Navigating the Prevailing Challenges of the Nigerian Power Sector

The entire value chain of the Nigerian power sector (the production, transmission and distribution sector) is bedeviled with numerous challenges. Challenges that hamper and make the seventh sustainable development goal only a mirage. This paper aims to take a panoramic view of the Nigerian power architecture, outlining the challenges of the various stakeholders (The Generation Companies, The Transmission Company of Nigeria, The National Control Center, The Distribution Companies, The Nigerian Bulk Electricity Trading Plc, The Nigerian Electricity Regulatory Commission, The Gas producers, The Nigerian Gas Company and the consumers) with the goal of providing a roadmap of solutions; solutions to light up the African largest economy and invariably guarantee her socio-economic development.

Virtual Power Plant Platform for Demand Response Based on Microservice Architecture

It is a trend to use virtual power plant technology to realize demand response and participate in electricity trading. We design and implement the software control platform of virtual power plant for demand response. For this software platform, we analysed the requirements and got the overall architecture of the platform. On this basis, we design and implement the microservice architecture, interface design, basic application function design, advanced application function design, hardware architecture, communication architecture and security encryption of the platform. Finally, we summarize the application of the platform, and put forward the direction of further research and development.

Bidding Agents for PV and Electric Vehicle-Owning Users in the Electricity P2P Trading Market

As the world strives to decarbonize, the effective use of renewable energy has become an important issue, and P2P power trading is expected to unlock the value of renewable energy and encourage its adoption by enabling power trading based on user needs and user assets. In this study, we constructed a bidding agent that optimizes bids based on electricity demand and generation forecasts, user preferences for renewable energy (renewable energy-oriented or economically oriented), and owned assets in a P2P electricity trading market, and automatically performs electricity trading. The agent algorithm was used to evaluate the differences in trading content between different asset holdings and preferences by performing power sharing in a real scale environment. The demonstration experiments show that: EV-owning and economy-oriented users can trade more favorably in the market with a lower average execution price than non-EV-owning users; forecasting enables economy-enhancing moves to store nighttime electricity in batteries in advance in anticipation of future power generation and market prices; EV-owning and renewable energy-oriented users can trade more favorably in the market with other users. EV-owning and renewable energy-oriented users can achieve higher RE ratios at a cost of about +1 yen/kWh compared to other users. By actually issuing charging and discharging commands to the EV and controlling the charging and discharging, the agent can control the actual use of electricity according to the user’s preferences.

Volatility and Dispersion of Hourly Electricity Contracts on the German Continuous Intraday Market

Intraday electricity trading on the continuous intraday market of EPEX SPOT is particularly well suited for the rebalancing of energy production. We analyzed the volatility and dispersion of individual hourly contracts, taking into account the particularities of the market, due to which the standard volatility measure from financial time series cannot be applied. We used and analyzed five measures for price fluctuations, which turned out to be similarly well suited for electricity contracts, with small differences. We then identified fundamental drivers of price fluctuations: the relative share of wind in the overall mix increased dispersion. In addition, price dispersion was positively correlated with the traded volume as well as the absolute difference between the day-ahead auction price and the volume-weighted intraday price. We furthermore analyzed the timely structure of price fluctuations to identify forecast indicators for a contract’s peak trading hour before maturity, finding that trading-related variables are more important to forecast price fluctuations than fundamental factors. With lagged realizations and additional external drivers, forecast regressions reached an adjusted R2 of 0.479 for volatility and around 0.3 for the dispersion measures.

Decentralized P2P Electricity Trading Model for Thailand

Thailand’s power system has been facing an energy transition due to the increasing amount of Renewable Energy (RE) integration, prosumers with self-consumption, and digitalization-based business models in a Local Energy Market (LEM). This paper introduces a decentralized business model and a possible trading platform for electricity trading in Thailand’s Micro-Grid to deal with the power system transformation. This approach is Hybrid P2P, a market structure in which sellers and buyers negotiate on energy exchanging by themselves called Fully P2P trading or through the algorithm on the market platform called Community-based trading. A combination of Auction Mechanism (AM), Bill Sharing (BS), and Traditional Mechanism (TM) is the decentralized price mechanism proposed for the Community-based trading. The approach is validated through a test case in which, during the daytime, the energy import and export of the community are significantly reduced when 75 consumers and 25 PV rooftop prosumers participate in this decentralized trading model. Furthermore, a comparison analysis confirms that the decentralized business model outperforms a centralized approach on community and individual levels.