A useful tool for reducing energy consumption at peak times is through an incentive-based demand ... more A useful tool for reducing energy consumption at peak times is through an incentive-based demand response program. Each participant user is paid for diminishing his energy requirement according to a baseline. However, this demand response program presents truthfulness and gaming concerns since consumers can alter their reported information in order to increase their well-being. Therefore, a novel contract is proposed to induce asymptotic incentive-compatibility (truthfulness) and individual rationality (voluntary participation) through the probability of call. In this approach, each consumer announces his baseline and reduction capacity; given the cost of electricity, incentive price and a penalty caused by any deviation between self-reported and actual energy consumption. A payment scheme is implemented for all participant consumers where an aggregator decides what users are called to perform the energy reduction. A two-stage stochastic optimization problem is formulated in order to understand the rational behavior of consumers that participate under this contract. As result, asymptotic truth-telling behavior in incentive-based DR is managed by the aggregator through the probability of call for each agent. Numerical optimization results show that the aggregator can limit gaming opportunities irrespective of consumer's private preferences by controlling user's participation.
This article presents a methodology for LPV (Linear Parameter-Varying) control system design. A w... more This article presents a methodology for LPV (Linear Parameter-Varying) control system design. A weighted sum of robust LTI (Linear Time-invariant) controllers is employed, where the weights are adapted on the base of an estimation of the radius of the reel. Robust stability of the loop is guaranteed. Performance of the LPV control system is analyzed and compared with a LTI
The Heating Ventilation and Air Conditioning (HVAC) systems are essential loads in world energy c... more The Heating Ventilation and Air Conditioning (HVAC) systems are essential loads in world energy consumption. The proper management of these loads produces a reduction in energy demand. Colombia is an agricultural country, one of its favorite products is flowers. That product needs to be refrigerated for three months to maintain its quality or complete many flowers (a batch) to export and commercialize. In favor of this reason, it is crucial to have an exemplary refrigeration system or improve the current one. This article presents the comparison among some standard system identification algorithms. This development is vital to the flower greenhouses in the Boyacá region to improving efficiency in the post-harvest stage. Matlab software makes the data processing and executes some system identification algorithms in order to determine the most suitable tool for flower greenhouse cooling systems. This process aims to get a fitting percentage above 80%. As a result, the N4SID algorithm presents the best performance with a fitting of 81.23%.
The optimal behavior of the demand side in an electricity market is studied when a consumer parti... more The optimal behavior of the demand side in an electricity market is studied when a consumer participates in a Peak Time Rebate Program (PTR). The main motivation is the growth of demand bidding programs around the world in order to reduce peak power consumption events. The situation is posed as a stochastic programming problem where the user chooses the optimal consumption profile to maximize his economic benefits. The consumer preferences are modeled as a risk-averse function under additive uncertainty. The case considered uses the previous consumption as the household-specific baseline for PTR program. As result, a rational user alters the baseline in order to increase his well-being. When the incentive is greater than the energy retail price, the best behavior for the user is to consume the maximum possible energy during the baseline setting period in order to get the highest profits during the PTR time. Thus, PTR program is not a favorable mechanism for a System Operator (SO) from an economic view whether the SO does not control properly the user participation.
Electricity access is strongly linked to human growth. Despite this, a portion of the world’s pop... more Electricity access is strongly linked to human growth. Despite this, a portion of the world’s population remains without access to energy. In Colombia, rural communities have energy challenges due to the National Interconnected System’s (NIS) lack of quality and stability. It is common to find that energy services in such locations are twice as costly as in cities and are only accessible for a few hours every day due to grid overload. Implementing market mechanisms that enable handling imbalances through the flexible load management of main loads within the grid is vital for improving the rural power grid’s quality. In this research, the energy from the rural grid is primarily employed to power a heating, ventilation, and air-conditioning (HVAC) system that chills flowers for future commerce. This load has significant consumption within the rural grid, so handling HVAC consumption in a suitable form can support the grid to avoid imbalances and improve the end-user access to energy. ...
