Initialization of a multi-objective evolutionary algorithms knowledge acquisition system for renewable energy power plants

The large-scale renewable energy power plants connected to a weak grid may cause bus voltage fluctuations in the renewable energy power plant and even power grid. Therefore, reactive power compensation is demanded to stabilize the bus voltage and reduce network loss. For this purpose, time-series characteristics of renewable energy power plants are firstly reflected using K-means++ clustering method. The time group behaviors of renewable energy power plants, spatial behaviors of renewable energy generation units, and a time-and-space grouping model of renewable energy power plants are thus established. Then, a mixed-integer optimization method for reactive power compensation in renewable energy power plants is developed based on the second-order cone programming (SOCP). Accordingly, power flow constraints can be simplified to achieve reactive power optimization more efficiently and quickly. Finally, the feasibility and economy for the proposed method are verified by actual renewable energy power plants.

Orthogonal simulated annealing for multiobjective optimization

The energy crisis, global warming, emissions, and greenhouse gas effects have become a global issue and an urgent problem to be resolved. CO2 is One of the contributors to global warming. The operation of fossil energy generation produces CO2 significantly. This paper examines the use of land for renewable energy power plant and the impact. The operation of 648 MW renewable energy power plants can reduce CO2 emissions by 94.78% compared to the coal-fired power plants at the same capacity. However, the construction of renewable energy plants requires a much larger area, which is 44.89 to 78.51 times the land requirement for coal-fired power plants. So, land clearing for renewable energy power plants will result in a much larger loss of land absorption for CO2 emissions compared to coal-fired power plants. The use of plantation land can reduce CO2 emissions due to the total operation and clearing of land of 4,444,907.97 tons/year up to 4,452,016.56 tons/year compared to the construction of the coal-fired power plant, at the same capacity. The use of plantation land for the construction of renewable energy power plant reduces the impact of CO2 emissions by up to 95.39% compared to the construction and operation of the coal-fired power plants.

This paper presents a scheme of distance protection for a renewable energy plant in electric power distribution systems. In many developing countries where renewable energy power plants are typically located in rural remote areas, they must be connected to weak power distribution systems inevitably. Although over-current relays are used to protect feeders at substations, fuses are only available elsewhere along feeder lines. To secure the system operation, distance protection is assigned to protect feeders. In this paper, distance relays are placed in the feeder along with over-current relays and fuses. Design of the distance protection of multi-source systems is described. This study considered the system consisting of a renewable energy plant. The power plant was a 6-MW unit of firmed power generation. The test feeder was simplified to be an equivalent four-bus test feeder for relaying purpose. Fault analysis in this paper was performed by using PowerWorld™ software. Obtained fault currents were used to establish protective zones of distance relays. In addition, this paper also compared the result of using distance protection with those of using directional over-current protection. As a result, protection of the power feeder with renewable power plants by using distance relaying can reduce complication in relay setting due to the impedance-based setting of the distance relay.

Due to global warming problems and increasing environmental pollution, there is a strong tendency to install and apply renewable energy power plants (REPPs) around the world. On the other hand, with the increasing development of information and communication technology (ICT) infrastructures, power systems are using these infrastructures to act as smart grids. In fact, future modern power systems should be considered as smart grids with many small and large scale REPPs. One of the main problems and challenges of the REPPs is uncertainty and fluctuation of electrical power generation. Accordingly, a suitable solution can be combination of different types of REPPs. So, the penetration rate of large-scale wind-PV farms (LWPF) is expected to increase sharply in the coming years. Given that the LWPFs are added to the grid or will replace fossil fuel power plants, they should be able to play the important roles of synchronous generators such as power low-frequency oscillation (LFO) damping. In this paper, an LFO damping system is suggested for a LWPF, based on a phasor measurement unit (PMU)-based fractional-order proportional–integral–derivative (FOPID) controller with wide range of stability area and proper robustness to many power system uncertainties. Finally, the performance of the proposed method is evaluated under different operating conditions in a benchmark smart system.

