Vito Calderaro

Failure Identification in Smart Grids Based on Petri Net Modeling

This paper presents a method to identify and localize failures in smart grids. The method is based on a carefully designed Petri net (PN) that captures the modeling details of the protection system of the distribution network and allows the detection/identification of failures in data transmission and faults in the distribution network by means of simple matrix operations. The design of the PN model is carried out by carefully composing multiple PN models for single protection systems: Such an approach allows the identification of the faults despite possible strong penetration of distributed generation. In order to verify the method, two case studies are discussed. The results highlight that the proposed method can remove a lot of the complexity of the associated data analysis despite the possible presence of malfunctioning protection systems and misinformation due to communication and other errors.

Optimal Decentralized Voltage Control for Distribution Systems With Inverter-Based Distributed Generators

The increasing penetration of distributed generation (DG) power plants into distribution networks (DNs) causes various issues concerning, e.g., stability, protection equipment, and voltage regulation. Thus, the necessity to develop proper control techniques to allow power delivery to customers in compliance with power quality and reliability standards (PQR) has become a relevant issue in recent years. This paper proposes an optimized distributed control approach based on DN sensitivity analysis and on decentralized reactive/active power regulation capable of maintaining voltage levels within regulatory limits and to offer ancillary services to the DN, such as voltage regulation. At the same time, it tries to minimize DN active power losses and the reactive power exchanged with the DN by the DG units. The validation of the proposed control technique has been conducted through a several number of simulations on a real MV Italian distribution system.

Maximizing DG penetration in distribution networks by means of GA based reconfiguration

The distributed generation (DG) capacity will increase considerably in the future distribution networks, involving more and more complex control systems able to integrate DG supervision and control into network control schemes. This paper proposes a reconfiguration methodology based on a genetic algorithm (GA), that aims at achieving the maximum DG penetration, while observing thermal and voltage constraints. The proposed methodology has been tested on a 33-bus system with DG units. Simulation results demonstrated its effectiveness in increasing both individual and overall DG penetration allowing to exploit network capability. The methodology can assist distribution system operators (DSOs) in planning and managing DG connections and in maximizing the total GD penetration and renewable sources exploitation

A smart strategy for voltage control ancillary service in distribution networks

The expected impact of distributed generation (DG) into Smart Grid represents a great challenge of the future for power systems. In particular, the integration of DG based on renewable energy sources (RESs) in distribution networks, without compromising the integrity of the grid, requires the development of proper control techniques to allow power delivery to customers in compliance with power quality and reliability standards. This paper proposes a coordinated local control approach that allows distribution system operator (DSO) and independent power producers (IPPs) to obtain benefits offering the voltage regulation ancillary service to DSO and maximizing allowable active power production for each RES unit belonging to the same IPP. The control is based on a cooperation of data transfer between DSO and IPPs. In order to realize such cooperation, a nonlinear constrained optimization problem is formulated and solved by sequential quadratic programming (SQP) method. The validation of the proposed control technique has been conducted through several time series simulations on a real MV Italian distribution system.

A new algorithm for steady state load-shedding strategy

This paper deals with a steady state load-shedding strategy considering the effect of the demand priorities on the operation of the power system during emergencies. The load-shedding problem is solved by a new algorithm (the Alliance Algorithm) based on the “alliance among tribes” (a tribe or an alliance is a possible solution with a proximity degree to the optimum). The obtained results prove additional enhancements compared to other heuristic approaches. The case studies are carried out on 30 and 57 bus IEEE test networks.

Distributed Generation and local voltage regulation: An approach based on sensitivity analysis

The increasing diffusion of distributed generation plants in recent years could introduce problems concerning voltage regulation in Medium Voltage (MV) radial distribution networks. Among the various control techniques able to perform voltage regulation, local sensitivity analysis based ones are suitable to regulate voltage profiles within standard limits. This paper presents a decentralized sensitivity based control technique able to regulate voltage profiles at buses where wind power generators are connected, taking into account capability curves constraints of wind turbines. The implemented control strategy allows voltage regulation avoiding, as much as possible, both disconnection of the wind turbine and reduction of active power production. Validation of the proposed control algorithm has been carried out by simulations run on a real MV Italian radial distribution network.

Optimal Switch Placement by Alliance Algorithm for Improving Microgrids Reliability

A method for optimal switches placement in distribution systems with distributed generation is presented in this paper. According to both technical and economical issues, the method allows minimizing the unsupplied loads in case of permanent faults, while limiting the number of installed switches. The problem is formulated as a mixed integer non linear programming problem (MINLP) and the solution is obtained by a new metaheuristic algorithm, i.e., the Alliance Algorithm. The method is based on self-microgrids forming and allows improving the continuity of the service as confirmed by simulation results on both an IEEE standard and a real test network.

Optimal fuzzy controller for voltage control in distribution systems

The increasing diffusion of distributed generation plants in recent years highlights problems concerning voltage regulation in medium voltage (MV) radial distribution networks. Among various possible control techniques able to regulate voltage profiles, intelligent systems based ones seems to be very promising. In particular, fuzzy control techniques are very interesting for a wide range of applicative fields like power distribution systems control, allowing regulation of voltage profiles handling uncertainty/vagueness and imprecise information. This paper presents a decentralized fuzzy based control technique finalized to realize a local regulation of voltage profiles at buses where wind power generators are connected, in order to avoid their disconnection. Validation of the proposed control system has been carried out by simulations conducted on a real MV Italian radial distribution system.

Impact analysis of distributed PV and energy storage systems in unbalanced LV networks

The integration of distributed PV units in LV distribution networks with co-located energy storage systems (ESSs) allows increasing the amount of consumed local electrical energy while significantly raising the PV penetration. The installation of ESSs may in addition promote the self-consumption of energy and reduce the mismatch between the demand and the PV power generation making such power source dispatchable. A Monte Carlo simulation is performed by varying residential load profiles, sizes and locations of PV units and ESSs in order to assess the impact that a local and independent control of co-located PV units and ESSs have on the grid. Time series unbalanced power flow simulations are carried out considering different scenarios on a typical LV Italian distribution network. The results are evaluated in terms of benefits on voltage profiles pointing out a significantly reduction of voltage problems on the network at each penetration level.

An algorithm to optimize speed profiles of the metro vehicles for minimizing energy consumption

The calculation of optimal driving speed profiles for metro vehicles that improve energy saving and, thus, reduce costs, are investigated. The optimization problem is solved in two different steps: in the first one, a Dynamic Programming Optimization (DPO) algorithm (including slopes and curves effects) is used to find a set of pseudo-optimal speed cycles; the objective is to minimize the electrical energy used for traction subject to constraints such as travel time, trip distance, acceleration limits, etc. In the second optimization step, the speed profiles set are evaluated in a simulation tool implemented to estimate the power flow among vehicles through the metro network. A test campaign monitoring the saved energy and main electric variables have been implemented and the presented results showing the effectiveness of the performance of the proposed optimization algorithm.