碳交易试点政策与电力行业碳减排

低碳战略下,碳交易制度对于电力行业的碳排放量具有重要影响。以碳交易地方试点政策作为准自然实验,利用中国2006—2018年30个省际面板数据,采用双重差分模型检验了碳交易政策的实际影响效果。发现：（1）相对非试点地区,试点地区电力行业碳排放量具有更为迅速的下降趋势;（2）试点地区碳交易总量越高,交易额越大,则该地区电力行业碳排放量越低。结论表明：中国的碳交易试点制度对于地区电力行业碳排放具有控制作用。     

新能源消纳电量库交易机制的实践与经验

近年来,随着清洁低碳能源战略持续推进,新能源装机容量快速增长,新能源发电在系统中的比例不断提升。新能源高渗透性、随机性和波动性对系统调节能力和承载能力提出更高的要求。在深入分析新能源发电特性的基础上,挖掘电网互补潜力,提出新能源电量库交易机制。首先,建立新能源电量库交易模型,设置约束条件,给出交易申报和出清方式。然后,探索综合考虑灵活价格机制和电量库价值体系的价格机制,给出电量库结算方式。最后,基于中国西北电网新能源消纳实际,创新开展主控区置换电量库、援疆电量库、陕青省间调峰置换电量库等多品种交易实践。实际数据表明,电量库机制充分展现了系统调节价值,能够调动平抑新能源波动的系统灵活调节能力,显著提升新能源消纳水平。     

考虑碳交易的定、变频空调负荷降碳能力研究

在“双碳”目标的驱动下,为进一步提高负荷侧定、变频空调负荷和基础柔性负荷在需求响应的作用并分析其降碳能力,文中提出一种考虑碳交易的定、变频空调负荷及柔性负荷参与需求响应的电力系统优化运行策略。首先建立定、变频空调单体模型并推导其功率聚合模型;在此基础上结合多种影响空调用户参与需求响应的主要因素计算定、变频空调负荷最大降载能力;进而在传统需求响应调度模型中加入对定、变频空调负荷的考虑,并引入碳交易机制,基于此构建以机组发电成本、碳排放成本、负荷调度成本等综合运行成本最小为目标的电力系统优化运行策略;最后,以某配网系统进行验证分析,通过设置多种运行场景对比验证了所提策略在经济最优和节能减排方面的有效性。     

计及碳交易的热电联产-储热-电锅炉风电消纳策略

为解决传统热电联产机组的热电耦合特性以及冬季采暖期间弃风消纳问题,提出了计及碳交易含储热热电联产机组和电锅炉联合运行的弃风消纳策略。首先将储热设备、电锅炉与热电联产机组联合运行来满足系统所需热负荷,从而提高热电联产机组电调峰能力。其次,为进一步控制碳排放量,引入阶梯式碳交易与优化电锅炉运行模式,兼顾系统运行成本、弃风消纳量以及碳排放量,构建计及碳交易的热电联产-储热-电锅炉风电消纳模型并进行求解。最后,以IEEE-30节点为例进行算例分析,结果表明所提策略能够有效促进风电消纳、减少碳排放量且有效降低系统运行成本。     

A secure blockchain‐based demurrage mechanism for energy trading in smart communities

This paper combines additive homomorphic encryption and consortium blockchain technology to provide privacy and trust. Additionally, a dynamic energy pricing model is formulated based on the demand response ratio (DRR) of the load demand of prosumers to address fixed energy pricing problems. The proposed dynamic pricing model includes demurrage fees, which is a monetary penalty imposed on a prosumer, if it failed to deliver energy within the agreed duration. Furthermore, this paper also designs and analyzes a threat model of the proposed system. Experimental evaluations show the effectiveness of the proposed model with regards to low transaction cost, the minimum execution time for block creation, the privacy of prosumers and dispute resolution of demurrage fees. Moreover, the proposed scheme reduces the average system overhead cost up to 66.67% as compared to 33.43% for an existing scheme. Additionally, the proposed blockchain proof‐of‐authority consensus average hash power is minimized up to 82.75% as compared to 60.34% for proof‐of‐stake and 56.89% for proof‐of‐work consensus mechanisms.     

