-size scenario using an MPEG-4 Simple Profile decoder implemented in a FPGA platform.
ABSTRACT In this paper we propose a design methodology to partition dataflow applications on a mu... more ABSTRACT In this paper we propose a design methodology to partition dataflow applications on a multi clock domain architecture. This work shows how starting from a high level dataflow representation of a dynamic program it is possible to reduce the overall power consumption without impacting the performances. Two different approaches are illustrated, both based on the post-processing and analysis of the causation trace of a dataflow program. Methodology and experimental results are demonstrated in an at-size scenario using an MPEG-4 Simple Profile decoder.
Abstract In this work we compare two optimization approaches to tackle the short-term operational... more Abstract In this work we compare two optimization approaches to tackle the short-term operational planning of energy systems including power plants, boilers, heat storage, as well as cogeneration units. We first describe a mixed-integer nonlinear programming formulation for the problem and then a mixed-integer linear one, obtained using piecewise-linear approximations of the nonlinear performance functions. We report and discuss numerical results on a set of realistic test cases, comparing the quality of the solutions and the computing time of the two approaches.
Abstract Process engineering applications often lead to non-smooth constrained optimization probl... more Abstract Process engineering applications often lead to non-smooth constrained optimization problems in which the objective function and/or the constraints have non-differentiabilities and step discontinuities. Since the objective function is often the outcome of a complex simulation or the outcome of a lower level optimization problem, it may also be noisy and not defined in some point. In this work we propose and test a new hybrid direct search method for constrained non-smooth discontinuous problems which combines the positive features of Particle Swarm, Generating Set Search, and Complex, that we refer to as PGS-COM. Computational results show that PGS-COM outperforms the main available methods and exhibits considerable robustness to non-smoothness, unrelaxable constraints, evaluation failures and numerical noise.
Abstract. We consider the combinatorial problem MAXFLS which consists, given a system of linear r... more Abstract. We consider the combinatorial problem MAXFLS which consists, given a system of linear relations, of finding a maximum feasi-ble subsystem, that is a solution satisfying as many relations as possible. The approximability of this general problem is investigated for the ...
The forecasts of electricity and heating demands are key inputs for the efficient design and oper... more The forecasts of electricity and heating demands are key inputs for the efficient design and operation of energy systems serving urban districts, buildings, and households. Their accuracy may have a considerable effect on the selection of the optimization approach and on the solution quality. In this work, we describe a supervised learning approach based on shallow Artificial Neural Networks to develop an accurate model for predicting the daily hourly energy consumption of an energy district 24 h ahead. Predictive models are generated for each one of the two considered energy types, namely electricity and heating. Single-layer feedforward neural networks are trained with the efficient and robust decomposition algorithm DEC proposed by Grippo et al. on a data set of historical data, including, among others, carefully selected information related to the hourly energy consumption of the energy district and the hourly weather data of the region where the district is located. Three diffe...
2013 Asilomar Conference on Signals, Systems and Computers, 2013
ABSTRACT This paper proposes a new design methodology to partition streaming applications onto a ... more ABSTRACT This paper proposes a new design methodology to partition streaming applications onto a multi clock domain architecture. The objective is to save power by running different parts of the application at the lowest possible clock frequency that will not violate the throughput requirements. The solution involves partitioning the application into an appropriate number of clock domains, and then assigning each of those domains a clock frequency. Two different approaches are illustrated, both based on the post-processing and analysis of the causation trace of a dataflow program. Methodology and initial experimental results are demonstrated in an at-size scenario using an MPEG-4 Simple Profile decoder implemented in a FPGA platform.
ABSTRACT In this paper we propose a design methodology to partition dataflow applications on a mu... more ABSTRACT In this paper we propose a design methodology to partition dataflow applications on a multi clock domain architecture. This work shows how starting from a high level dataflow representation of a dynamic program it is possible to reduce the overall power consumption without impacting the performances. Two different approaches are illustrated, both based on the post-processing and analysis of the causation trace of a dataflow program. Methodology and experimental results are demonstrated in an at-size scenario using an MPEG-4 Simple Profile decoder.
Abstract In this work we compare two optimization approaches to tackle the short-term operational... more Abstract In this work we compare two optimization approaches to tackle the short-term operational planning of energy systems including power plants, boilers, heat storage, as well as cogeneration units. We first describe a mixed-integer nonlinear programming formulation for the problem and then a mixed-integer linear one, obtained using piecewise-linear approximations of the nonlinear performance functions. We report and discuss numerical results on a set of realistic test cases, comparing the quality of the solutions and the computing time of the two approaches.
Abstract Process engineering applications often lead to non-smooth constrained optimization probl... more Abstract Process engineering applications often lead to non-smooth constrained optimization problems in which the objective function and/or the constraints have non-differentiabilities and step discontinuities. Since the objective function is often the outcome of a complex simulation or the outcome of a lower level optimization problem, it may also be noisy and not defined in some point. In this work we propose and test a new hybrid direct search method for constrained non-smooth discontinuous problems which combines the positive features of Particle Swarm, Generating Set Search, and Complex, that we refer to as PGS-COM. Computational results show that PGS-COM outperforms the main available methods and exhibits considerable robustness to non-smoothness, unrelaxable constraints, evaluation failures and numerical noise.
Abstract. We consider the combinatorial problem MAXFLS which consists, given a system of linear r... more Abstract. We consider the combinatorial problem MAXFLS which consists, given a system of linear relations, of finding a maximum feasi-ble subsystem, that is a solution satisfying as many relations as possible. The approximability of this general problem is investigated for the ...
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Papers by Edoardo Amaldi