2021 IEEE 5th Colombian Conference on Automatic Control (CCAC)
The Heating Ventilation and Air Conditioning (HVAC) systems are essential loads in world energy c... more The Heating Ventilation and Air Conditioning (HVAC) systems are essential loads in world energy consumption. The proper management of these loads produces a reduction in energy demand. Colombia is an agricultural country, one of its favorite products is flowers. That product needs to be refrigerated for three months to maintain its quality or complete many flowers (a batch) to export and commercialize. In favor of this reason, it is crucial to have an exemplary refrigeration system or improve the current one. This article presents the comparison among some standard system identification algorithms. This development is vital to the flower greenhouses in the Boyacá region to improving efficiency in the post-harvest stage. Matlab software makes the data processing and executes some system identification algorithms in order to determine the most suitable tool for flower greenhouse cooling systems. This process aims to get a fitting percentage above 80%. As a result, the N4SID algorithm presents the best performance with a fitting of 81.23%.
2017 IEEE 3rd Colombian Conference on Automatic Control (CCAC), 2017
This paper presents the design of non-linear torque control strategy for an engine, developed as ... more This paper presents the design of non-linear torque control strategy for an engine, developed as the weighted sum of linear model predictive control (MPC) laws. The controller is optimized for tracking a reference torque signal and for reducing CO2 emissions. The engine model is taken from Toyota student competition of European Control Conference (ECC) 2015. Subspace identification techniques were employed to identify linear local models of the engine. Two control strategies are proposed: a) linear MPC and b) MPC weighted sum approach. Both solutions are compared to determine the best one. Lastly, MPC weighted sum control shows better results than linear MPC in tracking problems and the performance index proposed by the competition.
This paper presents a methodology for determining the optimal portfolio allocation for a demand r... more This paper presents a methodology for determining the optimal portfolio allocation for a demand response aggregator. The formulation is based on Day-Ahead electricity prices, in which the aggregator coordinates a set of residential consumers that are recruited through contracts. Four types of contracts are analyzed, considering both direct and indirect demand response programs. The objective is to compare different scenarios for contract portfolios in order to establish the benefits of each market agent. An optimization problem is formulated to capture the interactions between the aggregator and end consumers. The model is formulated as a mathematical program with equilibrium constraints: At the upper level, the aggregator maximizes its benefits, whereas the lower level represents the consumers’ contracts. By applying the developed methodology, the characterization of the consumers’ behavior is established in order to forecast their responses to the generation of punctual incentives...
2018 IEEE International Conference on Industrial Technology (ICIT), 2018
A useful tool for reducing energy consumption at peak times is through an incentive-based demand ... more A useful tool for reducing energy consumption at peak times is through an incentive-based demand response program. Each participant user is paid for diminishing his energy requirement according to a baseline. However, this demand response program presents truthfulness and gaming concerns since consumers can alter their reported information in order to increase their well-being. Therefore, a novel contract is proposed to induce asymptotic incentive-compatibility (truthfulness) and individual rationality (voluntary participation) through the probability of call. In this approach, each consumer announces his baseline and reduction capacity; given the cost of electricity, incentive price and a penalty caused by any deviation between self-reported and actual energy consumption. A payment scheme is implemented for all participant consumers where an aggregator decides what users are called to perform the energy reduction. A two-stage stochastic optimization problem is formulated in order to understand the rational behavior of consumers that participate under this contract. As result, asymptotic truth-telling behavior in incentive-based DR is managed by the aggregator through the probability of call for each agent. Numerical optimization results show that the aggregator can limit gaming opportunities irrespective of consumer's private preferences by controlling user's participation.
This article proposes an energy-efficiency strategy based on the optimization of driving patterns... more This article proposes an energy-efficiency strategy based on the optimization of driving patterns for an electric vehicle (EV). The EV studied in this paper is a commercial vehicle only driven by a traction motor. The motor drives the front wheels indirectly through the differential drive. The electrical inverter model and the power-train efficiency are established by lookup tables determined by power tests in a dynamometric bank. The optimization problem is focused on maximizing energy-efficiency between the wheel power and battery pack, not only to maintain but also to improve its value by modifying the state of charge (SOC). The solution is found by means of a Particle Swarm Optimization (PSO) algorithm. The optimizer simulation results validate the increasing efficiency with the speed setpoint variations, and also show that the battery SOC is improved. The best results are obtained when the speed variation is between 5% and 6%.
