Ricardo Pineda

Forecasting Power Output of Solar Photovoltaic System Using Wavelet Transform and Artificial Intelligence Techniques

Abstract With increased penetration of solar as a variable energy resource (VER), solar photovoltaic (PV) power production is rapidly increasing into large-scale power industries. Since power output of PV systems depends critically on the weather, unexpected variations of their power output may increase the operating costs of the power system. Moreover, a major barrier in integrating this VER into the grid is its unpredictability, since steady output cannot be guaranteed at any particular time. This biases power utilities against using PV power since the planning and overall balancing of the grid becomes very challenging. Developing a reliable algorithm that can minimize the errors associated with forecasting the near future PV power generation is extremely beneficial for efficiently integrating VER into the grid. PV power forecasting can play a key role in tackling these challenges. This paper presents one-hour-ahead power output forecasting of a PV system using a combination of wavelet transform (WT) and artificial intelligence (AI) techniques by incorporating the interactions of PV system with solar radiation and temperature data. In the proposed method, the WT is applied to have a significant impact on ill-behaved PV power time-series data, and AI techniques capture the nonlinear PV fluctuation in a better way.

Service Systems Engineering Applications

Abstract The rapid growth in the global service economy has greatly increased research in Service Science and Service Systems Engineering (SSE). In Service Systems practice, the service value chain in terms of links among system entities is defined to co- create value and deliver high quality of service. A Service System is thus defined by its value co-creation chain in which all relevant stakeholders collaborate dynamically in real time or near-real time to deliver high quality service according to the business, service, and customer goals. This paper illustrates how SSE can help define, and discover relationships among Service System entities and addresses the service-oriented, customer-centric, holistic systems view in order to plan, design, adapt or self- adapt to co-create value. Modern service systems, which may be classified as system of systems (SoS), mandate well-defined integration and governance to link service system entities for the real-time dynamic analysis of ever-changing requirements within a Service System. In this paper, SSE concepts and methodologies are applied across various SSE stages to describe an intelligent emergency transportation system and a near real-time dynamic Smart Grid service system. Additionally, issues which need to be addressed within SSE methodologies for global deployment of efficient world-wide service systems are discussed. Finally, future work required for improving current SSE methodologies and help steer research towards achieving global service effectiveness is discussed.

Performance Evaluation of Different Optimization Algorithms for Power Demand Forecasting Applications in a Smart Grid Environment

Abstract This paper presents an in-depth performance evaluation of three different optimization algorithms, in particular genetic algorithm (GA), particle swarm optimization (PSO), and firefly (FF) algorithm for power demand forecasting in a deregulated electricity market and smart grid environments. In this framework, this paper proposes a hybrid intelligent algorithm for power demand forecasts using the combination of wavelet transform (WT) and fuzzy ARTMAP (FA) network that is optimized by using FF optimization algorithm. The effectiveness and accuracy of the proposed hybrid WT+FF+FA model is trained and tested utilizing the data obtained from ISO-NE electricity market.

Model Based Systems Engineering for Smart Grids as Systems of Systems

Abstract This paper presents a System of Systems (SOS) approach to understand, analyze, and design modern energy Smart Grids using Model-Based Systems Engineering (MBSE) methodologies. The concept and definition of a Smart Grid as SOS is presented and Smart Grids are analyzed in the form of detailed architectural artifacts with System Modeling Language (SySML) using industry standards. As part of this research, the design space for Smart Grids was viewed from a logical, behavioral, physical, and techno-economical perspective for the optimal integration of various systems. In summary, this paper uses Methods, Processes, and existing Technologies (MPTs) in systems engineering (SE) and extends them to SOS perspective to help provide an end-to-end life cycle view of a fully functional energy Smart Grid system; in addition, we complement the NIST reference model with an Enterprise layer to address specific enterprise strategies. The paper intends to provide an insight into the methodologies that are involved to realize a functional Smart Grid as a self sustaining energy enterprise and presents the challenges and benefits of achieving the above goal.

