Systems Design for Energy Demand by Optimal Utilization of Renewable Energy in Robust Aquaponic Systems

In a debate with other reservoirs, ocean waves furnish an ample supply of clean, reliable, and decent energy, but this origin requires to be made a cost-effective fount for physical energy return. For this mission, the proposed membership functions are adopted and stabilization criterion of the closed-loop T-S fuzzy systems are obtained through a new parametrized LMI (linear matrix) inequality which is rearranged by machine learning membership functions.

Published by SCHOLINK INC. designed as shown in Fig. 1, which indicate the diversity of the practical applications in the ocean. The cost of tapping the wave energy has increased from the 1980s but gradually declined and is likely to further reduce with advances in the technology industry (Osmundsen, Almklov, & Tveterås, 2017). As energy costs from fossil fuels are exorbitant, wave energy could become economically feasible in the near future. Thus, policy-makers, the private sector, and the general public are interested in the conversion of wave energy into electrical energy. The two important steps in this process are (1) assessment of the ability of a site to produce electricity and (2) identification of surrounding ecosystems and the potential impacts and activities in support of electricity production (Read & Fernandes, 2003).

Figure 1. Wave Power Devices
While the waves may provide a source of clean and renewable energy, a wave energy conversion project may harm the protection of the marine species and habitats, and create a strategic conflict with the existing marine ecosystems. Wave energy conversion facilities and their potential impacts, including fishing, planktonic and benthic habitat; recreation; aesthetic point of view changes; hydrodynamic and wave environment; and navigational hazards were studied by (Bohl, 1977;Collins et al., 1975;Naegel, 1977). Many potential impacts are site specific, and the extent of these impacts on coastal and marine ecosystems is unclear, because the studies on the wave energy conversion projects are limited; hence, the concept is poorly understood. This knowledge gap hindered the development of practical equations to support wave energy projects related to marine spatial planning. An assessment of wave energy capacity of a site considers various factors such as wave energy resources, the characteristics of wave energy conversion device, the cost-effectiveness of energy conversion facility, locational constraints, and uses of the information on ecosystem properties or compatibility with others.
Marine spatial planning is at a nascent stage in North America, and involves an interaction between the planners to consider the cumulative impact of the procedure on the coastal and marine space human activities (Sneed, Allen, & Ellis, 1975). Implementing the wave energy projects and efficient marine www.scholink.org/ojs/index.php/ees Energy and Earth Science Vol. 1, No. 1, 2018 spatial planning requires a comprehensive framework that considers these various kinds of information.
It is estimated that the wave power resources can help to identify potential sites of energy-rich areas and sustainable resources. Previous studies employed different scales to estimate the potential of wave power. For example, the global-and regional-scale studies have shown that the west coast of Europe (i.e., Ireland, Portugal, and Scotland), similar to the North American west coast (i.e., British Columbia, Washington, Oregon, and California), is the main area of wave energy projects because of its potential for abundant wave energy harvest, which can be used to meet the demands of high coastal population areas (Lewis, Yopp, & Schramm, 1978;Sutton & Lewis, 1982;Timmons & Ebeling, 2010). Previous research focused on a local scale to quantify near-shore wave energy resources and to identify hot spots in the field of wave energy (Mollison & Holmgren, 1981;Todd, 1980). Different types of wave energy conversion device are used to extract energy from the waves, and various technologies are employed to calculate how much energy can be harvested as a function of the local wave condition change. For example, using a attenuator-type device (for example, sea snake, the Pelamis Wave Power, Edinburgh, Scotland) works more effectively in the Irish and Scottish region (Lewis, Yopp, & Schramm, 1978), where the wave height typically under high sea conditions aids in the estimation. In contrast, the terminator-type devices (for example, an oscillating water column device from Energetech Corporation, Utah, USA) work more efficiently on the west coast of North America (Zweig, 1986), where there is disposal of longer period waves (such as swelling).
In reality, a wave energy conversion efficiency of the device depends not only on the location of the potential energy to be harvested, but also on income and decisions related to the construction and operating costs of the facility. The economic value of the harvested wave energy facilitates to identify the specific location of energy conversion facility and to evaluate the potential tradeoff between the cost positioning factors related to the installation location, maintenance, and operation of the facility.
While the ability to develop the harvest wave energy method is explored in (Lewis, Yopp, & Schramm, 1978;Sutton & Lewis, 1982;Zweig, 1986;McMurtry, Nelson, & Sanders, 1990), harvest wave energy does not provide explicit spatial information to assess the cost of wave site energy generation or the other associated estimates.
This study developed a wave energy conversion device to identify a potential site, which provides decision support equations for the policy-makers to respond to the challenges of wave energy projects related to integrated coastal and marine spatial planning. First, the study developed a model of wave energy as ecosystem services, and the tradeoffs (investment) equation (McMurtry, 1992) is a part of an integrated assessment (Rakocy 1984;Watten & Busch, 1984). The wave energy model by using ecosystem services is based on the framework of Talese and other researchers (Rakocy, 2012) and consists of three parts: (1) the model was based on wave conditions ("supply measures"), (2) the model used a wave energy conversion device to quantify the potential of wave power evaluation ("service standards") consisting certain technical information in harvesting energy, and (3) the utility of the model was evaluated as capital investment ("value index") to assess the economic value of wave energy conversion facilities. Second, the study conducted a compatibility analysis to determine the optimum compatibility between the wave energy conversion device and the existing uses of the oceans.
Investment in an ecosystem service model, including wave energy in the model, is described here. This equation is used in many other coastal and marine spatial planning processes, and can be used for a variety of related marine renewable energy projects to support marine spatial planning (Rakocy, Masser, & Losordo, 2006).

