The total number of solar power-producing facilities whose Feed-in Tariff (FIT) Program-based ten-year contracts will expire by 2023 is expected to reach approximately 1.65 million in Japan. If the facilities that produce or consume renewable energy would increase to reach a large number, e.g., two million, blockchain would not be capable of processing all the transactions. In this work, we propose a blockchain-based electricity-tracking platform for renewable energy, called ‘ZGridBC,’ which consists of mutually cooperative two novel decentralized schemes to solve scalability, storage cost, and privacy issues at the same time. One is the electricity production resource management, which is an efficient data management scheme that manages electricity production resources (EPRs) on the blockchain by using UTXO tokens extended to two-dimension (period and electricity amount) to prevent double-spending. The other is the electricity-tracking proof, which is a massive data aggregation scheme that significantly reduces the amount of data managed on the blockchain by using zero-knowledge proof (ZKP). Thereafter, we illustrate the architecture of ZGridBC, consider its scalability, security, and privacy, and illustrate the implementation of ZGridBC. Finally, we evaluate the scalability of ZGridBC, which handles two million electricity facilities with far less cost per environmental value compared with the price of the environmental value proposed by METI (=0.3 yen/kWh).

RCP (Reconfigurable Computing Processor) is intended to fill the gap between ASIC and GPP (General Purpose processor), which achieves much higher energy efficiency than GPP, while is much more flexible than ASIC. In this paper, one organization of on-chip data memory called LIBODM (LIfetime Based On-chip Data Memory) is proposed to reduce the reference delay for data and on-chip data memory size in RCP. In the LIBODM, the allocation of data is based on the data dependency. The data with low data dependency are stored off-chip to save the storage costs, while the data with high data dependency are stored on-chip to reduce the reference delay. Besides, in the LIBODM, the on-chip data are classified into two types, and the classification is based on the lifetime of data. For short lifetime data, they are preferred to be stored into FIFO to increase the reuse ratio of memory space naturally. For long lifetime data, they are preferred to be stored into RAM for several time references. The LIBODM has been testified in one CGRA (Coarse Grained Reconfigurable Architecture) called RPU (Reconfigurable Processing Unit), and two RPUs has been integrated in a RCP-REMUS_HP (High Performance version of Reconfigurable MUlti-media System) focused on video decoding. Thanks to the LIBODM, although the size of on-chip data memory in REMUS_HP is small, a high performance can still be achieved. Compared with XPP and ADRES, in REMUS_HP, the on-chip data memory size at same performance level is only 23.9% and 14.8%. REMUS_HP is implemented on a 48.9mm2 silicon with TSMC 65nm technology. Simulation shows that 1920*1088 @30fps can be achieved for H.264 high-profile decoding when exploiting a 200MHz working frequency. Compared with the high performance version of XPP, the performance is 150% boosted, while the energy efficiency is 17.59x boosted.