To reduce the financial burden brought by the feed-in tariff (FIT) policy, China is shifting its renewable energy support policy to the renewable portfolio standard with tradable green certificates (RPS/TGC). Moreover, the two policies are being implemented in parallel in the transitional period. In this context, this study investigates the game between renewable energy power plants (REPPs) regarding electricity outputs and tradable green certificate (TGC) prices under different renewable energy support policies practiced in China. We focus on analyzing the impact of policy changes on the competing REPPs’ decisions and the renewable electricity market with TGCs. The results show that implementing the RPS/TGC policy inhibits the development of renewable electricity unless the subscription of TGCs is promoted. Government subsidy arrears significantly affect electricity outputs and TGC subscriptions. The low subscription rate of TGCs is caused not by the subsidy-based TGC pricing mechanism but by government subsidies. This suggests that the government should implement the RPS/TGC policy, and demand-side power consumption responsibility weights should also be strengthened to promote TGC subscriptions.

Government power plants cannot supply all electricity demand in East Kalimantan Province especially if there is damage to the power plant with the largest production capacity, so cooperation with other suppliers needs to be done. There are four stakeholders that can supply electricity, namely State Electricity Company (SEC), Independent Power Producer (IPP), Rent, and Excess Capacity (EC). Each supplier has different power generation characteristics that lead to differences in fuel costs and emissions. This research proposes 4 mathematical models. The models are scenarios 4 forms of cooperation between electrical stakeholders in East Kalimantan taking into consideration the potential of renewable energy (RE) power plants. This mathematical model is solved with a heuristic algorithm solver excel. The result, the best scenario by integrating three power plants owned by SEC, IPP and RE. Whereas collaboration with the smallest emissions is SEC + Rent + RE.

Distributed parallel cooperative coevolutionary multi-objective large-scale immune algorithm for deployment of wireless sensor networks

At the end of 2012 and the beginning of 2013, the Serbian Government issued the new national regulations in order to provide an acceptable legislation framework to achieve 2020 targets of 27% increase of total renewable energy sources share in the gross final energy consumption, relative to 2009. The target of a 37% increase relates to participation of renewable energy sources in electricity production. It requires construction of new significant capacities of renewable energy power plants as clearly defined in the National Action Plan for Renewable Energy Sources. This paper comprises critical analyses of targeted new installed capacity of renewable energy power plants for electricity production from different point of views, such as: new national energy policy, new national regulations, renewable energy sources potential in Serbia, efficiency of power plants and the investment financial models. According to the new national energy policy identified in the National Action Plan for Renewable Energy Sources, it is concluded that the new regulations related to the construction of new renewable energy power plants is completed, particularly concerning the investment security, provision of green electricity market, status of green electricity producer, and significant reduction of time for administrative procedures required to obtain a building permit. Particularly, the real wind potential in Serbia, based on the measured data over the past ten years of measurement campaigns at more than thirty locations, has been used to correct the targeted installed capacity of wind power plants.

Efficient design and management of water distribution networks is critical for conservation of water resources and minimization of both energy requirements and maintenance costs. Several computational routines have been proposed for the optimization of operational parameters that govern such networks. In particular, multi-objective evolutionary algorithms have proven to be useful both properly describing a network and optimizing its performance. Despite these computational advances, practical implementation of multi-objective optimization algorithms for water networks is an abstruse subject for researchers and engineers, particularly since efficient coupling between multi-objective algorithms and the hydraulic network model is required. Further, even if the coupling is successfully implemented, selecting the proper set of multi-objective algorithms for a given network, and addressing the quality of the obtained results (i.e., the approximate Pareto frontier) introduces additional complexities that further hinder the practical application of these algorithms. Here, we present an open-source project that couples the EPANET hydraulic network model with the jMetal framework for multi-objective optimization, allowing flexible implementation and comparison of different metaheuristic optimization algorithms through statistical quality assessment. Advantages of this project are discussed by comparing the performance of different multi-objective algorithms (i.e., NSGA-II, SPEA2, SMPSO) on case study water pump networks available in the literature.

