Exact Convex Modeling of the Optimal Power Flow for the Operation and Planning of Active Distribution Networks with Energy Storage Systems

The distribution networks are experiencing important changes driven by the massive integration of renewable energy conversion systems. However, the lack of direct controllability of the Distributed Generations (DGs) supplying Active Distribution Networks (ADNs) represents a major obstacle to the increase of the penetration of renewable energy resources characterized by a non-negligible volatility. The successful development of ADNs depends on the combination of i) specific control tools and ii) availability of new technologies and controllable resources. Within this context, this thesis focuses on developing practical and scalable methodologies for the ADN planning and operation with particular reference to the integration of Energy Storage Systems (ESSs) owned, and directly controlled, by the Distribution Network Operators (DNOs). In this respect, an exact convex formulation of Optimal Power Flow (OPF), called AR-OPF, is first proposed for the case of radial power networks. The proposed formulation takes into account the correct model of the lines and the security constraints related to the nodal voltage magnitudes, as well as, the lines ampacity limits. Sufficient conditions are provided to guarantee that the solution of the AR-OPF is feasible and optimal (i.e., the relaxation used is exact). Moreover, by analyzing the exactness conditions, it is revealed that they are mild and hold for real distribution networks. The AR-OPF is further augmented by suitably incorporating radiality constraints in order to develop an optimization model for optimal reconfiguration of ADNs. Then, a two-stage optimization problem for day-ahead resource scheduling in ADNs, accounting for the uncertainties of nodal injections, is proposed. The Adaptive Robust Optimization (ARO) and stochastic optimization techniques are successfully adapted to solve this optimization problem. The solutions of ARO and stochastic optimization reveal that the ARO provides a feasible solution for any realization of the uncertain parameters even if its solution is optimal only for the worst case realization. On the other hand, the stochastic optimization provides a solution taking into account the probability of the considered scenarios. Finally, the problem of optimal resource planning in ADNs is investigated with particular reference to the ESSs. In this respect, the AR-OPF and the proposed ADN reconfiguration model, are employed to develop optimization models for the optimal siting and sizing of ESSs in ADNs. The objective function aims at finding the optimal trade-off between technical and economical goals. In particular, the proposed procedures accounts for (i) network voltage deviations, (ii) feeders/lines congestions, (iii) network losses, (iv) cost of supplying loads (from external grid or local producers) together with the cost of ESS investment/maintenance, (v) load curtailment and (vi) stochasticity of loads and renewables production. The use of decomposition methods for solving the targeted optimization problems with discrete variables and probable large size is investigated. More specifically, Benders decomposition and Alternative Direction Method of Multipliers (ADMM) techniques are successfully applied to the targeted problems. Using real and standard networks, it is shown that the ESSs could possibly prevent load and generation curtailment, reduce the voltage deviations and lines congestions, and do the peak shaving

A digital information model framework for uas-enabled bridge inspection

Unmanned aerial systems (UAS) provide two main functions with regards to bridge inspections: (1) high-quality digital imaging to detect element defects; (2) spatial point cloud data for the reconstruction of 3D asset models. With UAS being a relatively new inspection method, there is little in the way of existing framework for storing, processing and managing the resulting inspection data. This study has proposed a novel methodology for a digital information model covering data acquisition through to a 3D GIS visualisation environment, also capable of integrating within a bridge management system (BMS). Previous efforts focusing on visualisation functionality have focused on BIM and GIS as separate entities, which has a number of problems associated with it. This methodology has a core focus on the integration of BIM and GIS, providing an effective and efficient information model, which provides vital visual context to inspectors and users of the BMS. Three-dimensional GIS visualisation allows the user to navigate through a fully interactive environment, where element level inspection information can be obtained through point-and-click operations on the 3D structural model. Two visualisation environments were created: a web-based GIS application and a desktop solution. Both environments develop a fully interactive, user-friendly model which have fulfilled the aims of coordinating and streamlining the BMS process.publishedVersio

The First Metal Complexes of 4,6-diamino-1-hydro-5-hydroxy-pyrimidine-2-thione: Preparation, Physical and Spectroscopic Studies, and Preliminary Antimicrobial Properties

