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Open Access Regular Paper Issue
Formulation of Locational Marginal Electricity-carbon Price in Power Systems
CSEE Journal of Power and Energy Systems 2023, 9 (5): 1968-1972
Published: 12 October 2022
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Decarbonisation of power systems is essential for realising carbon neutrality, in which the economic cost caused by carbon needs to be qualified. Based on the formulation of locational marginal price (LMP), this paper proposes a locational marginal electricity-carbon price (EC-LMP) model to reveal carbon-related costs caused by power consumers. A carbon-price-integrated optimal power flow (C-OPF) is then developed to maximise economic efficiency of the power system considering the costs of electricity and carbon. Case studies are presented to demonstrate the new formulation and results demonstrate the efficacy of the EC-LMP-based C-OPF on decarbonisation and economy.

Open Access Issue
Data-driven Optimal Dynamic Dispatch for Hydro-PV-PHS Integrated Power Systems Using Deep Reinforcement Learning Approach
CSEE Journal of Power and Energy Systems 2023, 9 (3): 846-858
Published: 18 August 2022
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To utilize electricity in a clean and integrated manner, a zero-carbon hydro-photovoltaic (PV)-pumped hydro storage (PHS) integrated power system is studied, considering the uncertainties of PV and load demand. It is a challenge for operators to develop a dynamic dispatch mechanism for such a system, and traditional dispatch methods are difficult to adapt to random changes in the actual environment. Therefore, this study proposes a real-time dynamic dispatch strategy considering economic operation and complementary regulatory ability. First, the dynamic dispatch of a hydro-PV-PHS integrated power system is presented as a multi-objective optimization problem and the weight factor between different goals is effectively calculated using information entropy. Afterwards, the dispatch model is converted into the Markov decision process, where the dynamic dispatch decision is formulated as a reinforcement learning framework. Then, a deep deterministic policy gradient (DDPG) is deployed towards the online decision for dispatch in continuous action spaces. Finally, a case study is applied to evaluate the performance of the proposed method based on a real hydro-PV-PHS integrated power system in China. Simulations show that the system agent reduces the power volatility of supply by 26.7% after hydropower regulating and further relieves power fluctuation at the point of common coupling (PCC) to the upper-level grid by 3.28% after PHS participation. The comparison results verify the effectiveness of the proposed method.

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