Gian Giuseppe Soma

Advanced DMS to manage active distribution networks

The paper presents an advanced Distribution Management System capable to manage an active distribution network economically and safely. The DMS optimizes the power flows in the network, regulates the voltage profiles, acting on reactive flows and tap changers in substation, minimizes the energy losses, reconfigures the network, exploits storage devices and responsive loads in an integrated way. The optimization algorithm finds the optimal combination of such operation options to minimize system costs without causing violations of the technical constraints. The system costs include the energy losses, the cost of generation curtailment, the cost of reactive power, the cost of load shedding, and the cost of storages. The proposed method has been applied on a model test network to verify the validity of the approach.

Multi-objective programming for optimal DG integration in active distribution systems

Active distribution networks have the capability to allow the distributed energy resources integration at reasonable costs, opening new business opportunities. Although the sharing of responsibility among the system stakeholders (e.g., the Civil Society, the DSO and DER owners) is essential, undeniably they pursue different, and sometimes opposite goals. The authors, by adopting multi objective programming to simulate the behavior of the stakeholders, aim at assessing how the system players will drive the distribution evolution under the influence of different regulatory environments. All the scenarios have been analyzed on a case study representative of a typical distribution system. The results presented can help Regulators to define a fairer asset and performance based distribution revenue.

A comparison of distribution network planning solutions: Traditional reinforcement versus integration of distributed energy storage

Despite the radical changes that the electricity distribution system is currently facing and will have to face in the next decade, utilities still adopt a traditional approach for the expansion planning of their networks, based essentially on the fit and forget concept (only network reinforcements to cope with the worst case scenario). Although innovative solutions have been proposed in the last decade at the electricity distribution level (distributed energy storage, active management of distributed generation, demand side integration, etc.) and are becoming technically and economically feasible, they are not yet considered as viable planning alternatives. The reasons of this reluctance are the lack of ad hoc planning tools and business cases. In the paper, a novel planning tool for Active Distribution Networks is applied to a real MV distribution network of the A2A utility sited in the district of Brescia in order to prove the benefit of energy storage devices.

Active distribution network reliability assessment with a pseudo sequential Monte Carlo method

The increasing penetration of renewable intermittent generation imposes challenges on the existing distribution infrastructure and the system operator. New power flow patterns may require changes to control strategies, enhanced distribution automation, enforcement of distribution network infrastructure and/or greater degrees of information management and control according to the active distribution network paradigm (ADN). ADN might improve the quality of service or might lead to a more risky distribution system depending on the reliability of its communication and management system. In order to provide a measure of this risk, the reliability of ADNs operation is assessed in the paper with a pseudo sequential Monte Carlo method. The procedure is used to assess the reliability of a given active distribution network in different real case scenarios.

Aggregated electric vehicles load profiles with fast charging stations

The concept of electrical-mobility in opposition to the present oil-mobility is becoming even more attractive worldwide. Fast Charging Station (FCS) refers charging stations with nominal power equal or higher than 50 kW. The impacts of EV charging on electricity grids is becoming an increasingly important subject of study, but detailed knowledge about the future charging profiles of EVs appears to be missing in Literature. The FCS requires high power and they must be connected to MV networks. For that reasons, it is crucial to analyze these situations and to model the FCS consumption, in order to correctly plan the expansion of the MV system. In the paper a Monte Carlo simulation methodology is proposed to model the aspects that influence the request of fast charge for EVs. The EV charge profiles should be used in the planning and in the EV impact analysis of the future networks.

