Performance analysis and multi-objective optimization of the offshore renewable energy powered integrated energy supply system

Because of the problems of low operation efficiency and poor energy management of multienergy input and output system with complex load demand and energy supply, this paper uses the double-layer nondominated sorting genetic algorithm to optimize the multienergy complementary microgrid system in real-time, allocating reasonably the output of each energy supply end and reducing the energy consumption of the system on the premise of meeting the demand of cooling, thermal and power load, so as to improve the economy of the whole system. According to the system load demand and operation mode, the first layer of this double-layer operation strategy calculates the power required by each node of the microgrid system to reduce the system loss. The second layer calculates the output of each equipment by using nondominated sorting genetic algorithm with various energy values calculated in the first layer as constraint conditions, considering the operation characteristics of various equipment and aiming at economy and environmental protection. In this paper, a typical model of energy input-output is established. This model combines with the operation control strategy suitable for multienergy complementary microgrid system, considers the operation mode and equipment characteristics of the system, and uses a double-layer nondominated sorting genetic algorithm to optimize the operation of each equipment in the multienergy complementary system in real time, so as to reduce the operation cost of the system.

The multi-energy complementary system can meet the increasingly abundant and diversified energy consumption needs of users and, at the same time, help to improve energy utilization efficiency, reduce environmental pollution, and optimize the balance of energy supply and demand. In this paper, a multi-energy complementary cogeneration system with a gas turbine distributed photovoltaic, gas boiler, and heat storage tank is proposed, and the operation scheduling optimization model of the system is constructed. Aiming to minimize the comprehensive cost of economy and carbon emission, the model adopts a linear programming method to optimize the operation scheduling of multi-energy complementary systems. Taking a multi-energy complementary cogeneration system as an example, the key equipment of the system is optimized under three different scenarios with different time-of-use prices, and the influence of time division of time-of-use electricity price on the comprehensive cost of the system is analyzed. The results show that the time division method, which is more in line with the system net load curve, can effectively reduce the comprehensive cost of the complementary system and increase the consumption space of new energy.

Organic Rankine Cycle (ORC) applications include ocean thermal energy conversion (OTEC), in which mechanical work is generated from heat energy to rotate generators and generate electricity. The OTEC system heated and cooled its refrigerant by taking advantage of the relatively small temperature difference between the warmer surface seawater and the colder deep seawater. The low-temperature difference between seawater and the rest of the system meant that the thermal efficiency of the system was relatively low; to address this problem, the OTEC cycles needed to be revised. To increase the basic OTEC cycle's thermal efficiency by 3.3–4.0%, various modifications have been developed. Two such cycles are the Solar Boosted OTEC (SOTEC) cycle and the Ejector Pump cycle (EP-OTEC). While the two improvements alter the rotating turbine parameters in different ways, they can be combined to create an improved OTEC cycle through the use of thermodynamics. In this study, an algorithm for revised OTEC was developed using MATLAB, and the performance of the system after the modifications was further quantified. This SEP-OTEC cycle thermal efficiency gives a 1.2-fold improvement when compared to the previous OTEC cycle thermal efficiency, which was 3.1%.

As the main body of energy supply, the park needs to integrate various energy sources such as electric power, fossil energy, and thermal energy in the regional system. The integrated energy system is an important means to achieve "multiple energy complementarity and coordinated development of source, grid, storage, and storage" in the industrial park. This paper explores the external development environment of multi-energy complementarity in the park and the current status of domestic and foreign pilots, and provides a reference for my country's extensive implementation of the multi-energy complementarity system in the park. Taking the park's multi-energy complementary system as an object, analyze the development status of the park's multi-energy complementary system, and carry out analysis of the operating characteristics of the park's multi-energy complementary system, specifically from the analysis of operating scenarios and clarify the park under the multi-condition coupling of operation mode, capacity configuration and user type Analyze and discuss several aspects of the operating scenario. This article puts forward the function of implementing multi-energy complementary system in the park, and establishes the basic operation mechanism of the multi-energy complementary system in the park, which lays a theoretical foundation for the in-depth study of the multi-energy complementary system in the park to participate in the integration of clean energy.

