The optimal power flow with stochastic wind and solar energy is formulated as a multi-objective optimization problem. A multi-objective evolutionary algorithm based on non-dominated sorting with constraint handling technique are presented to solve it.
This study presents a multi-objective solving indicator-based evolutionary algorithm (IBEA) to solve the optimal power flow (OPF) problem with multiple and competing objectives. The objective functions for the multi-objective OPF (MOOPF) are active power loss, aggregate voltage deviation, total generation cost, and emission pollution.
To verify this, as shown in Eq. (45), we control the emphasis on the cost of wind/PV power in the economic objective by adding a parameter η ∈ [0, + ∞) to (18).
Provided by the Springer Nature SharedIt content-sharing initiative In this paper, the multi-objective optimal power flow (MOOPF) problem optimization objectives focus on four optimization objectives: generation cost, emission, real power loss and voltage deviation (VD).
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During operation, wind turbine systems are affected by external wind speed disturbances and the dynamic coupling of the system, which can lead to significant resonance …
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Classical OPF problems consider only thermal power generation based on the fossil fuels and only the generation cost as the optimization objective is taken into consideration …
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In addition, both systems have significant solar generation and retain the hydro-wind power plant generation system. However, there has been a considerable increase in its …
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Hydropower compensating for wind and solar power is an efficient approach to overcoming challenges in the integration of sustainable energy. Our study proposes a multi …
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This study presents a multi-objective solving indicator-based evolutionary algorithm (IBEA) to solve the optimal power flow (OPF) problem with multiple and competing …
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The above literature review reveals the following: (i) Most of the authors designed the OPF problem as single-objective optimization. In real time, multiple objectives play a key …
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In this paper, the multi-objective optimal power flow (MOOPF) problem optimization objectives focus on four optimization objectives: generation cost, emission, real power loss …
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This paper details the role of MPC technology in multi-level and multi-objective control within the wind power sector, aiming to help engineers and scientists understand its …
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Multi-energy complementary generation systems are usually responsible for tasks such as maximizing power generation benefits and ensuring system stability and their …
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Inspired by the concept of wind power integrated power system for optimizing multiple objectives, this work proposes a novel real-time MO-OPF framework for wind farm …
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Hydropower compensating for wind and solar power is an efficient approach to overcoming challenges in the integration of sustainable energy. Our study proposes a multi …
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The share of installed capacity and power generation capacity of renewable energy in the constructed system, as well as the installed capacity of wind power and solar PV, are all …
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A general framework for multi-objective optimization using this simulation technique is proposed for solar–wind hybrid system, considering the feed-in tariff regulations, …
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This paper proposes a method that combines meta reinforcement learning with multi-agent reinforcement learning to solve the multi-objective two-stage robust optimization of …
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