Virgil Dumbrava

Expansion planning and reliability evaluation of distribution networks by heuristic algorithms

Due to the gradual increase of power demand and variation of loads, the modern distribution networks are growing with complexity more and more. Configuration problems in distribution networks are basically large-scaled combinatorial optimization problems and their solution requires a considerable computing effort, because an urban distribution system usually contains numerous power line sections and sectionalizing switches to be operated. It is, therefore, difficult to rapidly obtain an exact optimal solution on real system. Moreover, reliability issues are becoming increasingly important in modern distribution networks because of both social as well as economic implications. This paper describes several heuristic algorithms applied to find the optimal configuration of meshed distribution network. Also, the most usual reliability indices for the analyzed networks are calculated.

Virtual power plant with energy storage optimized in an electricity market approach

This paper deals with the mathematical formulation and implementation of the optimization model for virtual power plants (VPPs). The daily optimized operation of the VPP is focusing on maximizing its benefit, considering VPP comprising renewable energy sources and energy storage systems, thermal engines and demand-response loads. The optimization model is tested considering two case studies of average electricity prices on the day-ahead market, each of them in four scenarios of the mix renewable energy sources. The model, analyzed on a 24 hours time horizon, is implemented and tested in GAMS. The obtained results show that the best benefit obtained by the virtual power plant owner is obtained when the energy production of analyzed available renewable energy sources is high, and the day-ahead market prices are elevated. In the present paper, the case when the power system operator constraints the exchanges with the virtual power was not considered.

Smart campus-an energy integrated approach

This paper analyzes the optimized operation of smart campus on the electricity market for maximizing his overall profit. The smart campus has the character of a virtual power plant with distributed energy resources with stochastic power and dispatchable classical generating units. The load is represented by the campus consumptions which can be shifted daily to accomplish the desired goals. This smart campus optimizes the use of electrical energy through exchanged electricity with the market and thermal energy through internal production such that to maximize his yearly profit.

Transient analysis of DG interfaced low voltage dc system

The paper deals with the analysis of a low voltage dc distribution system. This dc system efficiently uses the opportunities that distribution generators (DG) offers for the power quality improvement, considering the more easily interconnection of the energy storage devices. The analysis of the energy management system and the behavior of the dc system during faults in the ac grid and dc grid are conducted.

Stochastic optimization of microgrids with renewable and storage energy systems

The microgrids can function as a single controllable system in a grid-connected or islanded operation mode. The transition from grid-connected mode to islanded mode can result in microgrid excess generation or demand, which must be spilled or curtailed. This paper proposes an optimization model for optimizing the microgrid operations accounting for distributed energy resources (stochastic generation and time-varying demand), as well as microgrid operation constrains. The objective is to minimize the microgrid operational costs considering the classical generation capacities and exchanged power with the upstream grid, as well the operational constraints. The analyzed microgrid is composed of a thermal engine, a photovoltaic system, an electrochemical storage system, critical and interruptible loads. The deterministic and stochastic optimization model were formulated, and each optimization model is tested in various case studies considering the different operational states of the microgrid.

Power quality investigation in a passive house

Economic and environmental reasons stimulated people to build low energy houses all over the world. In order to study this kind of buildings, adapted to the Romanian climatic conditions, a new project was developed by the University POLITEHNICA of Bucharest. The present paper deals with the presentation of the passive house build within the campus of University POLITEHNICA of Bucharest and with the power quality analysis of the photovoltaic system installed on the rooftop of the passive house.

Transmission expansion planning optimization for improving RES integration on electricity market

To accommodate the intermittent renewable energy sources in existing power systems, the expansion of networks, storage integration, back-up capacities and efforts for a flexible consumption are required, otherwise grid can be overloaded. The transmission expansion planning (TEP) has the purpose to ensure two important objectives: economic trade and engineering reliability. TEP can increase the competitiveness of the market participants, providing the reliability and safety of the power grid. In this paper, TEP problem is formulated for establishing the optimal decisions in a large real network with classical generators and high share of RES to minimize load-shedding costs and to facilitate energy exchange between consumers and producers. The analysis results were obtained considering the variation of investment budget for a certain number of new transmission lines.

Energy-informatic-centric smart campus

An energy-informatic-centric smart campus represents a viable structure addressing to different groups of users, like: students, teachers/educators, researchers and technical administrators, using information and communications technology system interface for accessing various services and requiring real time information regarding university buildings energy consumption and production, air quality and environmental conditions. This paper deals with the ongoing implementation of a smart campus infrastructure based on an informatic hierarchical system for monitoring and controlling energy consumption and production within a large number of buildings within the university campus. This system can minimize the overall campus exploitation costs using as much as possible the internal energy resources, like high efficiency combined heat and power units and photovoltaic installations, in strong correlation with the objective of high level educational and research activities.

Load profiling for the electricity market

In this paper the load profiles used by different entities (distribution utilities, suppliers) on the electricity market have been analyzed. Load profiles are necessary for utilities from cost of service and rate design to load management and forecasting to settlement. Principal applications for retail suppliers include pricing, cost analysis, planning and assessment of load management, load scheduling and market settlement. Following some methods used to load profiling are presented, together with a case study done according with the Romanian procedure for load profiling.

Consumption profile optimization in smart city vision

The existing trend of consumption increase and population growth, combined with reduction of primary energy resources, determined adoption of energy efficiency increase measures to better cope with the existing necessities. The main characteristics of smart cities are starting to be defined such that to be applied to various cities with different population, sizes and level of technology development. In the future smart cities, the consumer will have a determinant role, possibly becoming a prosumer with consumption/generation profiles scheduled such that to maximize his utility. This paper will contribute to the understanding of smart consumers and intelligent buildings within the smart cities (optimized consumption patterns, demand side management, energy efficiency-all that using price signals information).