With increasing scale of renewable energy integrated into the power system, the power system needs more flexible regulating resources. At present, besides traditional thermal and hydro power plants, pumped hydro storage and battery storage are the most commonly used resources, and they form a wind-thermal-hydro-storage multi-energy complementary system. This paper proposes an optimal scheduling strategy to dispatch the resources in the multi-energy complementary system. First, models of diverse types of resources. i.e., hydro power, pumped hydro storage, and battery storage, are established. Then, a day-ahead optimization scheduling model is proposed for the multi-energy complementary system. Finally, case study is conducted on a revised IEEE 30 node system. Simulation results demonstrate that the proposed method can fully utilize the characteristics of different kinds of power resources to consume renewable energy and enhance the safety and economy of the multi-energy complementary system.

Demand response is an effective way to alleviate the gap between energy supply and demand and enhance energy utilization efficiency. It is of great significance to promote the sustainable development of multi-energy complementary systems. Firstly, a demand response model based on demand elasticity matrix is constructed for a multi-energy complementary system. With the consideration of uncertainty of clean energy output, a two-level coordinated operation optimization model of the multi-energy complementary system is constructed, where the upper layer considers the overall benefit of the multi-energy complementary system, and the lower layer focuses on the benefit of the internal generation side. A two-stage solution algorithm composed of "clean energy uncertainty processing - optimization model processing based on genetic algorithm" was adopted to carry out multi-scenario simulation example analysis.

Constructing multi-energy complementary system is a promising way to promote the utilization of renewable energy. This paper proposes a novel method based on time series simulation technology to optimize capacity of battery energy storage system in the multi-energy complementary system with wind power, photovoltaic and concentrating solar power. An optimization model is established to maximize the equivalent uniform annual profit of the system with considering operation constraints of power plants and renewable energy curtailment rate. To make full use of complementary characteristics of the renewable energy, the power rating and battery storage capacity are then optimized coordinately based on hourly wind and solar power outputs in a year. Case studies are conducted on a multi-energy complementary system of China with wind power, photovoltaic, concentrating solar power and battery. Optimization results indicate that the proposed method can fully utilize the complementary characteristics and provide the optimal battery capacities. Sensitivity analyses also show that the proposed method can obtain the threshold of generation price for the project. Overall, the testing results verify the effectiveness and applicability of the proposed method.

The ocean thermal energy is abundant. The global total is about 40 billion kW. The ocean thermal energy conversion (OTEC) is clean and renewable, the power generation is stable, and the energy storage has high capacity. Active exploitation of ocean thermal energy resources is of great significance to realize the strategy of maritime power. In view of the efficiency limit of a traditional OTEC, authors propose an approach of a multi-energy complementary OTEC system that they can improve the efficiency of this system. The approach sets parameters at the system level and integrates solar energy, wind energy, energy storage and OTEC. For example, a 1MW integrated power generation system is designed and simulated by means of computer aided design and of conducting a model-based simulation, respectively. The efficiency of the complementary OTEC system with solar heating can reach 13.12%. In this article, the basic principle and working process of the approach are analyzed, and the system efficiency is calculated. The results show that, in comparison to the traditional OTEC, the complementary system of OTEC can improve the ratio of power generation output efficiency, stability and ocean energy utilization.

With the gradual expansion of the development scale of wind power and photovoltaic (PV) power plants, the multi-energy complementary power generation system, typically represented by hydro-PV/hydro-wind/hydro-wind-PV, has become an important part of modern power systems. Aiming at the joint operation of the cascaded hydropower stations after wind-PV grid connection, a medium- and long-term implicit stochastic joint dispatching function model for wind-PV-cascaded hydropower stations based on the SVM(support vector machine) method is developed in this paper, which selects the final water levels of the reservoirs as the dependent variables, and the initial water levels of the reservoirs, the reservoir inflow, the interval inflow as well as the wind and PV output are independent variables. First, the optimization of main parameters C (Penalty coefficient), g (Kernel function parameter) and p (Insensitive loss coefficient) of the model are achieved by particle swarm algorithm. The Gaussian radial basis function is then used to fit the scheduling function proposed in this paper. Finally, the rolling simulation calculation and correction of the obtained scheduling function are realized by C# programming language of VS2017 platform. The results show that the proposed scheduling function is an effective method for scheduling decision-making, and the revised water level process, output process as well as annual electricity production of the scheduling model are not significantly different from the optimal scheduling results. Moreover, the simulation results conform to the existing scheduling rules, which has shown it can be used to inform the operation of cascaded hydropower stations under the multi-energy complementary system.

