With the large-scale development of Chinese electric power, the contradiction of China’s energy supply and demand that reverse distributed is very prominent, therefore, promoting electricity trading is one of the imp...With the large-scale development of Chinese electric power, the contradiction of China’s energy supply and demand that reverse distributed is very prominent, therefore, promoting electricity trading is one of the important measures to get optimized configuration of energy resources in nationwide. For the two kinds of trading method, the “power point to the grid” trading and the “grid to grid” trading, this paper designed pricing mechanism model, and took one area as an example, we analyzed the impact of the participants by using different pricing mechanism, and put forward reasonable policy proposals for China’s pricing mechanism of trans-regional and trans-provincial electricity trading.展开更多
The randomness and uncertainty of renewable energy generation are expected to significantly change the optimal decision-making of trans-provincial electricity market subjects.Therefore,it is beneficial to optimize the...The randomness and uncertainty of renewable energy generation are expected to significantly change the optimal decision-making of trans-provincial electricity market subjects.Therefore,it is beneficial to optimize the interests of each of these subjects,considering the unpredictable risks of renewable energy under the renewable portfolio standards(RPS)and researching their effects on the optimal decision-making of transprovincial electricity market multi-subjects.First,we develop a trans-provincial trading market mechanism for renewable energy and clarify the electricity supply and demand relation and the green certificates supply and demand relation of trans-provincial electricitymarketmulti-subjects.Then,under the RPS,we construct a multi-subject game model of the power supply chain that recognizes the risks,and adopt the reverse induction method to discuss the optimum risk-taking judgment of each subject in the trans-provincial electricity market.Finally,we useMATLAB to verify the viability and efficacy of the proposed gamemodel,and obtain a certain reference value for the optimal decision-making of trans-provincial electricity market subjects.In summary,we consider the uncertainty risks of renewable energy under RPS,study the effects of the green certificate price and risk aversion coefficient in the RPS mechanism on the optimal decisionmaking of trans-provincial electricity market subjects,and obtain the changing trends of two different power products and those of different electricity market subjects under the influence of the green certificate price and risk aversion coefficient,which have a certain reference value for studying the factors affecting the optimal decision-making of trans-provincial electricity market subjects.展开更多
In this paper a novel cost function based on the relationship between operation cost of unit and generation load rate is employed in an agent-based model of Trans-provincial Centralized Bidding Trading Market of East ...In this paper a novel cost function based on the relationship between operation cost of unit and generation load rate is employed in an agent-based model of Trans-provincial Centralized Bidding Trading Market of East China Grid. Simulation results are compared to real data to prove that the model is correct. Further analysis on simulation results point out the way to achieve an all-win game for power market members: generation companies improve their average load rates of the units by selling their electricity in the market, which makes units' cost drop and settlement price stay lower than benchmark price. Consequently electricity-demand provinces saved expenses, and units increase their profits. In conclusion, the trans-provincial electricity market of East China Power Grid is a successive case which improves the efficiency of the electricity industry by market-oriented measures.展开更多
The option of organizing E-auctions to purchase electricity required for anticipated peak load period is a new one for utility companies.To meet the extra demand load,we develop electricity combinatorial reverse aucti...The option of organizing E-auctions to purchase electricity required for anticipated peak load period is a new one for utility companies.To meet the extra demand load,we develop electricity combinatorial reverse auction(CRA)for the purpose of procuring power from diverse energy sources.In this new,smart electricity market,suppliers of different scales can participate,and homeowners may even take an active role.In our CRA,an item,which is subject to several trading constraints,denotes a time slot that has two conflicting attributes,electricity quantity and price.To secure electricity,we design our auction with two bidding rounds:round one is exclusively for variable energy,and round two allows storage and nonintermittent renewable energy to bid on the remaining items.Our electricity auction leads to a complex winner determination(WD)task that we represent as a resource procurement optimization problem.We solve this problem using multi-objective genetic algorithms in order to find the trade-off solution that best lowers the price and increases the quantity.This solution consists of multiple winning suppliers,their prices,quantities and schedules.We validate our WD approach based on large-scale simulated datasets.We first assess the time-efficiency of our WD method,and we then compare it to well-known heuristic and exact WD techniques.In order to gain an exact idea about the accuracy of WD,we implement two famous exact algorithms for our constrained combinatorial procurement problem.展开更多
文摘With the large-scale development of Chinese electric power, the contradiction of China’s energy supply and demand that reverse distributed is very prominent, therefore, promoting electricity trading is one of the important measures to get optimized configuration of energy resources in nationwide. For the two kinds of trading method, the “power point to the grid” trading and the “grid to grid” trading, this paper designed pricing mechanism model, and took one area as an example, we analyzed the impact of the participants by using different pricing mechanism, and put forward reasonable policy proposals for China’s pricing mechanism of trans-regional and trans-provincial electricity trading.
