SIMULATION RESEARCH ON CARBON EMISSIONS TRADING BASED ON BLOCKCHAIN

Global warming caused by greenhouse gases is one of the problems that need to be solved urgently. Blockchain technology can achieve automatic quota certification and settlement, providing a new direction for carbon emissions trading. This paper provides a quantitative analysis of blockchain-based carbon emissions trading through the Repast simulation platform. Firstly, it designs the blockchain-based carbon emissions trading simulation framework from a macro perspective, including identity and quota certification, quota trading, risk prevention and smart contracts management. Then, it establishes a blockchain-based carbon emissions trading simulation model and formulates the behavior rules of the government, investors and company agents and market transaction processes. Finally, it simulates the carbon emissions trading based on public chain and private chain on the Repast platform, and analyzes the simulation results.

Data interaction model for power transaction based on CIM

With the increase of power transaction business, traditional power transaction data interaction models cannot fully meet the needs of data interaction. The data model conforming to the power transaction data architecture plays an important role. Data interaction requirements of Chinese electricity market transaction business are analyzed, and the specific method of power transaction data description is given in the IEC-61970 protocol standard. Also a common information model (CIM) for electricity trans-action data interaction is built that conforms to the data interaction architecture. Finally the functional description of the model is built adopting the unified modeling language (UML). Compared with the existing electricity transaction data interaction model, the method is beneficial to reduce the degree of data redundancy, increase the speed of data interaction, and thus improve the transaction efficiency of the electricity market.

Social capital as a determinant for raising ecosystem services awareness - an application to an Albanian pastoral ecosystem

This paper aims to map the ecosystem services (ES) provided by a reputed agropastoral ecosystem in the south of Albania and ascertain whether social capital affects the level of importance attributed to them. A perception analysis of both buyers and sellers of ES within the pastoral ecosystem is undertaken. The pastoral ecosystem is mainly evaluated for cultural services such as tradition, enhancing the area’s image, and environment ES. The strong inclination towards cultural ES and socioeconomic services indicates a lack of awareness of both buyers and sellers of ES in the local community regarding the environmental aspects of their ecosystem. However, participants showing a higher radius of trust with high linking social capital are more likely to confer very high importance to environmental services. Similarly, the cultural ES (traditional aspect) of the pastoral ecosystem is affected by cognitive and structural social capital. These are interesting findings for public policymaking concerning the opportunity to develop market transaction ES. Its development is more ground-based and effective if participation and civic engagement, especially the Linking dimension, is enhanced in the pastoral community.

The Effect of Expected Losses on the Hong Kong Property Market

Expected losses anchored to purchase prices can affect actual transactions in different property sectors. Utilizing the data of over a million commercial and residential property transactions in Hong Kong from 1991 to 2015, we find that sellers facing nominal losses relative to their prior purchase prices attained higher selling prices than their counterparts. We suggest two market factors to account for the extent of the loss effect on the market transaction prices. First, the loss effect is only prominent when comparable transaction information is not readily accessible, such as in the less-transacted commercial property market. Second, our results suggest the relevance of the loss effect to the boom-bust property cycle in both the residential and commercial markets. The effect of expected losses on transaction prices is relatively weak in the bust period between 1998 and 2003 when the Hong Kong property market lost almost two-thirds of its value, and it enlarges with the market recovering. The loss effect is not attenuated at the aggregate market level but is associated with strong reductions in price declines in the bust period and in the commercial market. These results have implications for understanding the market adjustment of the loss effect in the property market and its association with the aggregate market dynamics in a boom-bust property cycle.

Souvenir Sales Analysis using Apriori Algorithm (Case Study: Ubud-Market Transaction in March 2020)

Ubud market is one of the largest art markets in Bali, there are many local Balinese souvenir traders and craftspeople, most of them are livelihoods depend on buying and selling local souvenirs, Since the Covid-19 pandemic entered in April 2020, Ubud market traders have started to close their business and hoping economic recoveryin future. The author tries to do a track record of souvenir sales transactions in Ubud market to find the last sales pattern before the traders closes their business to give a solution for marketing strategies in future. The sales transaction data will just become meaningless trash if it’s useless.. To get use information about the products that are most sold out at Ubud Market from the transaction database, the author uses the Apriori algorithm. This study was determined final rules on 2 itemset combination, If buying Manik-Manik Craft, Also buy Barong Shirt with the highest confidence 70% and Minimum Support 28%, and for 3 itemset a combination, If buying Celuk Silver, and Barong Shirt, Also buy Manik-Manik Craft with the highest confidence 37.5% and Minimum Support 12%, based on that there are 3 best-selling souvenir products, namely Barong Shirt, Manik-Manik Craft and Silver-Celuk in March 2020. Keywords: Apriori Algorithm, Data Mining, Sales Analysis, Association Rule Mining, Ubud Market.

Research on Decision Optimization Model of Microgrid Participating in Spot Market Transaction

The development of electricity spot trading provides an opportunity for microgrids to participate in the spot market transaction, which is of great significance to the research of microgrids participating in the electricity spot market. Under the background of spot market construction, this paper takes the microgrid including wind power, photovoltaic (PV), gas turbine, battery storage, and demand response as the research object, uses the stochastic optimization method to deal with the uncertainty of wind and PV power, and constructs a decision optimization model with the goal of maximizing the expected revenue of microgrids in the spot market. Through the case study, the optimal bidding electricity of microgrid operators in the spot market is obtained, and the revenue is USD 923.07. Then, this paper further investigates the effects of demand response, meteorological factors, market price coefficients, and cost coefficients on the expected revenue of microgrids. The results demonstrate that the demand response adopted in this paper has better social–economic benefits, which can reduce the peak load while ensuring the reliability of the microgrid, and the optimization model also ensure profits while extreme weather and related economic coefficients change, providing a set of scientific quantitative analysis tools for microgrids to trade electricity in the spot market.

Analysis of Taiwan’s Mask Collection and Plan Evasion during the COVID-19 Pandemic

This study established a two-stage dynamic game strategy to analyze how the planned quota and price of masks were set and why mask manufacturing firms on the national mask team (NMT) in Taiwan evaded the plan. Plan evasion occurred when the NMT decided to produce less than the quota set by the government, even though they were incentivized and able to produce more. Taiwan’s experience shows that through the collection of masks and the Name-Based Mask Rationing System, the people’s right to procure masks can be guaranteed; however, to promote market transaction efficiency, the government should adopt a lower quota for the collection of masks and allow firms to freely sell them in the market after they complete their plans. The self-interest of the government played a key role in inducing plan evasion.