Multi-objective optimization and evaluation of supercritical CO_(2) Brayton cycle for nuclear power generation

The supercritical CO_(2) Brayton cycle is considered a promising energy conversion system for Generation IV reactors for its simple layout,compact structure,and high cycle efficiency.Mathematical models of four Brayton cycle layouts are developed in this study for different reactors to reduce the cost and increase the thermohydraulic performance of nuclear power generation to promote the commercialization of nuclear energy.Parametric analysis,multi-objective optimizations,and four decision-making methods are applied to obtain each Brayton scheme’s optimal thermohydraulic and economic indexes.Results show that for the same design thermal power scale of reactors,the higher the core’s exit temperature,the better the Brayton cycle’s thermo-economic performance.Among the four-cycle layouts,the recompression cycle(RC)has the best overall performance,followed by the simple recuperation cycle(SR)and the intercooling cycle(IC),and the worst is the reheating cycle(RH).However,RH has the lowest total cost of investment(C_(tot))of$1619.85 million,and IC has the lowest levelized cost of energy(LCOE)of 0.012$/(kWh).The nuclear Brayton cycle system’s overall performance has been improved due to optimization.The performance of the molten salt reactor combined with the intercooling cycle(MSR-IC)scheme has the greatest improvement,with the net output power(W_(net)),thermal efficiencyη_(t),and exergy efficiency(η_(e))improved by 8.58%,8.58%,and 11.21%,respectively.The performance of the lead-cooled fast reactor combined with the simple recuperation cycle scheme was optimized to increase C_(tot) by 27.78%.In comparison,the internal rate of return(IRR)increased by only 7.8%,which is not friendly to investors with limited funds.For the nuclear Brayton cycle,the molten salt reactor combined with the recompression cycle scheme should receive priority,and the gas-cooled fast reactor combined with the reheating cycle scheme should be considered carefully.

Analysis on decision-making model of plan evaluation based on grey relation projection and combination weight algorithm

In military service joint operations, when there are more operational forces, more multifarious materials are consumed, the support is more complex and fuzzy, the deployment of personnel is more rapid, and the support provided by wartime military material support powers can be more effective. When the principles,requirements, influencing factors and goals of military material support forces are deployed in wartime, an evaluation indicator system is established. Thus, a new combined empowerment method based on an analytic hierarchy process（AHP） is developed to calculate the subjective weights, and the rough entropy method is used to calculate the objective weights. Combination weights can be obtained by calculating the weight preference coefficient error, which is determined by combining the cooperative game method and the minimum deviation into objectives. This approach can determine the grey relation projection coefficient and synthesize the measure scheme superiority to finally optimize the deployment plan using the grey relation projection decision-making method. The results show that the method is feasible and effective;it can provide a more scientific and practical decision-making basis for the military material support power deployment in wartime.

Optimal Bidding and Operation of a Power Plant with Solvent-BasedCarbon Capture under a CO2 Allowance Market： A Solution with aReinforcement Learning-Based Sarsa Temporal-Difference Algorithm

In this paper, a reinforcement learning （RL）-based Sarsa temporal-difference （TD） algorithm is applied tosearch for a unified bidding and operation strategy for a coal-fired power plant with monoethanolamine（MEA）-based post-combustion carbon capture under different carbon dioxide （CO2） allowance market con-ditions. The objective of the decision maker for the power plant is to maximize the discounted cumulativeprofit during the power plant lifetime. Two constraints are considered for the objective formulation. Firstly,the tradeoff between the energy-intensive carbon capture and the electricity generation should be made un-der presumed fixed fuel consumption. Secondly, the CO2 allowances purchased from the CO2 allowance mar-ket should be approximately equal to the quantity of COs emission from power generation. Three case stud-ies are demonstrated thereafter. In the first case, we show the convergence of the Sarsa TD algorithm andfind a deterministic optimal bidding and operation strategy. In the second case, compared with the inde-pendently designed operation and bidding strategies discussed in most of the relevant literature, the SarsaTD-based unified bidding and operation strategy with time-varying flexible market-oriented CO2 capturelevels is demonstrated to help the power plant decision maker gain a higher discounted cumulative profit.In the third case, a competitor operating another power plant identical to the preceding plant is consideredunder the same CO2 allowance market. The competitor also has carbon capture facilities but applies a differ-ent strategy to earn profits. The discounted cumulative profits of the two power plants are then compared,thus exhibiting the competitiveness of the power plant that is using the unified bidding and operation strat-egy explored by the Sarsa TD algorithm.