Existing methods cannot accurately establish the joint output probabilistic model of the Wind-PV-CSP multi-energy complementary generation system. Therefore, based on the analysis of the correlation and complementarity among wind power, PV, and CSP output, a method of establishing the joint output probability model of Wind-PV-CSP multi-energy complementary system by using Copula theory and Gaussian mixture model is proposed. Considering the operational history data of wind power, PV, and CSP, the Copula function based on the correlation between PV and CSP output is adopted to establish the probabilistic model of CSP-PV combined output. Moreover, the probabilistic model for the joint output of PV-wind power generation is set up using the mixed Gaussian model based on the complementarity of wind power and PV output. Subsequently, based on the probabilistic models for the combined outputs of wind power-PV and CSP-PV, the probabilistic model for the combined output of wind power-PV-CSP mixed Gaussian model was established. Moreover, three evaluation metrics-the Nash efficiency coefficient (NSE), root mean square error (RMSE), and Euclid coefficient, are used to judge the quality of the model. The operational history data of CSP-PV-wind power in Jiuquan high proportion renewable energy base is taken as examples; the simulation results verify the validity and usability of the proposed method.

Sustainable development is an inevitable choice for the development of human society, and energy is closely related to sustainable development. Improving energy structure, increasing energy efficiency, and vigorously developing renewable energy are of great significance to the sustainable development of rural areas. Moreover, the establishment of a distributed multi-energy complementary system (MECS) using abundant renewable energy such as wind, solar, and biomass energy is an effective way to solve the rapid growth of rural power demand, weak rural power grids, and rural environmental pollution. This paper proposes a new type of Wind–Solar–Biomass–Storage MECS composed of wind power generation (WPG), photovoltaic power generation (PVG), biogas power generation (BPG) and energy storage system (ESS) and establishes a MECS optimization operation model with the goal of maximizing daily operating economic benefits, considering the characteristics of each power generation system and power demand characteristics. By using the multi-population genetic algorithm (MPGA), the simulation experiments of the MECS operation under four typical weather scenarios are carried out. The results show that the MECS can operate stably in different scenarios and achieve the goal of maximizing economic benefits, which verifies the feasibility of the MECS model. In addition, the simulation results are compared with the standard genetic algorithm (SGA), which shows the effectiveness of the optimization method. This paper takes Chinese rural areas as an example for research. The proposed MECS and optimal operation model are also applicable to developing countries with a high proportion of the rural population.

Coupling geospatial suitability simulation and life cycle carbon emissions towards uncertain optimization planning for wind-photovoltaic-hydrogen multi-energy complementary system

The multi-energy complementary distributed energy system (MCDES) covers a variety of energy forms, involves complex operation modes, and contains a wealth of control equipment and coupling links. It can realize the complementary and efficient use of different types of energy, which is the basic component of the physical layer of the Energy Internet. In this paper, aiming at the demand of the energy application for towns, a distributed energy system based on multi-energy complementary is constructed. Firstly, the supply condition of the distributed energy for the demonstration project is analyzed, and the architecture of the multi-energy complementary distributed energy system is established. Then the regulation strategy of the multi-energy complementary distributed energy system is proposed. Finally, an overall system scheme for the multi-energy complementary distributed energy system suitable for towns is developed, which provides a solid foundation for the development and promotion of the multi-energy complementary distributed energy system.

Optimal design of multi-energy complementary power generation system considering fossil energy scarcity coefficient under uncertainty

Design optimization and uncertainty analysis of multi-energy complementary system for residential building in isolated area