The new complexes [M2O5L2(H2O)2] · H2O (M = Mo, 1; M = W, 2), [RuL2(H2O)2] · H2O (3), [ML3] · xH2O (M = Rh, x = 2, 4; M = Ir, x = 1, 5), [RhL2(PPh3)2](ClO4) · 2H2O (6), [PdL2] · 2H2O (7), [PdL(phen)]Cl · H2O (8), [Re OL2(PPh3)]Cl (9) and [UO2L2] (10) are reported, where LH is 4,6-diamino-1-hydro-5-hydroxy-pyrimidine-2-thione. The complexes were characterized by elemental analyses, physical techniques (molar conductivity, room-temperature magnetic susceptibility), and spectroscopic (IR, Raman, UV/VIS/ligand field, NMR, mass) methods. The ligand L− is in its thione form and behaves as a bidentate chelate with the deprotonated (hydroxyl) oxygen and the nitrogen of one amino group as donor atoms. Oxobridged dinuclear (1, 2) and various mononuclear (3–10) structures are assigned for the complexes in the solid state. The metal ion coordination geometries are octahedral (1–6, 9, 10) or square planar (7, 8). The free ligand LH and complexes 1, 4, 7, and 8 were assayed in vitro for antimicrobial activity against two bacterial and two fungal cultures

Trends in Maths and Science Study (TIMSS): National Report for England

The Trends in International Mathematics and Science Study (TIMSS) is overseen by the International Association for the Evaluation of Educational Achievement (IEA). It provides participating countries internationally comparable data on the performance and attitudes of 9 to 10 (year 5) and 13 to 14 year-olds (year 9) in maths and science as well as comparisons of the curriculum and the teaching of these subjects in primary and secondary schools. This National Report for England focuses on comparisons of our pupils’ performance and their experiences of maths and science teaching compared to: high-performing and rapidly improving countries; other English-speaking countries; and similar countries in terms of context and geography. It also shows trends in England’s absolute and relative performance over a twenty-year period

Stochastic Day-ahead Optimal Scheduling of Active Distribution Networks with Dispersed Energy Storage and Renewable Resources

This paper focuses on the problem of the probabilistic optimal day-ahead scheduling of energy resources in Active Distribution Networks (ADNs). These resources include both dispersed energy storage systems (DESSs) and volatile renewable embedded generators. Technical constraints related to both energy resources and electrical network are modeled and taken into account in the proposed optimization problem. The paper first proposes a convex formulation of a specific optimal power flow (OPF) used to compute the resources schedule. Its objective function aims at achieving the minimum of the following quantities: network and DESSs losses, energy cost imported from the external grid, and deviations from the day-ahead scheduled power flow with the same external grid. In addition, the ability of using the substation transformer tap-changer is incorporated into the problem with a suitable cost function. The initial OPF formulation is then enhanced thanks to the use of the Mixed Integer Second Order Cone Programming approach in order to formulate a stochastic AC-OPF. The uncertainties of the problem are due to the forecast errors of the PV generation, load consumption and energy prices. The applicability and the effectiveness of the proposed scheduling approach are tested by using a modified version of the IEEE 34 buses test feeder

Optimal siting and sizing of distributed energy storage systems via alternating direction method of multipliers

Energy Storage Systems (ESSs) has an important role in Active Distribution Networks (ADNs). Within this context this paper focuses on the problem of ESSs optimal siting and sizing. Following similar approaches already proposed by the Authors, this paper uses a multi-objective procedure to account various ancillary services that can be provided by ESSs. The proposed procedure takes into account the voltage support and network losses minimization along with minimization of the cost of energy from external grid. For the case of large-scale problems, accounting networks with large number of nodes and scenarios, the selection of the solution methodology is a non-trivial problem. In this respect, the paper proposes and discusses the applicability of the Alternative Direction Method of Multipliers in order to provide an efficient algorithm for large-scale networks that also provide a solution to the optimality aspect. A real large-scale network with real profiles of load and distributed photovoltaic generation is used as the case study to analyze the effectiveness of the proposed methodology