Integration of hydrogen storage system and solar panels in smart buildings

In the residential area, the cost of the electricity is at the maximum level during the peak demand periods. Regarding this, the peer-to-peer (P2P) energy trading strategy is a hopeful and practical solution to deal with this problem. Also, in the P2P home energy management system, the buildings have become more flexible by sharing their powers to meet their electricity demands. In this work, we have considered three buildings, in which two of them are equipped with solar panels, and in the third one, the hydrogen source is established. In the proposed residential zone, the considered buildings are connected in order to perform P2P transactions to reduce the energy billing. The operator of the system is wholly investigated under uncertain conditions based on the downside risk constraint (DRC) method in both risk-averse and risk-neutral models. With the help of a P2P energy trading strategy as well as renewable energy resources, we can provide electricity to customers in remote areas where it is not possible to supply electricity or is not economically beneficial. Based on the obtained results, the function of the proposed system has manifested in an acceptable manner. For instance, in the solar panel function in the second building, the amount of generated solar power is 30 kW in the risk-averse model, whereas, in the risk-neutral model, it is 18 kW. On the other hand, the level of consumed electricity by the electrolyzer system is generally lower in the risk-averse model than risk-neutral model in the second season.     

Automated Negotiation in E Commerce: Protocol Relevance and Improvement Techniques

We all negotiate, formally or informally, in jobs, in day today lives and outcomes of negotiations affect those processes of life. Although negotiation is an intrinsic nature of human psyche, it is very complex phenomenon to implement using computing and internet for the various purposes in E Commerce. Automation of negotiation process poses unique challenges for computer scientists and researchers, so here we study how negotiation can be modeled and analyzed mathematically, what can be different techniques and strategies or set of rules/protocols to be implemented and how they can be relevantly implemented. We are in a quest to find out how this complex process, which involves human psyche can be automated using computers and modern day technologies. Now, the quest is not only automation, looking at the research in the related field in last ten years; but it is all about finding solutions to make e-negotiation more efficient and more accurate, as well as useful in any kind of electronic trading situations. Here is an attempt to consolidate our work of last few years on automation of negotiation process; we call it as negotiation protocol on research, study as well as implementation level of negotiation automation. Overall, we are trying to give few solutions to make the automation more efficient.     

State-of-the-Art Analysis and Perspectives for Peer-to-Peer Energy Trading

As a promising solution to address the “energy trilemma” confronting human society, peer-to-peer (P2P) energy trading has emerged and rapidly developed in recent years. When carrying out P2P energy trading, customers with distributed energy resources (DERs) are able to directly trade and share energy with each other. This paper summarizes and analyzes the global development of P2P energy trading based on a comprehensive review of related academic papers, research projects, and industrial practice. Key aspects in P2P energy trading are identified and discussed, including market design, trading platforms, physical infrastructure and information and communication technology (ICT) infrastructure, social science perspectives, and policy. For each key aspect, existing research and practice are critically reviewed and insights for future development are presented. Comprehensive concluding remarks are provided at the end, summarizing the major findings and perspectives of this paper. P2P energy trading is a growing field with great potential and opportunities for both academia and industry across the world.     

Influences of uncertainties to the generation feasible region for medium- and long-term electricity transaction

For the implementation of power market in China, medium- and long-term security checks are essential for bilateral transactions, of which the electricity quantity that constitutes the generation feasible region (GFR) is the target. However, uncertainties from load forecasting errors and transmission contingencies are threats to medium- and long-term electricity trading in terms of their influences on the GFR. In this paper, we present a graphic distortion pattern in a typical three- generator system using the Monte Carlo method and projection theory based on security constrained economic dispatch. The underlying potential risk to GFR from uncertainties is clearly visualized, and their impact characteristics are discussed. A case study on detailed GFR distortion was included to demonstrate the effectiveness of this visualization model. The result implies that a small uncertainty could distort the GFR to a remarkable extent and that different line-contingency precipitates disparate the GFR distortion patterns, thereby eliciting great emphasis on load forecasting and line reliability in electricity transactions.     

Designing an emissions trading scheme for China with a dynamic computable general equilibrium model

To fulfill its Copenhagen pledges to control carbon emissions and mitigate climate change, China plans to establish a nationwide emissions trading scheme (ETS) in 2016. This paper develops a multi-sector dynamic computable general equilibrium model with an ETS module to study the appropriate ETS policy design, including a carbon cap, permit allocation and supplementary policies (e.g., penalty policies and subsidy policies). The main results are as follows. (1) To achieve China's Copenhagen pledge, the equilibrium nationwide carbon price is observed to be between 36 and 40 RMB yuan per metric ton. (2) The ETS policy has a cost-effective mitigation effect by improving China's production and energy structures with relatively little economic harm. (3) Various ETS sub-policies should be carefully designed to balance economic growth and carbon mitigation. In particular, the carbon cap should be set according to China's Copenhagen pledge. A relatively large distribution ratio of free permits, the output-based grandfathering rule for free permits, a penalty price (on illegitimate emissions) slightly above the carbon price, and a sufficient subsidy (from ETS revenue) are strongly recommended in the early stages to avoid significant economic loss. These designs can be adjusted in later stages to enhance the mitigation effect.