Evaluation of the Formulas
The mathematical models of many physical and engineering systems are frequently of high dimension, or possessing interacting dynamic phenomena. The information processing and requirements to experiment with these models for control purposes are usually excessive. It is therefore natural to seek techniques that can reduce the computational effort. The methodologies of large-scale systems provide such techniques through the manipulation of system structure in some way. Thus, there has been considerable interest in the research area of modeling, analysis, optimization and control of large-scale systems (Mahmoud, Hassan, & Darwish, 1985). During the past several years, fuzzy-rule-based modeling has become an active research field because of its unique merits in solving complex nonlinear system identification and control problems. This approach can obtain more flexibility and more effective capability of handling and processing uncertainties in complicated and ill-defined systems. Unlike conventional modeling, fuzzy rule-based modeling is essentially a multimodel approach in which individual rules are combined to describe the global behavior of the system (Mei, Grossberg, Ng, Navarro, & Ellmore, 2017).
In this paper, we consider a fuzzy large-scale system composed of J subsystems with interconnections and each subsystem is represented by the so-called Takagi-Sugeno fuzzy model. One critical property of control systems is stability and considerable reports have been issued in the literature on the stability problem of fuzzy dynamic systems. However, a literature survey indicates that the stability problem of fuzzy large-scale systems has not yet been resolved. Hence, a stability criterion in terms of Lyapunov's direct method is proposed to guarantee the asymptotic stability of fuzzy large-scale systems.

System Description and Stability Analysis
Consider a fuzzy large-scale system F which consists of J interconnected fuzzy subsystems Lemma 1 (Bohl, 1977): The jth isolated subsystem (2) is asymptotically stable if there exists a common positive definite matrix j P such that ( Based on Lemma 1, a stability criterion is derived below to guarantee the asymptotic stability of the fuzzy large-scale system F. Theorem 1: The fuzzy large-scale system F is asymptotically stable, if each isolated subsystem of F is asymptotically stable and the following inequality is fulfilled (Warsito & Herman, 2018;Wardono, Mariani, & Candra, 2016;Yuanita & Zakaria, 2016;Mulbar & Zaki, 2018;Meika, Suryadi, & Darhim, 2018): where j P is the solution of Eq. (3). Taking the backward difference of V(k), we have From Eqs. (9-10), we have Substituting Eqs. (7-12) into Eq. (6) yields

Conclusions and Suggestions
This paper introduced a practical simulation model for renewable energy in aquaponic systems. The output current has harmonic component of both high order frequencies and dispersed harmonics. The characteristic is more close to the real electric arc furnace property. A flicker testing model is established to test the instantaneous flicker visual sensitivity S. Modulating waves of different frequencies and the same amplitude is introduced to test the correctness of the model. It can help to establish a more practical model to simulate a wide output range of harmonics. It would be more help full for harmonic-preventing sets such as active power filter to test their characteristics. The power system would be more reliable and Electro-insulating material will have a longer using life. The method is proved to be reasonable and realizable to reflect the real electric arc furnace property.
Developing future politics requires simple goals, which are beyond economic development and employment or the protection and environmental protection. The difficulty of the maritime market www.scholink.org/ojs/index.php/ees Energy and Earth Science Vol. 1, No. 1, 2018 shows there are many opportunities to increase the pace of sustainable aquatic life and new perspectives that can be used through political support.

Funding Acknowledgement
This research was in part enlightened by the grant 106EFA0101550 of Ministry of Science and Technology, Taiwan.