基金This work was supported by Project of Philosophy and Social Science Foundation of Shanghai,China(Grant No.2020BGL011).
文摘The randomness and uncertainty of renewable energy generation are expected to significantly change the optimal decision-making of trans-provincial electricity market subjects.Therefore,it is beneficial to optimize the interests of each of these subjects,considering the unpredictable risks of renewable energy under the renewable portfolio standards(RPS)and researching their effects on the optimal decision-making of transprovincial electricity market multi-subjects.First,we develop a trans-provincial trading market mechanism for renewable energy and clarify the electricity supply and demand relation and the green certificates supply and demand relation of trans-provincial electricitymarketmulti-subjects.Then,under the RPS,we construct a multi-subject game model of the power supply chain that recognizes the risks,and adopt the reverse induction method to discuss the optimum risk-taking judgment of each subject in the trans-provincial electricity market.Finally,we useMATLAB to verify the viability and efficacy of the proposed gamemodel,and obtain a certain reference value for the optimal decision-making of trans-provincial electricity market subjects.In summary,we consider the uncertainty risks of renewable energy under RPS,study the effects of the green certificate price and risk aversion coefficient in the RPS mechanism on the optimal decisionmaking of trans-provincial electricity market subjects,and obtain the changing trends of two different power products and those of different electricity market subjects under the influence of the green certificate price and risk aversion coefficient,which have a certain reference value for studying the factors affecting the optimal decision-making of trans-provincial electricity market subjects.
文摘In this paper a novel cost function based on the relationship between operation cost of unit and generation load rate is employed in an agent-based model of Trans-provincial Centralized Bidding Trading Market of East China Grid. Simulation results are compared to real data to prove that the model is correct. Further analysis on simulation results point out the way to achieve an all-win game for power market members: generation companies improve their average load rates of the units by selling their electricity in the market, which makes units' cost drop and settlement price stay lower than benchmark price. Consequently electricity-demand provinces saved expenses, and units increase their profits. In conclusion, the trans-provincial electricity market of East China Power Grid is a successive case which improves the efficiency of the electricity industry by market-oriented measures.
文摘The option of organizing E-auctions to purchase electricity required for anticipated peak load period is a new one for utility companies.To meet the extra demand load,we develop electricity combinatorial reverse auction(CRA)for the purpose of procuring power from diverse energy sources.In this new,smart electricity market,suppliers of different scales can participate,and homeowners may even take an active role.In our CRA,an item,which is subject to several trading constraints,denotes a time slot that has two conflicting attributes,electricity quantity and price.To secure electricity,we design our auction with two bidding rounds:round one is exclusively for variable energy,and round two allows storage and nonintermittent renewable energy to bid on the remaining items.Our electricity auction leads to a complex winner determination(WD)task that we represent as a resource procurement optimization problem.We solve this problem using multi-objective genetic algorithms in order to find the trade-off solution that best lowers the price and increases the quantity.This solution consists of multiple winning suppliers,their prices,quantities and schedules.We validate our WD approach based on large-scale simulated datasets.We first assess the time-efficiency of our WD method,and we then compare it to well-known heuristic and exact WD techniques.In order to gain an exact idea about the accuracy of WD,we implement two famous exact algorithms for our constrained combinatorial procurement problem.