• Energy Research

Capítulos en libros This paper describes a strategic information platform developed for the German electric utility Eon, to provide historical bidding analysis and medium-term forecasting of the Iberian Electricity Market. This platform, PLAMER, has three main modules: Initialization module, consisting of different sub-modules to define the electrical system structure and to organize the input data of the rest of modules, PLAMER-bids, to read, aggregate and visualize market historical bids and also to prepare them for their future forecasted values, and PLAMER-clearing, for market clearing emulation using forecasted bids. PLAMER-clearing models the Iberian market based on a bid clearing mechanism with an inherent market splitting procedure. This market splitting is built with a bi-nodal simplification, one node representing the Spanish System and the other the Portuguese one. Both are simply connected by a unique equivalent interconnection line. The medium term clearing model uses a generation portfolio per generation company in terms of technologies, for supplying monthly demand for different load levels, and labour and non-labour periods. Some technical constraints, such as minimum outputs and pumping energy balance, are also taking into account. The mathematical problem of PLAMER-clearing is a quadratic programming model solved using GAMS language and CPLEX optimizer. Finally, a real Iberian case study is detailed and some market splitting outputs are analyzed. info:eu-repo/semantics/publishedVersion

Artículos en revistas The significant growth in gas-fired units worldwide has increased the grade of interdependency between power and natural gas networks. Since these units are usually required to ramp up during the peak and backup intermittent renewable generation and contingencies, the power system tends to demand more flexibility and reliability from the gas system. This paper contributes with a novel mixed-integer linear programing (MILP) formulation that couples power and gas networks taking into account the gas traveling velocity and compressibility. As a result, the model accounts for the gas adequacy needed to assure the power system reliability in the short term. The robustness of the MILP formulation allows guaranteeing global optimality within predefined tolerances. Case studies integrate the IEEE 24-bus system and Belgian high-calorific gas network for validating the formulation. info:eu-repo/semantics/publishedVersion

Artículos en revistas Electrical layout design is, for offshore wind farms (OWF), a complex problem that has a far-reaching impact on both plant cost and reliability. A full optimization of the layout, as opposed to just selecting the most favorable pre-established configuration, is required in order to capture all the potential efficiencies. However, classical optimization methods such as mixed-integer programming (MIP) might not be applicable to large OWFs. This paper describes a novel combination of ordinal optimization (OO) and MIP that is able to deal with large problems in reduced computation times with a statistical optimality guarantee. The algorithm is applied to a real case study taken from Barrow Offshore Wind Farm in the East Irish Sea. info:eu-repo/semantics/publishedVersion

Artículos en revistas When olives are harvested, local presses dispose of olive husk, the residue of the pressing process, transporting it to Olive Waste Management Centres (OWMC). Once there, the husk is emptied into pools to be classified, stored and then processed to obtain olive pomace oil and thermal and electric energy. Olive pomace oil extracted mechanically offers benefits over oil extracted chemically, both in terms of its culinary properties and in terms of its market price. This paper describes a decision model whose objective function seeks to maximise the quantity of olive pomace oil by improving the efficiency of mechanical extraction at OWMC. To improve this efficiency, a husk management decision model has been developed to cope with nonlinear husk pooling relationships over a multistage period. The convergence difficulties of mixed integer nonlinear optimisation in the decision model are dealt with by means of a novel multistage iterative linear formulation based on the first order Taylor approximation. The output accuracy and convergence of the proposed model is compared with that of a relaxed mixed integer nonlinear optimisation model. Finally, a real case study located in the south of Spain is described. In this study, by using the linear decision model the total amount of olive pomace oil was 10% greater than that obtained from the current procedure implemented at OWMC. info:eu-repo/semantics/publishedVersion

In this work, the optimal participation of heterogeneous, Renewable Energy Source (RES)-based Virtual Power Plant (VPP) in Day-Ahead Market (DAM) and Intra-Day Market (IDM) is studied. For this purpose, a detailed model of the RES-based VPP and of the market operation is needed. The VPP includes both dispatchable and non-dispatchable RESs and flexible demand assets. This paper presents an improved, linear solar thermal plant model to consider its non-linear efficiency curve. A novel demand model with two flexibility levels that are associated with the different market sessions is also proposed. The market operation allows for updates of energy offers and this is used by the VPP to submit DAM auctions and to participate subsequently in IDM to correct for deviations. Finally, the optimal participation of the VPP in energy markets is assessed under different weather conditions.

Artículos en revistas One of the main factors impacting the reliability of energy systems nowadays is the growing interdependence between electricity and gas networks due to the increase in the installation of gas-fired units. Securityconstrained unit commitment (SCUC) models are used to economically schedule generating units without compromising the system reliability. This paper proposes a novel SCUC formulation that includes dynamic gas constraints, such as the line pack, and transmission contingencies in power and gas networks for studying the integrated system reliability. A Bendersâ decomposition with linear programming techniques is developed to be able to study large systems. By including dynamic gas constraints into the SCUC, the proposed model accounts for the flexibility and reliability that power systems require from gas systems in the short term. Case studies of different size and complexity are employed to illustrate how the reliability of one system is affected by the reliability of the other. These experiments show how both systems operate in a secure way (by including contingencies) increases operating costs by approximately 9% and also show how these costs can vary by 24% depending on the line pack scheduling. info:eu-repo/semantics/publishedVersion

Artículos en revistas This paper shows a midterm transmission planning methodology for liberalized electricity markets. This methodology evaluates expansions and reinforcements using a transmission adequacy linear programming model. This type of modeling solves efficiently, taking into account power exchange deviations, n-1 network preventive adequacy level, and nonsupply demand. Statistical results are obtained sampling power exchange scenarios and computing transmission investment sensitivities. After each sample of generation and consumption bidding and generator and circuit failures, means, ranges, and confidence intervals of transmission investment sensitivities are updated. These sensitivities are computed using dual variables and reduced costs of the transmission adequacy model. This statistical sensitivity information and additional information are evaluated jointly using multicriteria decision theory. An extended Garver’s six-bus and the Spanish system cases are analyzed. info:eu-repo/semantics/publishedVersion

Artículos en revistas This paper details a decision model to implement Direct Load Control (DLC) on battery charging processes at Electric Vehicle Charging Points located at parking areas. The programming model combines optimally three types of energy management decisions: Grid to Vehicle charges, Vehicle to Grid discharges and novel Vehicle to Vehicle energy exchanges. The objective function maximizes the net energy supplied to batteries minimizing simultaneously the global energy cost. A 50 plug-in vehicle park case is analyzed for three possible mobility patterns: household, commercial and mixed. Outputs from the DLC model are compared with the ones using a dumb charging policy from the service quality and economic points of view. Finally, a sensitivity analysis has been done to evaluate the economic impact of the Depth of Discharge condition to preserve battery lifecycle of Electric Vehicles. info:eu-repo/semantics/publishedVersion