Mark Ehsani’s scientific contributions

This paper represents an approach for renewable energy sources integration with the existing grid. Unique types of loads can be exploited to allow for a sustainable solution to energy integration. A case study of Saudi Arabia is investigated where desalination plants coupled with a water storage tank is utilized to mitigate the variability of renewable sources. A hybrid photovoltaic-wind turbine generator system (PV-WTG) is proposed. The results indicate two critical points. First, even in a fossil fuel-rich country, sustainable renewable sources are economically feasible. The second point is that the typical storage element (i.e., batteries), is not always the best candidate for energy storage as in the case of desalination plants. Instead, storing the excess energy as water in a storage tank is economical and less prone to failures as compared to large-scale batteries. The problem is formulated as an optimization problem and solved using heuristic techniques.

The Integration of renewable energy resources suffers from two fundamental issues, variability, and uncertainty of their power output. These issues hinder the integration of renewable resources with the existing grid. This paper addresses these issues and proposes a new methodology to minimize the impact of intermittency by offering an alternative approach for energy storage. The concept of value storage is introduced as an alternative to energy storage to replace the typical large-scale battery energy storage system (BESS). The concept refers to the storage of excess renewable energy as products from industrial loads instead of the energy itself which enables a Demand Side Management (DSM) technique to be applied, namely, load shifting for some industrial plants. A hybrid Photovoltaic-wind turbine generator PV-WTG and storage system is proposed to penetrate the existing electric grid, with significant cost savings by displacing the conventional energy generation in a fossil fuel-rich location. A size optimization based on differential system cost is formulated and solved by an Enhanced Genetic Algorithm (EGA) technique. Uncertainty impact studies were done by incorporating multiple scenarios and comprehensive sensitivity analysis.

This paper investigates the impact of the wind turbine (WT) modeling on a hybrid wind-photovoltaic (PV) system installed in a city in Jordan. A closer look is taken at the parameters affecting the output power to accurately model the system. This helps in monitoring the turbine performance, sizing of the wind farm and the entire hybrid system, which will definitely affect the annual energy extracted (AEE) from a single WT as well as the entire wind turbines (WTs). Also, the cost of the hybrid system such as the net present cost (NPC), the grid operating cost (GOC) and the cost of energy (COE) will be affected. Six WT models are added to Hybrid Optimization Multiple Energy Resources software in order to see the sizing and cost effects of the new system. A step-by-step analysis and design of each proposed WT model and its effects on the hybrid system are presented. Results show that as the WT simplified models change from the cubic, quadratic, toward the linear one, the resulting system has a significant percentage error in the estimation of the cost as well as AEE. Also, the number of WTs increases at the system level till it becomes a wind only configuration in the linear model. But, this is at the penalty of the imprecise sizing solution, which leads to wrong estimates for the project investment. Therefore, the WT has to be modeled accurately by considering many parameters such as the air density, e.g., geographic elevation. The results show that the WT model designed at sea level shows error estimates in both AEE and the system cost from the one designed at actual temperature or elevation above sea level (a.s.l). The simple WT models will not deliver the AEE theoretically calculated. This energy deficit will be substituted by the more expensive on-grid conventional power plant fuel energy. In other words, in order to solve a real problem, the real values for parameters affecting the WT model have to be considered. The same procedure can be applied in other locations around the world.

Renewable energy is the ultimate goal to mitigate global greenhouse gas emissions, and to have energy independence. Renewable energy computation is best accomplished by taking into account the annualized statistical wind power availability. In this paper, the annual energy has been accurately computed for a wind turbine (WT) by an advanced modeling, taking into account the characteristics of the WT and the environment. Accounting for the parameters affecting the output energy, is implemented in order to correctly model the system. This helps in monitoring the power generation, and sizing of the wind farm. Mainly, two scenarios are discussed. First, accuracy of WT modeling when the wind speed only affects the output power. Second, accuracy of air density modeling when many parameters affect the WT output power which include wind speed, power coefficient, elevation above sea level, temperature, pressure and humidity. It is shown that accurate modeling has a considerable impact on the computed annual energy extracted from a single WT and thus the whole wind farm. This will have a major impact on the sizing of the wind farm, and hence affects the net present cost of the entire system.

Photovoltaic (PV) renewable energy resources are of interest for researchers today. An investigation of the PV characteristics is useful to understand its behavior. In this paper, the characteristics of the PV module have been explored and analyzed for different values of temperature at constant insolation (1kW/m2), and with different values of irradiance at constant temperature (25°C). Moreover, the characteristics of the PV module have been compared to an ideal voltage source in many cases by varying the ripple and average value of the PV voltage, current and power. The maximum power point (MPP) of the PV module is found graphically and analytically. Then, the duty ratio at which the PV module operates at maximum power, effect of changing the inductance value and switching frequency are explored for the PV voltage, current and power. The results show that the PV module behaves like an ideal voltage source at the MPP in case of average value comparison. Furthermore, the two sources have approximately the same ripple current. The effects of increasing the inductance value as well as the switching frequency values are investigated. As the inductance value and frequency increase, this will give very low ripple current, voltage and power, and thereby a better approximation for the MPP.