How Load Aggregators Avoid Risks in Spot Electricity Market:In the Framework of Power Consumption Right Option Contracts

There is uncertainty in the electricity price of spot electricity market,which makes load aggregators undertake price risks for their agent users.In order to allow load aggregators to reduce the spot market price risk,scholars have proposed many solutions,such as improving the declaration decision-making model,signing power mutual insurance contracts,and adding energy storage and mobilizing demand-side resources to respond.In terms of demand side,calling flexible demand-side resources can be considered as a key solution.The user’s power consumption rights(PCRs)are core contents of the demand-side resources.However,there have been few studies on the pricing of PCR contracts and transaction decisions to solve the problem of price forecast deviation and to manage the uncertainty of spot market prices.In addition,in traditional PCR contracts,PCRs are mostly priced using a single price mechanism,that is,the power user is compensated for part of the electricity that was interrupted or reduced in power supply.However,some power users might engage in speculative behaviours under this mechanism.Further,for load aggregators,their price risk avoidance ability has not substantially improved.As a financial derivative,options can solve the above problems.In this article,firstly,the option method is used to build an option pricing optimization model for power consumption right contracts that can calculate the optimal option premium and strike price of option contracts of power consumption rights.Secondly,from the perspective of power users and load aggregators,a simulation model of power consumption right transaction decision-making is constructed.The results of calculation examples show that(1)Under the model in this article,the pricing of option contracts for power consumption rights with better risk aversion capabilities than traditional compensation contracts can be obtained.(2)The decision to sell or purchase the power consumption rights will converge at respective highvalue periods,and option contracts will expedite the process.(3)Option contracts can significantly reduce the loss caused by the uncertainty of spot electricity prices for load aggregators without reducing users’willingness to sell power consumption rights.

Discussion on the Logical Coordination between Legal Theory and Legal Practice——from the Perspective of the Legal Basis of NPC5s Discussion and Decisiomaking Power on Major Issues

The decision of local people's congresses to discuss major issues is a basic right granted to local people's congresses by the Chinese Constitution and laws.However,in practice,the implementation of the power of deliberation of major issues by local people's congresses is worrying.By applying the theory of Chinese traditionalism and unity in the theory of law,the theory of"sovereignty in the people"in the social contract theory of Western natural law school,Austin's"legal command theory55 in Western positivist law and Hart's"recognition""Rules theory"to argue that the integrity of rights necessarily involves the dual factors of decision-making and execution.At the same time,the existence and operation of the law always reflects the development of the political system.The realistic political situation requires us to make more precise and meticulous refinement of the external form and specific technical links of the legal system,and to coordinate the rules to make up the legal theory and Conflicts and conflicts in legal practice help to reform social institutions.

Apply to the Micro Grid Data Limit Learning Algorithm

More and more microgrid projects are put into operation and completed, and the load data are becoming more and more multidimensional and massive. This requires effective classification of load data. Most of the traditional processing methods are based on neural network to classify the grid data. However, with the development of microgrid, the traditional neural network algorithm is having a hard time meeting the requirement of the classification and operation of massive microgrid data. In this paper, the back propagation neural network (BPNN) algorithm is parallelized based on the traditional reverse neural network algorithm. Multiple algorithms are applied for data learning, for example, the combined application of extreme learning algorithm and simulated annealing algorithm, artificial fish swarm algorithm and other evolutionary algorithms. The input variables in BPNN are optimized in the network training process. After adding the algorithm fitness evaluation function, the combined algorithm of improved back propagation neural network algorithm came out. It is most in line with the real-time data of power grid by means of root mean square error. This result could provide data support and theoretical basis for load management, microgrid optimization, energy storage management and electricity price modeling of microgrid.

Resilience-oriented Restoration Strategy by Offshore Wind Power Considering Risk

Global climate changes have created intense naturaldisasters such as typhoons, which may cause serious damage topower systems. As an emerging renewable energy resource, offshore wind power has great potential in power systems resilienceenhancement with its rapid start-up capability and developmentof anti-typhoon technology. In this paper, a restoration strategyby offshore wind power considering risk is proposed to speedup the restoration process and enhance system resilience. Specifically, a failure risk model of an individual wind turbine andthen the whole wind farm is built for predicting severe weather’simpact, with focus on failure probability. Further, a quantificationmodel of resilience enhancement and risk cost, based on customerinterruption cost assessment method, is introduced. Then, a twostage optimized decision-making model is proposed to solve thescheme of offshore wind power and conventional power unitsin load restoration process. Case studies are undertaken on amodified IEEE RTS-79 system and results indicate the proposedrestoration strategy can shorten duration of restoration andreduce customers’ economic losses meanwhile ensuring systemsafety.

Fresh-Keeping Decision and Coordination of Fresh Agricultural Product Supply Chain Considering Carbon Cap-and-Trade under Different Dominance

In the context of low carbon,this paper discussed the impact of the carbon cap-and-trade policy on the fresh-keeping decision-making of two-echelon fresh agricultural product supply chains under different dominance,and designed cost-sharing contracts to coordinate the supply chain of fresh agricultural products dominated by suppliers and retailers respectively.The results showed that:dominance has no effect on the fresh-keeping decision and total revenue of fresh agricultural product supply chain,but it affects the internal income distribution,and dominance does not always bring more benefits;the implementation of carbon cap-and-trade reduces the fresh-keeping decision-making of fresh agricultural products supply chain and reduces the free-rider income of followers;the role of higher carbon trading price is twofold,which not only brings about the speculation of leading enterprises,but also promotes the application of low-carbon technologies;consumers’high preference for freshness,low-cost and high-efficiency low-carbon technology are all conducive to improving the fresh-keeping efforts and benefits of the supply chain;cost-sharing contracts can coordinate the supply chain of fresh agricultural products.