N.D. Hatziargyriou

On-Line Preventive Dynamic Security of Isolated Power Systems Using Decision Trees

In this paper the application of decision trees for on-line preventive dynamic security of isolated power systems is presented. Decision trees provide the necessary computational speed for on-line performance and the flexibility of providing preventive control. Emphasis is placed on the on-line use of the decision trees to test the dynamic security of each generation dispatch scenario and thus to provide corrective advice via generation redispatch. Moreover, the algorithm implemented provides the flexibility of displaying the cost of each redispatch. In this way, the method can help in objective decision making. Results from the application of the system on actual load series from the island of Crete, where the proposed system is in trial operation, are presented.

AI helps reduce transformer iron losses

Methods for iron loss reduction during manufacturing of wound-core distribution transformers are presented. More specifically, measurements taken at the first stages of core construction are effectively used, in order to minimize iron losses of transformer (final product). To optimally exploit the measurements (feedback), artificial intelligence methods are applied. It is shown that intelligent systems are able to learn and interpret several variations of the same conditions, thus helping in predicting iron losses with increased accuracy.

Quantification of economic, environmental and operational benefits of Microgrids

Microgrids are Low Voltage distribution networks comprising various distributed generators (DG), storage devices and controllable loads that can operate either interconnected or isolated from the main distribution grid as one controlled entity. The effect of the use of a Microgrid Central Controller (MGCC) to achieve this co-ordinate operation with regards to the potential economic benefits and the power losses avoided in both the local network and the upstream network are presented. Finally, a methodology based on the marginal emissions curve of the upstream network is presented, taking also into account the calculated losses is used for the environmental assessment of the co-ordinate operation of Microgrids. All the above studies have been applied to a typical LV Microgrid interconnected to an actual MV network using actual market prices and DG bids reflecting realistic operational costs.

Decision trees for determination of optimal location and rate of series compensation to increase power system loading margin

Series compensation of transmission lines is one of the most effective means to increase the loading margin of an interconnected power system. In this paper, a methodology is proposed for the identification of the critical transmission lines and their proper compensation rate with respect to voltage stability using decision trees (DTs) methodology. This methodology is applied to the Hellenic interconnected transmission system in normal operation and in (N-1) configurations, taking into account its future expansion plans. Results are validated by comparison with sensitivity analysis

Methods for evaluating penetration levels of wind generation in autonomous systems

During the last decades there has been a continuous growth of wind power generation. This trend, especially in Greek islands, where wind potential is high, raises the issue of acceptable penetration levels of wind generation especially in autonomous systems. This work is part of a research program between PPC S.A. –of Greece and NTUA. The method is applied to two islands, Crete and Rhodes, where wind power penetration is expected to be increased within the next years. The power grid of each island is modeled and speed governors, automatic voltage regulators of conventional plants, as well as wind turbines are modeled in detail. Case studies are formed and simulation results are produced, discussed and eventually the penetration levels are determined, together with proposed measures to increase them.

A Genetic Algorithm Solution to the Governor-Turbine Dynamic Model Identification in Multi-Machine Power Systems

Speed governors are key elements in the dynamic performance of electric power systems. Therefore, accurate governor models are of great importance in simulating and investigating the power system transient phenomena. Model parameters of such devices are, however, usually unavailable or inaccurate, especially when old generators are involved. Most methods for speed governor parameter estimation are based on measurements of frequency and active power variations during transient operation. This paper proposes a genetic algorithm based optimization technique for parameter estimation, which makes use of such measurements. The proposed methodology uses a real-coded genetic algorithm. The paper estimates the parameters of all system generators simultaneously, instead of every machine independently, which is fully in line with the interest to treat the electric power system as a whole and study its comprehensive behaviour. Moreover, the methodology is not model-dependent and, therefore, it is readily applicable to a variety of model types and for many different test procedures. The proposed methodology is applied to the electric power system of Crete and the results demonstrate the feasibility and practicality of this approach.

Evaluation of transmission pricing methodologies for pool based electricity markets

This paper presents and analyses several approaches for transmission cost allocation in a centralized pool based electricity market environment that includes composite embedded/marginal transmission pricing mechanisms. The revenue from marginal cost based remuneration (MBR) necessitates supplementary charges; thus it is required to identify the contribution of individual generators and loads to the line flows using tracing methods and implement usage-based transmission pricing methods for allocating the remaining fixed cost. Eight transmission pricing schemes and three tracing methods are being evaluated and applied on Garvers 6-bus system and on IEEE 24-bus reliability test system to illustrate the different results derived among the pricing schemes for each tracing method or among tracing methods for each pricing scheme.

An evaluation study of wireless access technologies for V2G communications

Vehicle-to-Grid (V2G) technology can be used to interconnect electric or plug in hybrid vehicles with the power grid by either delivering electricity and level peak demands or by throttling their charging rate. Two types of wireless communications are required to a V2G system. The communications between the Aggregator and the Control Center which will be realized through IEEE 802.16-2004 (802.16d) and between Aggregator and the Electric Vehicles which will be realized through vehicular communications (IEEE 802.11p). In this paper a V2G architecture design is presented and the two wireless communication protocols, are proposed and evaluated to the system needs. IEEE 802.16d referred to as Worldwide Interoperability for Microwave Access (WiMAX) specifies the air interface including the medium access control layer and multiple physical layer specifications of fixed broadband wireless access systems supporting multimedia services. IEEE 802.11p Wireless Access in Vehicular Environment defines modifications to IEEE 802.11 to support Intelligent Transportation Systems applications.

A Tabu search method for distribution network planning considering distributed generation and uncertainties

This paper deals with the problem of distribution network planning (DNP) considering distributed generation (DG) and uncertainties. The involved uncertainties are the output power of wind and PV generation, the future load growth in the planning period and the evolution of the electricity prices. A Tabu search (TS)-based method with an embedded probabilistic power flow analysis is developed in order to solve the DNP optimization problem. The probabilistic power flow problem is solved by Monte Carlo Simulation (MCS). The proposed method is applied to a benchmark system and to a 30-bus distribution network considering several scenarios to demonstrate the methods performance and robustness. Simulation results show how the network planning is affected from the considered uncertainties and the optimal network is rather different in comparison to the networks designed via a conventional approach without DG integration.

Transmission expansion planning by enhanced differential evolution

The restructuring and deregulation has exposed the transmission planner to new objectives and uncertainties. As a result, new criteria and approaches are needed for transmission expansion planning (TEP) in deregulated electricity markets. This paper proposes a new market-based approach for TEP. An enhanced differential evolution (EDE) model is proposed for the solution of this new market-based TEP problem. The modifications of EDE in comparison to the simple differential evolution method are: 1) the scaling factor F is varied randomly within some range, 2) an auxiliary set is employed to enhance the diversity of the population, 3) the newly generated trial vector is compared with the nearest parent, and 4) the simple feasibility rule is used to treat the constraints. Results from the application of the proposed method on the IEEE 30 bus test system demonstrate the feasibility and practicality of the proposed EDE for the solution of TEP problem.