Yiannis A. Katsigiannis

Hybrid Simulated Annealing–Tabu Search Method for Optimal Sizing of Autonomous Power Systems With Renewables

Small autonomous power systems (SAPS) that include renewable energy sources are a promising option for isolated power generation at remote locations. The optimal sizing problem of SAPS is a challenging combinatorial optimization problem, and its solution may prove a very time-consuming process. This paper initially investigates the performance of two popular metaheuristic methods, namely, simulated annealing (SA) and tabu search (TS), for the solution of SAPS optimal sizing problem. Moreover, this paper proposes a hybrid SA-TS method that combines the advantages of each one of the above-mentioned metaheuristic methods. The proposed method has been successfully applied to design an SAPS in Chania region, Greece. In the study, the objective function is the minimization of SAPS cost of energy (€/kWh), and the design variables are: 1) wind turbines size, 2) photovoltaics size, 3) diesel generator size, 4) biodiesel generator size, 5) fuel cells size, 6) batteries size, 7) converter size, and 8) dispatch strategy. The performance of the proposed hybrid optimization methodology is studied for a large number of alternative scenarios via sensitivity analysis, and the conclusion is that the proposed hybrid SA-TS improves the obtained solutions, in terms of quality and convergence, compared to the solutions provided by individual SA or individual TS methods.

A Novel Colored Fluid Stochastic Petri Net Simulation Model for Reliability Evaluation of Wind/PV/Diesel Small Isolated Power Systems

This paper introduces a new general methodology for the modeling and reliability evaluation of small isolated power systems, which include wind turbines, photovoltaics, and diesel generators, based on fluid stochastic Petri nets (FSPNs). The proposed methodology presents two major novelties in FSPN modeling, namely: 1) the introduction of a new kind of Petri net arc, called the database arc, which makes possible the direct import of real data in the simulation process; and 2) the selection of constant time intervals in FSPN modeling, instead of assuming continuous dynamics defined by the change of fluid level over time. Moreover, in order to construct the overall system model, this paper proposes a general framework for modular representation of the system under study following a number of well-defined steps. The obtained model is fully parameterized and compared to classical simulation methods, it provides to its user the additional advantage of graphical representation of systems components and attributes. Four scenarios, which describe power systems performance under different conditions, were implemented. For each one of the developed scenarios, nine reliability and performance indexes have been calculated and compared.

Energy efficiency and environmental impact of biogas utilization in landfills

This study investigates the utilization of landfill biogas as a fuel for electrical power generation. Landfills can be regarded as conversion biogas plants to electricity, not only covering internal consumptions of the facility but contributing in the power grid as well. A landfill gas plant consists of a recovery and a production system. The recovery of landfill gas is an area of vital interest since it combines both alternative energy production and reduction of environmental impact through reduction of methane and carbon dioxide, two of the main greenhouse gases emissions. This study follows two main objectives. First, to determine whether active extraction of landfill gas in the examined municipal solid waste sites would produce adequate electric power for utilisation and grid connection and second, to estimate the reduction of sequential greenhouse gases emissions. However, in order to optimize the designing of a plant fed by biogas, it is necessary to quantify biogas production over several years. The investigation results of energy efficiency and environmental impact of biogas utilization in landfills are considering satisfactory enough both in electric energy production and in contribution to greenhouse gases mitigation.

Improved wind power forecasting using a combined neuro-fuzzy and artificial neural network model

The intermittent nature of the wind creates significant uncertainty in the operation of power systems with increased wind power penetration. Con- siderable efforts have been made for the accurate prediction of the wind power using either statistical or physical models. In this paper, a method based on Artificial Neural Network (ANN) is proposed in order to improve the predictions of an existing neuro-fuzzy wind power forecasting model taking into account the evaluation results from the use of this wind power forecasting tool. Thus, an improved wind power forecasting is achieved and a better estimation of the confidence interval of the proposed model is provided.

