Factorized solution of power system state estimation

In this thesis a general two-stage factorized solution for nonlinear WLS problems has been developed, with two main applications: a geographically distributed multilevel hierarchical state estimation algorithm, suitable for very large-scale power systems covering multiple control areas; and a factorized multi-stage version, which enhances the convergence speed and reduces the computational effort. In the multilevel hierarchical state estimation, the way the algorithm can be customized to the system decomposition is analyzed, particularizing the methodology for the distribution feeder, substation, and transmission or multi-area system levels. Tests are performed on benchmark and realistic large-scale networks, including the entire European transmission system. The main advantage of this method lies in the possibility of filtering raw measurements at the specific location where they are captured, and then sending only local estimates for further processing by higher level state estimators. This multilevel estimator will be of special interest in upcoming systems, where the increased introduction of ICTs at lower levels and widespread interconnections at the regional transmission level are leading to an explosion of information which could be hardly managed by a single energy management system. In the second case, different approaches are proposed, all of them sharing a first linear stage, clearly showing computational efficiency and enhanced convergence speed compared to the conventional estimator. After a two-stage algorithm, the dissertation develops a bilinear three-stage state estimation factorization which virtually eliminates the need to iterate yielding the same solution as that provided by the Gauss-Newton iterative method. This is also extended to the case in which equality constraints are to be enforcedPremio Extraordinario de Doctorado U

State Estimation in Two Time Scales for Smart Distribution Systems

The monitoring of distribution systems relies on a critical set of pseudomeasurements and a varying but low number of redundant measurements. In the light of the different refreshing rates of both types of information, this paper considers a state estimation model structured in two time scales. Possibilities and limitations of the proposed model are discussed, and illustrated on a real distribution system comprising a diversity of load patterns

Offset-Assisted Factored Solution of Nonlinear Systems

This paper presents an improvement to the recently-introduced factored method for the solution of nonlinear equations. The basic idea consists of transforming the original system by adding an offset to all unknowns. When searching for real solutions, a real offset prevents the intermediate values of unknowns from becoming complex. Reciprocally, when searching for complex solutions, a complex offset is advisable to allow the iterative process to quickly abandon the real domain. Several examples are used to illustrate the performance of the proposed algorithm, when compared to Newton’s methodMinisterio de Economía y Competitividadt ENE2013-48428-C

Cross-Border Energy Exchange and Renewable Premiums: The Case of the Iberian System

In 2002, the European Union set a target of 10% electricity interconnection capacity for 2020: a target that has been further extended to 15% by 2030. Cross-border interconnection of regional/national electricity systems will allow the EU to enhance its security of supply and to integrate more renewables into energy markets. Although the EU has a common renewable directive, every Member State has its own renewable support policy. For the case of Spain, consumers pay the renewable premium in their electricity bills; however, consumers would not be overburdened if premiums were counter-balanced with the energy-cost reduction due to the merit-order effect of renewables. When two markets are interconnected, the energy exchange through the interconnection yields certain expected rent transfers due to the market rules. However, this exchange is also accompanied by other unforeseen rent transfers related to the regional/national policies on renewables. To the authors’ knowledge, the identification and quantification of these indirect rent transfers has not been previously addressed. This paper analyses and quantifies how the premiums on regional/national renewables are distributed between neighbouring countries through cross-border exchanges. The analysis focuses on the Iberian/Spanish system and its neighbours, although the methodology could be extended to other systems. To this end, data on the market and premiums has been considered, as well as the exchanges between France, Spain, Portugal, and Morocco, for the years 2015–2017. The main finding of this work is that the Spanish system, due to the lack of a coordinated/harmonized renewable premium policy, has been “importing” about 40 M€/year of renewable premium from France and 17 M€/year from Portugal while “exporting” about 66 M€/year towards the Moroccan systemsMinisterio de Economía y Competitividad PCIN-2015-043Ministerio de Economía y Competitividad ENE2016-77650-RComisión Europea (FEDER — European Regional Fondo de Desarrollo) PCIN-2015-043Comisión Europea (FEDER — European Regional Fondo de Desarrollo) ENE2016-77650-RComisión Europea (FEDER — European Regional Fondo de Desarrollo) SI-1778/12/201

A novel ensemble method for electric vehicle power consumption forecasting: Application to the Spanish system

The use of electric vehicle across the world has become one of the most challenging issues for environmental policies. The galloping climate change and the expected running out of fossil fuels turns the use of such non-polluting cars into a priority for most developed countries. However, such a use has led to major concerns to power companies, since they must adapt their generation to a new scenario, in which electric vehicles will dramatically modify the curve of generation. In this paper, a novel approach based on ensemble learning is proposed. In particular, ARIMA, GARCH and PSF algorithms' performances are used to forecast the electric vehicle power consumption in Spain. It is worth noting that the studied time series of consumption is non-stationary and adds difficulties to the forecasting process. Thus, an ensemble is proposed by dynamically weighting all algorithms over time. The proposal presented has been implemented for a real case, in particular, at the Spanish Control Centre for the Electric Vehicle. The performance of the approach is assessed by means of WAPE, showing robust and promising results for this research field.Ministerio de Economía y Competitividad Proyectos ENE2016-77650-R, PCIN-2015-04 y TIN2017-88209-C2-R

Compensated Load Flow Solutions for Distribution System State Estimation

State estimation of distribution systems typically relies on measurement sets with very low redundancy levels. In this paper, this fact is exploited by first solving a conventional load flow, using exclusively a critical set of measurements, and then compensating the solution to account for the few redundant measurements available. This leads to a suboptimal but sufficiently accurate estimate. It is shown how the sparse triangular factorization of the load flow Jacobian matrix can be fully exploited throughout the compensation-based procedure, preventing in this way the ill-conditioning associated with the gain matrix arising in the conventional least-squares formulation. Simulation results are provided for measurement configurations customarily found in distribution systems, showing the potential advantages of the proposed methodology

A Taxonomy of Multi-Area State Estimation Methods

This paper presents a critical review of the state of the art in Multi-Area State Estimation (MASE) methods, which are currently gaining renewed interest due to their capability of properly tracking multi-TSO transactions and accommodating highly redundant information systems. Based on several classification criteria, a taxonomy of MASE methods is first proposed. Two main categories, namely two-step or hierarchical versus decentralized, are identified. Then, for each class of methods, the resulting model structure and area interactions are discussed and a brief presentation is made of a selected subset of references