A useful tool for reducing energy consumption at peak times is through an incentive-based demand ... more A useful tool for reducing energy consumption at peak times is through an incentive-based demand response program. Each participant user is paid for diminishing his energy requirement according to a baseline. However, this demand response program presents truthfulness and gaming concerns since consumers can alter their reported information in order to increase their well-being. Therefore, a novel contract is proposed to induce asymptotic incentive-compatibility (truthfulness) and individual rationality (voluntary participation) through the probability of call. In this approach, each consumer announces his baseline and reduction capacity; given the cost of electricity, incentive price and a penalty caused by any deviation between self-reported and actual energy consumption. A payment scheme is implemented for all participant consumers where an aggregator decides what users are called to perform the energy reduction. A two-stage stochastic optimization problem is formulated in order to understand the rational behavior of consumers that participate under this contract. As result, asymptotic truth-telling behavior in incentive-based DR is managed by the aggregator through the probability of call for each agent. Numerical optimization results show that the aggregator can limit gaming opportunities irrespective of consumer's private preferences by controlling user's participation.
This article presents a methodology for LPV (Linear Parameter-Varying) control system design. A w... more This article presents a methodology for LPV (Linear Parameter-Varying) control system design. A weighted sum of robust LTI (Linear Time-invariant) controllers is employed, where the weights are adapted on the base of an estimation of the radius of the reel. Robust stability of the loop is guaranteed. Performance of the LPV control system is analyzed and compared with a LTI
The Heating Ventilation and Air Conditioning (HVAC) systems are essential loads in world energy c... more The Heating Ventilation and Air Conditioning (HVAC) systems are essential loads in world energy consumption. The proper management of these loads produces a reduction in energy demand. Colombia is an agricultural country, one of its favorite products is flowers. That product needs to be refrigerated for three months to maintain its quality or complete many flowers (a batch) to export and commercialize. In favor of this reason, it is crucial to have an exemplary refrigeration system or improve the current one. This article presents the comparison among some standard system identification algorithms. This development is vital to the flower greenhouses in the Boyacá region to improving efficiency in the post-harvest stage. Matlab software makes the data processing and executes some system identification algorithms in order to determine the most suitable tool for flower greenhouse cooling systems. This process aims to get a fitting percentage above 80%. As a result, the N4SID algorithm presents the best performance with a fitting of 81.23%.
The optimal behavior of the demand side in an electricity market is studied when a consumer parti... more The optimal behavior of the demand side in an electricity market is studied when a consumer participates in a Peak Time Rebate Program (PTR). The main motivation is the growth of demand bidding programs around the world in order to reduce peak power consumption events. The situation is posed as a stochastic programming problem where the user chooses the optimal consumption profile to maximize his economic benefits. The consumer preferences are modeled as a risk-averse function under additive uncertainty. The case considered uses the previous consumption as the household-specific baseline for PTR program. As result, a rational user alters the baseline in order to increase his well-being. When the incentive is greater than the energy retail price, the best behavior for the user is to consume the maximum possible energy during the baseline setting period in order to get the highest profits during the PTR time. Thus, PTR program is not a favorable mechanism for a System Operator (SO) from an economic view whether the SO does not control properly the user participation.
Electricity access is strongly linked to human growth. Despite this, a portion of the world’s pop... more Electricity access is strongly linked to human growth. Despite this, a portion of the world’s population remains without access to energy. In Colombia, rural communities have energy challenges due to the National Interconnected System’s (NIS) lack of quality and stability. It is common to find that energy services in such locations are twice as costly as in cities and are only accessible for a few hours every day due to grid overload. Implementing market mechanisms that enable handling imbalances through the flexible load management of main loads within the grid is vital for improving the rural power grid’s quality. In this research, the energy from the rural grid is primarily employed to power a heating, ventilation, and air-conditioning (HVAC) system that chills flowers for future commerce. This load has significant consumption within the rural grid, so handling HVAC consumption in a suitable form can support the grid to avoid imbalances and improve the end-user access to energy. ...