Genetic algorithm solution to optimal sizing problem of small autonomous hybrid power systems

The optimal sizing of a small autonomous hybrid power system can be a very challenging task, due to the large number of design settings and the uncertainty in key parameters This problem belongs to the category of combinatorial optimization, and its solution based on the traditional method of exhaustive enumeration can be proved extremely time-consuming This paper proposes a binary genetic algorithm in order to solve the optimal sizing problem Genetic algorithms are popular optimization metaheuristic techniques based on the principles of genetics and natural selection and evolution, and can be applied to discrete or continuous solution space problems The obtained results prove the performance of the proposed methodology in terms of solution quality and computational time.

Determining and exploiting the distribution function of wind power forecasting error for the economic operation of autonomous power systems

Many efforts have been presented in the bibliography for wind power forecasting in power systems and few of them have been used for autonomous power systems. The impact of knowing the distribution function of wind power forecasting error in the economic operation of a power system is studied in this paper. The papers proposes that the distribution of the wind power forecasting error of a specific tool can be easily derived if, for that model, an evaluation of its performance is made off-line comparing the forecasted values of the tool with the actual wind power values in the same horizon. The proposed methodology is applied to the autonomous power system of Crete. It is shown that the improvement of the performance of wind power forecasting tool has significant economic impact on the operation of autonomous power systems with increased wind power penetration. The obtained results for various levels of wind power production and load show that using only mean absolute percentage error (MAPE) leads to significant change in the estimation of the wind power to be shed to avoid technical limits violation, especially if the wind power forecasting tool presents underestimation of the actual production

Generation Expansion Planning of Crete Power System for High Penetration of Renewable Energy Sources

In this paper the Crete’s Island power system, which is the largest isolated power system in Greece, is analyzed in two long term scenarios in order to estimate the corresponding costs and benefits associated with a significant high electricity production from renewable energy sources (RES) technologies in the period 2009-2020. In the first scenario, a 20% RES energy penetration in year 2020 is assumed, while in the second scenario the final RES energy penetration is increased to 50%, and it is achieved with the installation of hydro pumped storage systems. Long-range Energy Alternatives Planning (LEAP) software is used to develop the electricity demand model, as well as to estimate the gross electricity generation in Crete and the annual CO2 equivalent emissions for the considered scenarios. This study demonstrates that substantial RES production till 2020 is technically feasible, and provides benefits in the forms of carbon emission reductions, energy adequacy and dependency.

Effect of Wind Turbine Classes on the Electricity Production of Wind Farms in Cyprus Island

This paper examines the effect of different wind turbine classes on the electricity production of wind farms in two areas of Cyprus Island, which present low and medium wind potentials: Xylofagou and Limassol. Wind turbine classes determine the suitability of installing a wind turbine in a particulate site. Wind turbine data from five different manufacturers have been used. For each manufacturer, two wind turbines with identical rated power (in the range of 1.5 MW–3 MW) and different wind turbine classes (IEC II and IEC III) are compared. The results show the superiority of wind turbines that are designed for lower wind speeds (IEC III class) in both locations, in terms of energy production. This improvement is higher for the location with the lower wind potential and starts from 7%, while it can reach more than 50%.

Techno-Economic and Environmental Evaluation of Large Scale PV Integration in Greece

This paper evaluates the current status of renewable energy sources integration and future trends, especially of the photovoltaics, in the interconnected power system of Greece and the power system of Crete Island, which is the largest isolated power system in Greece. Focusing on the ongoing developments and prospects, the paper investigates the impacts of the expected sufficient photovoltaic installations on the energy market and the greenhouse gas emissions, as well as the reduction in CO2 emissions costs due to the installation of photovoltaics and other renewable energy technologies.

Impact of Increased RES Generation on Power Systems Dynamic Performance

In this paper, the impact of high wind power and photovoltaics penetration on the dynamic behavior of an island power system like one operates in Crete is investigated. Several simulations were performed leading to the fact that it is possible to achieve higher level of renewable energy sources penetration without significant dynamic security problems, if power units spinning reserve exists and the corresponding control systems have a sufficiently fast response.