Application of Optimization to Sizing Renewable Energy Systems and Energy Management in Microgrids: State of the Art and Trends

Application of Optimization to Sizing Renewable Energy Systems and Energy Management in Microgrids: State of the Art and Trends

Khaled Dassa (University of Boumerdes, Algeria) and Abdelmadjid Recioui (University of Boumerdes, Algeria)
DOI: 10.4018/978-1-7998-8561-0.ch005
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Abstract

The smart grid is the aggregation of emerging technologies in both hardware and software along with practices to make the existing power grid more reliable and ultimately more beneficial to consumers. The smart grid concept is associated with the production of electricity from renewable energy sources (RES). For the distant isolated regions, microgrids (MG) with RES are offering a suitable solution for remote and isolated region electrification. The improper sizing would lead to huge investment cost which could have been avoided. The objective of this chapter is to review the state-of-the-art studies on the use of optimization techniques to renewable energy design and sizing. The chapter reviews the optimization techniques employed at different components of the microgrid including the energy sources, storage elements, and converters/inverters with their control systems.
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Introduction

The traditional power grid is made up of synchronous machines, power transformers, transmission lines, transmission substations, distribution lines, distribution substations, and various types of loads that are interconnected altogether. They are located far from the power consumption area and electric power is transmitted through long transmission lines. Traditional power grids have served us for decades because they are predictable and reliable however, Due to the growing concern about the climate change caused by greenhouse gas emissions and the escalating increase in electricity demand (2% per year until 2040) which exceeds the demand for any other form of final energy globally, there is a tendency to replace fossil fuels by renewable sources such as wind and solar (Baimel et al., 2016). Figure 1 shows the growth of renewable energy penetration into total energy generation over next three decades across the world. The Europe will take the maximum share of 44% of renewable generation in their total energy production (Ramesh Babu, 2017).

Figure 1.

Percentage growth forecast in renewable energy generation

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Built on top of an intelligent communications infrastructure, the smart grid is a combination of hardware, management, and reporting software. Consumers and utility corporations alike have capabilities to manage, monitor, and respond to energy challenges in the smart grid era. The transfer of electricity from the utility to the consumer becomes a two-way conversation, saving consumers money and energy while also providing greater transparency in terms of end-user usage and lowering carbon emissions. (Ramesh Babu, 2017).

A smart grid is an electricity network monitors and manages the delivery of power from all generation sources to satisfy the variable electricity demands of end-users using digital and other modern technology. Smart grids coordinate the demands and capacities of all generators, grid operators, end-users, and electrical market stakeholders to run the system as efficiently as possible, reducing costs and environmental consequences while maximizing system reliability, resilience, and stability. (Kingsley, Shongwe, & Joseph, 2018).

Figure 2.

Smart grid illustration diagram

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There are a lot of advantages from setting up Smart Grids (Ekanayaka, J. et al., 2012; Momoh J., 2012; Bayindir, R. et al., 2016). These include the following:

Technical Advantages

The complete implementation of Smart Grid would result in a number of technical advantages, including:

  • Increased energy efficiency: This is accomplished through loss reduction, peak shaving (demand control), AMI adoption, and automated energy system operation.

  • Increased grid reliability: This is accomplished by minimizing the frequency and duration of power outages.

  • Increased operational efficiency: Achieved through active control, automation, and management services in distribution grids, as well as customer empowerment via home automation and smart appliance use.

  • Enhanced security and safety: Enhanced security can be achieved through the use of sensors and automated operations.

Key Terms in this Chapter

Smart Grid: A smart grid is an electricity network that uses digital and other advanced technologies to monitor and manage the transport of electricity from all generation sources to meet the varying electricity demands of end-users.

Evolutionary Optimization: An evolutionary algorithm is a population-based optimization algorithm that uses mechanisms inspired by biological evolution, such as reproduction, mutation, recombination, and selection. Evolution of the population then takes place after the repeated application of the previous mechanisms.

Microgrid: A microgrid is a decentralized group of electricity sources and loads that is able to disconnect from the interconnected grid and to function autonomously. Microgrids improve the security of supply within the microgrid cell, and can supply emergency power, changing between autonomous and connected modes.

Metaheuristics: A metaheuristic is a higher-level procedure to find, generate, or select a sufficiently good solution to an optimization problem. Metaheuristics require a few assumptions about the optimization problem being solved and so may be usable for a variety of problems.

Optimization: Optimization is the process of choosing the best element from a set of available alternatives under some constraints. This process amounts to minimizing or maximizing the objective or cost function of the problem.

Renewable Energy Sources: Renewable energy sources are natural resources which will replace the portion depleted by usage and consumption. Common sources of renewable energy include solar, geothermal and wind power.

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