2021 IEEE 5th Colombian Conference on Automatic Control (CCAC)
The Heating Ventilation and Air Conditioning (HVAC) systems are essential loads in world energy c... more The Heating Ventilation and Air Conditioning (HVAC) systems are essential loads in world energy consumption. The proper management of these loads produces a reduction in energy demand. Colombia is an agricultural country, one of its favorite products is flowers. That product needs to be refrigerated for three months to maintain its quality or complete many flowers (a batch) to export and commercialize. In favor of this reason, it is crucial to have an exemplary refrigeration system or improve the current one. This article presents the comparison among some standard system identification algorithms. This development is vital to the flower greenhouses in the Boyacá region to improving efficiency in the post-harvest stage. Matlab software makes the data processing and executes some system identification algorithms in order to determine the most suitable tool for flower greenhouse cooling systems. This process aims to get a fitting percentage above 80%. As a result, the N4SID algorithm presents the best performance with a fitting of 81.23%.
2017 IEEE 3rd Colombian Conference on Automatic Control (CCAC), 2017
This paper presents the design of non-linear torque control strategy for an engine, developed as ... more This paper presents the design of non-linear torque control strategy for an engine, developed as the weighted sum of linear model predictive control (MPC) laws. The controller is optimized for tracking a reference torque signal and for reducing CO2 emissions. The engine model is taken from Toyota student competition of European Control Conference (ECC) 2015. Subspace identification techniques were employed to identify linear local models of the engine. Two control strategies are proposed: a) linear MPC and b) MPC weighted sum approach. Both solutions are compared to determine the best one. Lastly, MPC weighted sum control shows better results than linear MPC in tracking problems and the performance index proposed by the competition.
This paper presents a methodology for determining the optimal portfolio allocation for a demand r... more This paper presents a methodology for determining the optimal portfolio allocation for a demand response aggregator. The formulation is based on Day-Ahead electricity prices, in which the aggregator coordinates a set of residential consumers that are recruited through contracts. Four types of contracts are analyzed, considering both direct and indirect demand response programs. The objective is to compare different scenarios for contract portfolios in order to establish the benefits of each market agent. An optimization problem is formulated to capture the interactions between the aggregator and end consumers. The model is formulated as a mathematical program with equilibrium constraints: At the upper level, the aggregator maximizes its benefits, whereas the lower level represents the consumers’ contracts. By applying the developed methodology, the characterization of the consumers’ behavior is established in order to forecast their responses to the generation of punctual incentives...
2018 IEEE International Conference on Industrial Technology (ICIT), 2018
A useful tool for reducing energy consumption at peak times is through an incentive-based demand ... more A useful tool for reducing energy consumption at peak times is through an incentive-based demand response program. Each participant user is paid for diminishing his energy requirement according to a baseline. However, this demand response program presents truthfulness and gaming concerns since consumers can alter their reported information in order to increase their well-being. Therefore, a novel contract is proposed to induce asymptotic incentive-compatibility (truthfulness) and individual rationality (voluntary participation) through the probability of call. In this approach, each consumer announces his baseline and reduction capacity; given the cost of electricity, incentive price and a penalty caused by any deviation between self-reported and actual energy consumption. A payment scheme is implemented for all participant consumers where an aggregator decides what users are called to perform the energy reduction. A two-stage stochastic optimization problem is formulated in order to understand the rational behavior of consumers that participate under this contract. As result, asymptotic truth-telling behavior in incentive-based DR is managed by the aggregator through the probability of call for each agent. Numerical optimization results show that the aggregator can limit gaming opportunities irrespective of consumer's private preferences by controlling user's participation.
This article proposes an energy-efficiency strategy based on the optimization of driving patterns... more This article proposes an energy-efficiency strategy based on the optimization of driving patterns for an electric vehicle (EV). The EV studied in this paper is a commercial vehicle only driven by a traction motor. The motor drives the front wheels indirectly through the differential drive. The electrical inverter model and the power-train efficiency are established by lookup tables determined by power tests in a dynamometric bank. The optimization problem is focused on maximizing energy-efficiency between the wheel power and battery pack, not only to maintain but also to improve its value by modifying the state of charge (SOC). The solution is found by means of a Particle Swarm Optimization (PSO) algorithm. The optimizer simulation results validate the increasing efficiency with the speed setpoint variations, and also show that the battery SOC is improved. The best results are obtained when the speed variation is between 5% and 6%.
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Papers by Jose Vuelvas