Considering Voltage Dips Mitigation in Distribution Network Planning

Voltage dips are disturbances that undermine the quality of supply or, more precisely, the power quality perceived by the customers, often causing heavy economic damages to the end-users. Methods for mitigating voltage dips have been widely investigated in literature, but poor attention has been given to solutions that consider their mitigation at the planning stage. In previous works, the authors have proposed a distribution network planning methodology to deal simultaneously with the network design and the power quality. The optimization algorithm is able to find some convenient solutions to comply with power quality constraints. To reduce the expected number of voltage dips above a threshold established by regulators and to protect the customers, the planner is driven to perform specific actions, as the installation of custom power devices in particular nodes of the network. In this paper, an improved model of dynamic voltage restorer has been developed and implemented in the optimization methodology. Accordingly with this model the effectiveness of the compensation device has been evaluated with the aim at finding the most economical solution to voltage-dip problems. In the paper, examples are provided to showing the impact of voltage dips and their mitigation in distribution planning.

Robust distribution state estimation for active networks

A heuristic optimization algorithm based on the Dynamic Programming theory is proposed to find the optimal placement of measurement devices, i.e. to determine their number and position. The optimization procedure explicitly considers network reconfigurations (caused by random faults or by the active management of the network), so that the final measurement system allows the distribution state estimation to provide an accurate estimate of the system status in all the possible practical conditions. The branch currents are taken as state variables for improving the quality of the solution of the state estimator that exploits field measurements and load pseudo-measurements. The uncertainties introduced by the measurement chain are simulated with a Monte Carlo algorithm. Variations of both load demand and network parameters are also modeled in the Monte Carlo algorithm. The provided examples show the effectiveness of the optimization process.

Optimal placement of custom power devices to mitigate voltage dips in distribution networks

The paper presents an approach to optimally allocate custom power devices, as dynamic voltage restorers, in a given distribution network with the aim at reducing the expected number of voltage dips suffered by the customers. The optimization algorithm based on the paradigm of dynamic programming is able to find the best compromise between the benefits achievable by undertaking mitigation actions in the network and the total cost relevant to voltage dips, that includes the investment cost for the device, the cost paid by the customers for the damages caused by the not mitigated disturbances and for the premium quality contracts. In the paper, the expected voltage dip frequency is calculated by means of a stochastic method that combines the system fault rate with the deterministic short circuit theory. Examples derived from real cases are provided to show the effectiveness of the optimization.

Planning for “high quality” distribution networks

Voltage dips are the most common power quality disturbances. They can often cause serious damages to the end- users, especially to the industrial ones or those involved in services that today are almost entirely based on digital processes. Thus, their mitigation is assuming a key role for both customers and distributors. The first ones look for eliminating any obstacle to the correct operation of their processes, and are often willing to stipulate premium contracts that guarantee a high level of quality to their power supply. The second ones have to solve power quality problems in their networks with restrict available budget, first of all, to achieve the Regulatory targets on quality but also to satisfy the most exigent customers. In previous works, the authors proposed a distribution network planning methodology that adds to the traditional technical constraints also the target of the power quality. In terms of voltage dips, the power quality target to be achieved may be limiting the voltage dips frequency in each node of a given network within a prefixed threshold. In this paper, an improved algorithm able to find the most economical solutions to comply with this constraint has been developed. This improved algorithm considers by the same standards different corrective actions, with the aim at finding the best compromise between investment and benefits. Accordingly with this view, the goal is minimizing the cost that the distributors have to sustain for the protective measures, the cost paid by the customers for the damages caused by the not mitigated disturbances and for the premium quality contracts. The effectiveness of the proposed approach is proved by examples in a test network and in a small one derived from real cases.

Multi-objective programming for optimal WiMax allocation in smart grid

Wireless communication systems will be widely used in modern distribution networks to allow the integration of RES and the exploitation of energy storage and active demand without jeopardizing the overall system reliability. ICT is the enabling infrastructure for active distribution, but, since efficiency and reliability of power delivery may be influenced by weather conditions besides the reliability of ICT components, the optimal position and number of antennas must take into account not only the cost for radio stations but also the impact on the expected distribution reliability. In the paper, an NSGA-II multi-objective optimization algorithm to find the optimal location of WiMax antennas is proposed. The impact of the rain-fade is explicitly taken into account with an internal sub-optimization that considers the probability of rain days that can affect the communication between the control centre and DER.