An analysis of the power system functioning and the behaviors of the energy market participants allows the trends taking place within years to be identified, including these associated with the evolution of the electric energy and power demand profiles. The problems of balancing the peak power demand are of both a short and long term nature, which implies the need for changes in the electricity generation sector. Apart from the existing “silo-type” generation units, the construction of distributed energy sources implemented in the civic formula in the framework of self-sufficient energy communes and energy clusters is becoming increasingly important. Support for these programs is realized both at the legislative level, as well as within dedicated competitions and ministerial activities. The financial support carried out by the National Fund for Environmental Protection and Water Management and the Regional Operational Programs is also noticeable. One of the activities aimed at spreading the idea of clustering was the competition for certified energy clusters, conducted by the Ministry of Energy. The goal of the contest was the promotion and development of the distributed energy sector, which could be used for the improvement of energy security in the local manner and constitute a basis for the knowledge necessary in planning and developing the state’s energy policy. The paper presents a synthetic analysis of the results of the competition for a certified energy cluster from the perspective of planning and operational needs related to the functioning of the power system. Further, the information about the investment plans of new generation capacities, including their breakdown with respect to type, achievable power and costs has been provided. Also, the balancing of the demand for electric energy by own generation within the energy clusters has been characterized for three time perspectives
The growth in the system load accompanied by an increase of power loss in the distribution system. Distributed generation (DG) is an important identity in the electric power sector that substantially overcomes power loss and voltage drop problems when it is coordinated with a location and size properly. In this study, the DG integration into the network is optimally distributed by considering the load conditions in different load models used to surmount the impact of load growth. There are five load models tested namely constant, residential, industrial, commercial and mixed loads. The growth of the electrical load is modeled for the base year up to the fifth year as a short-term plan. Minimization of system power loss is taken as the main objective function considering voltage limits. Determination of the location and size of DG is optimally done by using the breeder genetic algorithm (BGA). The proposed studies were applied to the IEEE 30 radial distribution system with single and multiple placement DG scenarios. The results indicated that installing an optimal location and size DG could have a strong potential to reduce power loss and to secure future energy demand of load models. Also, commercial load requires the largest DG active injection power to maintain the voltage value within tolerable limits up to five years.
The loss of power and voltage can affect distribution networks that have a significant number of distributed power resources and electric vehicles. The present study focuses on a hybrid method to model multi-objective coordination optimisation problems for dis- tributed power generation and charging and discharging of electric vehicles in a distribution system. An improved simulated annealing based particle swarm optimisation (SAPSO) algorithm is employed to solve the proposed multi-objective optimisation problem with two objective functions including the minimal power loss index and minimal voltage deviation index. The proposed method is simulated on IEEE 33-node distribution systems and IEEE-118 nodes large scale distribution systems to demonstrate the performance and effectiveness of the technique. The simulation results indicate that the power loss and node voltage deviation are significantly reduced via the coordination optimisation of the power of distributed generations and charging and discharging power of electric vehicles.With the methodology supposed in this paper, thousands of EVs can be accessed to the distribution network in a slow charging mode.
This paper presents a new OpenFlow controller: the Distributed Active Information Model (DAIM). The DAIM controller was developed to explore the viability of a logically distributed control plane. It is implemented in a distributed way throughout a software-defined network, at the level of the switches. The method enables local process flows, by way of local packet switching, to be controlled by the distributed DAIM controller (as opposed to a centralised OpenFlow controller). The DAIM ecosystem is discussed with some sample code, together with flowcharts of the implemented algorithms. We present implementation details, a testing methodology, and an experimental evaluation. A performance analysis was conducted using the Cbench open benchmarking tool. Comparisons were drawn with respect to throughput and latency. It is concluded that the DAIM controller can handle a high throughput, while keeping the latency relatively low. We believe the results to date are potentially very interesting, especially in light of the fact that a key feature of the DAIM controller is that it is designed to enable the future development of autonomous local flow process and management strategies.