• Energy Research

Artículos en revistas In this paper we apply stochastic dual dynamic programming decomposition to a nonconvex multistage stochastic hydrothermal model where the nonlinear water head effects on production and the nonlinear dependence between the reservoir head and the reservoir volume are modeled. The nonconvex constraints that represent the production function of a hydro plant are approximated by McCormick envelopes. These constraints are split into smaller regions and the McCormick envelopes are used for each region. We use binary variables for this disjunctive programming approach and solve the problem with a decomposition method. We resort to a variant of the L-shaped method for solving the MIP subproblem with binary variables at any stage inside the stochastic dual dynamic programming algorithm. A realistic large-scale case study is presented. info:eu-repo/semantics/publishedVersion

The Start-Up (SU) & Shut-Down (SD) ramps of thermal units must be considered in Unit Commitment (UC) formulations to accurately represent the unit s power production. However, these ramps are usually ignored because they will considerably increase the computational burden of the UC problem. This paper presents a Mixed-Integer Linear Programming (MILP) formulation of SU & SD power trajectories of thermal units where the computational burden is considerably decreased in comparison to formulations commonly found in the literature. This is because the proposed formulation is i) tighter, i.e. the relaxed solution is nearer to the optimal integer solution; and ii) more compact, i.e. it needs fewer constraints, variables and nonzero elements in the constraint matrix. The proposed formulation is illustrated employing the self-UC problem faced by a thermal unit. Results show that not considering SU & SD ramps changes the commitment decisions causing a negative economic impact. We provide computational results comparing the proposed formulation with others found in the literature. The computation time was dramatically reduced as a natural consequence of the considerably tighter and more compact formulation. info:eu-repo/semantics/draft

Capítulos en libros This paper presents a Mixed-Integer Linear Programming (MILP) reformulation of the thermal Unit Commitment (UC) problem. The proposed formulation is simultaneously tight and compact. The tighter characteristic reduces the search space and the more compact characteristic increases the searching speed with which solvers explore that reduced space. Therefore, as a natural consequence, the proposed formulation significantly reduces the computational burden in comparison with analogous MILP-based UC formulations. We provide computational results comparing the proposed formulation with two others which are recognized as computationally efficient in the literature. The experiments were carried out on 40 different power system mixes and sizes, running from 28 to 1870 generating units. info:eu-repo/semantics/publishedVersion

info:eu-repo/semantics/draft

Artículos en revistas Growing load factors in winter and summer peaks are a serious problem faced by the Spanish electric energy system. This has led to the extensive use of peak load plants and thus to higher costs for the whole system. Wind energy represents a strongly increasing percentage of overall electricity production, but wind normally does not follow the typical demand profile. As generation flexibility is limited due to technical restrictions, and in absence of large energy storages, the other side of the equilibrium generation-demand has to react. Demand Side Management measures intend to adapt the demand profile to the situation in the system. In this paper, the operation of an electric system with high wind penetration is modeled by means of a unit commitment problem. Demand shifting and peak shaving are considered in this operation problem. Demand shifting is modeled in two different ways. Firstly the system operator controls the shift of demand; secondly each consumer decides its reaction to prices depending on its elasticity. The model is applied to the isolated power system of Gran Canaria. The impact of an increased installed wind capacity on operation and the cost savings resulting from the introduction of responsive demand are assessed. Furthermore, results from the different implemented demand response options are compared. info:eu-repo/semantics/publishedVersion

In stochastic optimization problems, uncertainty is normally represented by means of a scenario tree. Finding an accurate representation of this uncertainty when dealing with a set of historical series is an important issue, because of its influence in the results of the above mentioned problems. This article uses a procedure to create the scenario tree divided into two phases: the first one produces a tree that represents accurately the original probability distribution, and in the second phase that tree is reduced to make it tractable. Several clustering methods are analysed and proposed in the paper to obtain the scenario tree. Specifically, these are applied to an academic case and to natural hydro inflows series, and comparisons amongst them are established according to these results.

Artículos en revistas Climate change, added to security of supply concerns, has been leading many countries to strongly support the development of electric vehicles (EVs) not only as a cleaner and more energy efficient source of transportation but also as a flexible electricity storage option. However, the massive deployment of EVs will impose important challenges to power systems operation. In this context, this paper investigates the impact of EVs with V2G capability to power system operation. Since this impact depends on the power system considered and on the number (and type) of EVs, different scenarios for renewable energy sources (RES) generation and EV penetration are studied. A detailed analysis of the impact of EVs the Spanish power system - demand, generation, use of flexible units (pumped storage) and power reserve, and energy curtailment - is performed. For this purpose, a mid-term operation model that computes generation dispatch and simulates hourly power system operation is used. The advantage of this model is that it includes EVs in the unit commitment and represents in detail mobility and connection patterns, which allows the estimation of more realistic results. info:eu-repo/semantics/publishedVersion