André Luís Marques Marcato

Parallel computing applied to the stochastic dynamic programming for long term operation planning of hydrothermal power systems

In this paper, parallel processing techniques are employed to improve the performance of the stochastic dynamic programming applied to the long term operation planning of electrical power system. The hydroelectric plants are grouped into energy equivalent reservoirs and the expected cost functions are modeled by a piecewise linear approximation, by means of the Convex Hull algorithm. In order to validate the proposed methodology, data from the Brazilian electrical power system is utilized.

Stochastic Dynamic Programming Applied to Hydrothermal Power Systems Operation Planning Based on the Convex Hull Algorithm

This paper presents a new approach for the expected cost-to-go functions modeling used in the stochastic dynamic programming (SDP) algorithm. The SDP technique is applied to the long-term operation planning of electrical power systems. Using state space discretization, the Convex Hull algorithm is used for constructing a series of hyperplanes that composes a convex set. These planes represent a piecewise linear approximation for the expected cost-to-go functions. The mean operational costs for using the proposed methodology were compared with those from the deterministic dual dynamic problem in a case study, considering a single inflow scenario. This sensitivity analysis shows the convergence of both methods and is used to determine the minimum discretization level. Additionally, the applicability of the proposed methodology for two hydroplants in a cascade is demonstrated. With proper adaptations, this work can be extended to a complete hydrothermal system.

Optimal operation of hydrothermal systems with Hydrological Scenario Generation through Bootstrap and Periodic Autoregressive Models

In electrical power systems with strong hydro generation, the use of adequate techniques to generate synthetic hydrological scenarios is extremely important for the evaluation of the ways the system behaves in order to meet the forecast energy demand. This paper proposes a new model to generate natural inflow energy scenarios in the long-term operation planning of large-sized hydrothermal systems. This model is based on the Periodic Autoregressive Model, PAR (p), where the identification of the p orders is based on the significance of the Partial Autocorrelation Function (PACF) estimated via Bootstrap, an intensive computational technique. The scenarios generated through this new technique were applied to the operation planning of the Brazilian Electrical System (BES), using the previously developed methodology of Stochastic Dynamic Programming based on Convex Hull algorithm (SDP-CHull). The results show that identification via Bootstrap is considerably more parsimonious, leading to the identification of lower orders models in most cases which retains the statistical characteristics of the original series. Additionally it presents a closer total mean operation cost when compared to the cost obtained via historic series.

Series compensation device allocation under contingency constraints

In this paper the influence of a contingency in the series compensation (SC) device allocation and size is evaluated. The SC placement and size are determined using an optimal power flow (OPF) program via the Benders cut technique to include the contingency influence. This problem is solved in two steps: (i) The SC size and placement are determined as an investment OPF subproblem. The SC cost and energy production cost are included in the objective function; (ii) The operation OPF subproblem is solved considering the specified line and generation outages. The Benders cut are generated according to the outage occurrence probability. In this case the objective function is the minimum load shedding and energy production cost. The OPF subproblems are solved using linear programming technique. The IEEE-14 bus and IEEE-118 bus test systems are used to show the effectiveness of the proposed methodology.

Thermal Unit Commitment using improved ant colony optimization algorithm via Lagrange multipliers

This article proposes the use of Lagrange multipliers associated with discrete variables of the Thermal Unit Commitment problem as a source of information for the ant colony algorithm. To achieve this, the discrete variables that are inherent to the problem are mitigated through a sigmoid function. By doing so, the non-linear optimization issue is solved through the use of the primal-dual interior-point method, generating Lagrange multipliers associated to the ON/OFF decision variables as subproducts which are used to draw up a list of priorities, where part of the colony will make use of this information in the search for solutions. The results obtained show that the information taken into consideration significantly improves the efficiency of the colony search process.

Transmission expansion optimization via constructive heuristic technique

This work presents a heuristic constructive algorithm which evaluates the optimal set of transmission expansion paths of an electrical system. To do this, the discrete variables of transmission system are mitigated with the use of a linear function, which is valid for the [0,1] interval. These discrete variables are considered in the optimal power flow (OPF) using interior point technique. Considering that the solution region is non convex, there could be many combinations of expansion transmission paths to match the demand. Therefore, the proposed algorithm is started taking into account different starting points. Presently, it is possible to find a reduced set of likely transmission expansion paths. This algorithm has a trade off between efficiency and fastness to solve the transmission expansion problem of electrical systems. This algorithm was tested with the use of the Garver system.

Influência da variação da produtividade das usinas hidroelétricas no cálculo da energia firme

In the present work, the problem associated to the firm energy evaluation is treated as a non linear optimization model, which allows the representation of the productivity variation of the hydro plants. The proposed model takes into account the individualized representation of the plants and the historical series of flows since the month of January of 1931. The proposed optimization problem will be solved using the Primal-Dual Interior Point Method. A case study will be presented including the Brazilian Interconnected National System. The results obtained show that the proposed methodology is promising, since it presents an energy market value more realistic when compared with existing methodologies.

Using stochastic dual dynamic programming and a periodic autoregressive model for wind-hydrothermal long-term planning

In this study, we use a stochastic representation of wind for medium/long-term planning problems that are associated with the operation of hydro-thermal systems. The stochastic dual dynamic programming (SDDP) technique is used in this study. Synthetic wind and hydrological scenarios are generated using a periodic autoregressive model (PAR (p)). This algorithm has wide applicability in countries with a predominantly hydroelectric energy matrix that is associated with high penetration of thermal and wind generation, as in the Brazilian power system. The nonlinearities of the hydraulic production function also was been taking into account. The developed technique can be applied due to the global expansion of power generation over the last two decades with the increasing integration of alternative sources.

Modelo para o despacho de usinas individualizadas no planejamento hidrotérmico de médio prazo baseado em PNL

This paper presents a method to the hydrothermal dispatch using optimization techniques based on non linear programming techniques. To do so, the expected cost-to-go functions from a long term operation plannning strategic decision model are used. This decision model is based on stochastic dual dynamic programming and energy equivalent reservoirs. The proposed method considers a set of historical water inflow scenarios to the hydroelectric reservoirs. Those scenarios are used to simulate the long term operation planning to a given horizon. The results obtained from this disaggregation model (MIUH) are compared with those from the model officially adopted in the Brazilian power system, SUISHI-O. The latter is based on operation heuristics aiming at operating the reservoir maintaining the water storag e in similar levels, that is, trying to operate them in parallel.

Assessment of the generator remote voltage control through static security regions

This paper describes the use of a static security tool, based on security regions, to evaluate strategies of voltage control in power systems. The remote voltage control technique involving generators and/or synchronous compensators is used as strategy to exploit the system voltage control resources. The proposed tool has been tested using both a 9-bus tutorial system and the 39-bus New England system. The results presented validate and clearly indicate the effectiveness of the proposed method.