Wind power generation impact on electricity price in ERCOT

Texas continues to lead as the top wind power producer in the USA. The Electric Reliability Council of Texas (ERCOT) is an Independent System Operator (ISO), transmission operator and reliability coordinator in Texas. In recent years, numerous policies and incentives to promote renewable energies have been enacted. These policies were very appealing to many states including Texas because of its richness in renewable energy potential. It has been almost a year since ERCOT transitioned from the zonal to nodal market operation. This electricity market has seen significant improvements and consumers are reaping the benefits of lower spot electricity price based on a recent ERCOT report for the first 6 months since the transition took effect. This paper discusses the impact of wind power generation, based on favorable renewable energy policies coupled with the transition from zonal to nodal market, on the electricity price. The analysis performed in this paper indicates that it is very difficult to compute fairly the impact of wind energy on electricity price due to the number of uncertain variables involved and the scale of the problems.

Service Systems Engineering: Emerging Skills and Tools

We are living in a global service economy in which services now make up more than 78% of the US Gross Domestic Product (GDP). This growth in Service has also become a global phenomenon and this has brought much needed attention to Service Science and Service Systems Engineering (SSE). As part of these efforts, this paper proposes the enhancement of existing architectural frameworks for Service Systems. We readily concede that IT is at the heart of Service Systems but we argue existing frameworks need to be expanded to address service systems governance and insertion of technology breakthroughs. A modified NIST framework is illustrated, that includes an Enterprise/Service Management plane to analyze energy Smart Grids as an end-to-end service provider. We also realized the need for integration of tools for the real-time dynamic analysis of ever-changing requirements within a Service System. This concept is illustrated in the form of an internet manufacturing laboratory where design, fabrication, IT, and other supporting tools are integrated to rapidly fabricate complex 3D prototype models. Finally, we discuss issues which need to be addressed for the creation of curricula and professional degree programs in Service Systems Engineering at the graduate level. As a result, we propose a plan for including a Service Systems Engineering specialization track within traditional Systems Engineering programs.

Senior project design success and quality: A systems engineering approach

The capstone project, in most undergraduate engineering programs is the final phase of an academic career. It allows students to take knowledge acquired through the program and apply it to an innovative industry or research project. A well designed senior project affords the student the opportunity to demonstrate the skills and to model the behaviour, which are inherent in the education goals of the program. Most capstone projects focus on technical skills but soft skills oftentimes are not built into the experience. During the past three years we have observed that a significant amount of Sr. Design teams in our Electrical Engineering (EE) department do not complete the projects in a timely manner. We find that lack of technical knowledge is rarely the cause; more often the causes include lack of communication skills, lack of experience in organizing work in a team environment, and a bias towards focusing on the device level at the expense of having a clear, high level end-to-end view of the project. This paper describes our efforts to address these gaps through the incorporation of Systems Engineering disciplines into our undergraduate capstone course in EE and our results so far; thus, leading to more qualitative, competitive and successful projects.

How to generate worst-case scenarios when testing already deployed systems against unexpected situations

Before a system of systems is deployed, it is tested - but it is tested against known operational mission, under several known operational scenarios. Once the system is deployed, new possible unexpected and/or uncertain operational scenarios emerge. It is desirable to develop methodologies to test the system against such scenarios. A possible methodology to test the system would be to generate the worst case scenario that we can think of - to understand, in principle, the behavior of the system. So, we face a question of generating such worst-case scenarios. In this paper, we provide some guidance on how to generate such worst-case scenarios.

Self-Reference as a Principle Indicator of Complexity

Self-reference, the ability of a system to refer to itself, is a necessary condition for complexity, and can indeed form the basis for a definition of complexity. When a part of the system can refer to the whole of the system, there indeed have to be deeper complex structures and processes than those that only superficially appear. Examples of the centrality and essentialness of self-reference to complexity can be found in many fields of study, including mathematics, intelligent networks, and systems engineering processes.