The environmental/economic dispatch (EED) problem, as one of the most important optimization problems in power systems operations, is a highly constrained, nonlinear, multiobjective optimization problem. Multiobjective evolutionary algorithms have become effective tools for solving the EED problem. To obtain higher quality Pareto solutions for EED as well as further improve the uniformity and diversity of the Pareto set, this paper proposes a novel multiobjective evolutionary algorithm, namely multiobjective grey prediction evolution algorithm (MOGPEA). The MOGPEA first develops a novel grey prediction evolution algorithm (GPEA) based on the even grey model (EGM(1,1)). Unlike other evolutionary algorithms, the GPEA considers the population series of evolutionary algorithms as a time series and uses the EGM(1,1) model to construct an exponential function as a reproduction operator for obtaining offspring. In addition, the MOGPEA adopts two learning strategies to improve the uniformity and diversity of the Pareto optimal solutions of the EED. One is a leader-updating strategy based on the maximum distance of each solution in an external archive, and the other is a leader-guiding strategy based on one solution of each external archive. To validate the effectiveness of the MOGPEA, a standard IEEE 30-bus 6-generator test system (with/without considering losses) is studied with fuel cost and emission as two conflicting objectives to be simultaneously optimized. The experimental results are compared with those obtained using a number of algorithms reported in the literature. The results reveal that the MOGPEA generates superior Pareto optimal solutions of the multiobjective EED problem. Matlab_Codes of this article can be found in https://github.com/Zhongbo-Hu/Prediction-Evolutionary-Algorithm-HOMEPAGE.

Over the past 10 years, in most countries of Europe, North America and China, renewable energy grid integration technical standards are mostly developed by some electricity association or power grid companies. However, with the increasing scale of renewable energy generation and gradually intensified impact on the power grid, more countries confirm the legitimacy of renewable energy grid integration provisions through the legislation in national level. Due to the difference in the power source structure, load characteristics, power grid situation, and other specific circumstances in different countries or regions, grid code of renewable energy integration in different countries are not identical. However, these technical standards have some common focuses. They all stressed that the renewable energy power plants must have a certain active power control, reactive power / voltage control and fault ride through capability as well as the ability to withstand the power system voltage and frequency deviation. Some of the standards require the renewable energy power plants to provide model information, operating parameters and grid integration performance testing reports. This paper provides an introduction about common focus on technical standards of renewable energy grid integration, and tries to explore potential challenge caused by RE grid integration.

The conventional power grids and its components are being replaced with smart generation, transmission and protection metering systems as a result of advancement in the technology. The new generation networks consist of distributed generation units, microgrids, renewable energy power plants and smart communication technologies. The integration of such system elements presents new requirements for reliable and efficient network design. Necessary analysis and calculations have to be performed to ensure that the implemented microgrids will not present any drawback on the existing network after the optimal design of the renewable energy power plants which are foreseen as the key elements of the campus network equipped with microgrids. The effect of microgrids equipped with solar power plants (SPPs) are investigated considering day time variation of solar radiation along with the variable charging duration and power consumption of electric vehicle (EV) charging stations. The grid integrated campus microgrid with variable daytime operation sequences of SPP and EV charging stations are investigated considering optimal sizing and operation criteria. The major outcome of the study is the observation of the microgrid integration response of a conventional grid along with the effect of dynamic consumption characteristics of the EV charging stations.

The Ministry of the Environment of Japan has promoted the demonstration project named “wide-area operation systems for multiple renewable energy power plants”. The purpose of wide-area operation system is to stabilize the total generation output of photovoltaic (PV) power plants and wind farms using energy storage systems (ESSs) and a controllable renewable energy (RE) generator based on the weather forecasts and online synchronized generation output monitoring. In this paper, detailed control strategy for ESSs and a controllable RE generator is proposed considering the energy/power ratios. The efficacy of proposed control strategy is ascertained through chronological computation simulations using actual observed and forecasted solar irradiance data at Wakkanai PV power plant.

The increased number of renewable power plants pose threat to system balance. Their intermittent nature makes it very difficult to predict power output thus either additional reserve power plants are required or new storage and control technologies incorporated. Traditional spinning reserve cannot fully compensate sudden changes in renewable energy power plants. A feasible approach to balance the variation in power and voltage (within seconds) is using new storage technologies such as flow batteries. This paper covers the use of flow batteries and hydro power plant to help wind power plants reach near perfect balance i.e. make the total power output as predicted. It investigates the possibility of such technology to take part in the balance of the Lithuanian power system. A dynamic model of flow battery is demonstrated that evaluates the main parameters of it - power, energy, reaction time and efficiency. A range of hydro power plant reaction times are tested in order to find the required battery size. The research and study cases show that power and energy of a reasonable size flow battery is sufficient to correct the load and wind power imbalance.