Optimal Allocation of Dispersed Energy Storage Systems in Active Distribution Networks for Energy Balance and Grid Support

Dispersed storage systems (DSSs) can represent an important near-term solution for supporting the operation and control of active distribution networks (ADNs). Indeed, they have the capability to support ADNs by providing ancillary services in addition to energy balance capabilities. Within this context, this paper focuses on the optimal allocation of DSSs in ADNs by defining a multi-objective optimization problem aiming at finding the optimal trade-off between technical and economical goals. In particular, the proposed procedure accounts for: 1) network voltage deviations; 2) feeders/lines congestions; 3) network losses; 4) cost of supplying loads (from external grid or local producers) together with the cost of DSS investment/maintenance; 5) load curtailment; and 6) stochasticity of loads and renewables productions. The DSSs are suitably modeled to consider their ability to support the network by both active and reactive powers. A convex formulation of ac optimal power flow problem is used to define a mixed integer second-order cone programming problem to optimally site and size the DSSs in the network. A test case referring to IEEE 34 bus distribution test feeder is used to demonstrate and discuss the effectiveness of the proposed methodology

Optimal Location and Sizing of Distributed Storage Systems in Active Distribution Networks

Energy balance and ancillary services provided by distributed storage systems to active distribution networks represent two aspects of a single problem that needs to be properly treated in view of the typical distribution networks parameters. In this context, the paper focuses on the problem of the optimal siting and sizing of distributed storage systems. In particular, the paper proposes the formulation of a problem that accounts: (i) the voltage support of storage systems to the grid, (ii) the network losses and (iii) the cost of the energy-flow towards the external grid. As the formulated problem is mixedinteger, non-convex and non-linear, its solution requires the adoption of heuristic techniques. In this respect, a two-stage iterative procedure is proposed. The first stage of the procedure utilizes a genetic algorithm to provide locations and sizes of the distributed storage systems; the second stage evaluates the fitness of the solution provided by the first part by solving a daily AC optimal power flow. An application example, referring to the IEEE 13 busses test feeder, is included in order to demonstrate and discuss the efficiency of the proposed method

On the Optimal Placement of Distributed Storage Systems for Voltage Control in Active Distribution Networks

Within the context of ancillary services provided to active distribution networks by distributed storage systems (DSSs), the paper focuses on the problem of optimally locating DSSs in order to maximize their support to the network voltage control. In particular, the paper proposes an optimal planning procedure that accounts specifically for the minimization of the network voltage deviations based on the formulation of a mixedinteger linear programing problem. In view of the large size of the problem, its solution relies on the so-called benders decomposition technic. The paper discusses the performance and the sensitivities of the proposed method as function of different scenarios accounting for various loads and distributed generation (DG) profiles as well as for different number of DSSs. An application example, referring to the IEEE 13 busses test feeder, is finally included to demonstrate, and discuss, the efficiency of the proposed method

Security Constrained Unit Commitment With Dynamic Thermal Line Rating

The integration of the dynamic line rating (DLR) of overhead transmission lines (OTLs) in power systems secu- rity constrained unit commitment (SCUC) potentially enhances the overall system security as well as its technical/economic performances. This paper proposes a scalable and computation- ally efficient approach aimed at integrating the DLR in SCUC problem. The paper analyzes the case of the SCUC with AC load flow constraints. The AC-optimal power flow (AC-OPF) is linearized and incorporated into the problem. The proposed multi-period formulation takes into account a realistic model to represent the different terms appearing in the Heat-Balance Equation (HBE) of the OTL conductors. In order to include the HBE in the OPF, a relaxation is proposed for the heat gain associ- ated to resistive losses while the inclusion of linear approximations are investigated for both convection and radiation heat losses. A decomposition process relying on the Benders decomposition is used in order to breakdown the problem and incorporate a set of contingencies representing both generators and line outages. The effects of different linearization, as well as time step discretization of HBE, are investigated. The scalability of the proposed method is verified using IEEE 118-bus test system