Power Sales Research Articles

The Strategic Plan of the Working Day

“The Working Day” chapter of Capital makes sense today as an illustration of collective struggle over the sale of labor power by the hour. The historical materials in the chapter are instructive if read under the tutelage of Gertrud Kugelmann, considering the advice Karl Marx offers to her on where to start. A reassessment of Marx’s writing process is possible via his various plans in letters, his comments on method, the various sources used, and evaluating the role they have in Capital volume 1. Several scholars read Marx on commodities that “speak” but may sometimes miss idioms in English translation. Reading the German text can help us when searching for theoretical and political strategies for contemporary emancipation. With implications for replies to critics of Marx on slavery, my case is that the staging in Capital offers diagnostic potential where attention to the Parliamentary Blue Books might generate new research agendas, addressing current problems of time, social reproduction, climate, and class struggle. JEL Classification: B14

Capacity Optimization of Wind–Solar–Storage Multi-Power Microgrid Based on Two-Layer Model and an Improved Snake Optimization Algorithm

A two-layer optimization model and an improved snake optimization algorithm (ISOA) are proposed to solve the capacity optimization problem of wind–solar–storage multi-power microgrids in the whole life cycle. In the upper optimization model, the wind–solar–storage capacity optimization model is established. It takes wind–solar power supply and storage capacity as decision variables and the construction cost of the whole life cycle as the objective function. At the lower level, the optimal scheduling model is established, considering the output characteristics of various types of power supplies and energy storage, microgrid sales, and purchases of power as constraints. At the same time, the model considers constraints, such as the power balance, the operating state of the energy storage system, the power sales and purchases, and the network fluctuations, to ensure the system operates efficiently. Taking a microgrid in South China as an application scenario, the model is solved and the optimal capacity allocation scheme of the microgrid is obtained. Meanwhile, the demand response mechanism and the influence of planning years are introduced to further optimize the configuration scheme, and the impact of different rigid–flexible load ratios and various planning horizons on microgrid capacity optimization is analyzed, respectively, by a numerical example. The comparison shows that the ISOA has better optimization performance in solving the proposed two-layer model.

Optimal strategies for virtual power plants to participate in medium- and long-term power trading in the context of contracts for difference (CFDs)

Abstract In the context of virtual power plants gradually joining the medium-and long-term power market transactions, the decision-making problem of this new subject in the transaction process has attracted wide attention. Since virtual power plants possess distributed power sources on the supply side, as well as variable loads, energy storage, and other resources on the customer side, they are able to participate in both the sale and purchase of electricity in the medium-and long-term electricity market at the same time, which leads to the need for the relevant analysis to be divided into the two cases of sale and purchase of electricity. At the same time, due to the wide application of the CFD mechanism, power transactions should also take into account the compensation adjustment brought by this mechanism in addition to the market price. To sum up, this paper constructs a static game model for the virtual power plant’s power sales and purchasing strategies in the medium-and long-term power market under the premise of the CFD mechanism. The analysis shows that the optimal trading volume is related to the CFD volume, the total volume of power supplied by the bidding, the market price, etc. The relevant conclusions will help market managers to grasp the market price. The conclusions of the analysis help market managers grasp the key transaction information and assist virtual power plants to participate in medium-and long-term power transactions in an orderly manner.

Glimpse on Spot and Derivative Market of Electricity and Nepal’s Hydropower

Energy plays a vital role in a country’s economic development. Nepal abundantly blessed with various renewable resources like hydropower, solar energy, biogas, and biomass can achieve prosperity both economically and socially. Further, with a significant opportunities for the regional electricity market as the country has been surrounded by big powerhouses like China and India. It has huge possibilities for regional trading of renewable energy. The present total Installed capacity of power is 3157 MW in Nepal. With 95% hydropower generation, the energy mix in the Integrated Nepal Power System makes the country a surplus of electricity during the wet season when the water in the river is very high and a shortage during the dry season when the discharge in the river is minimal. Hence, to address the surplus generation during the wet season and shortage of power during the dry season, trading in the region plays a very vital role in balancing the demand and supply of the country. Nepal has been importing power during the dry season power deficit in the market during the dry season when the demand is high leaving NEA at risk of interrupting the supply to its customers. Likewise, uncertainty about clearing a bid during the wet season when the power production is high and Nepal is in the position to export the power in the regional market, as the Hydropower plant has to compete with the cheap coal power plant resulting in financial loss and uncertainty of return on investment. Hence, to tackle the mentioned financial risks, the Electricity Derivative market can be one of the best options as derivatives markets can be used to hedge against price fluctuations in electricity spot markets. Similarly, the uncertainty of power sale can be avoided by selling or buying the electricity through a derivative market for the future time period that secures the price and the amount that can be sold in the market in the future. In a nutshell, the Electricity Derivative market can be a useful mechanism for the development of hydropower in Nepal in the future.

Methods of long-term planning of corporate financing

The questions on long-term planning of an enterprise’ bonded loan interest rate payments have been studied. The methods have been considered and the classification of methods for planning the bonds interest rate proposed. Several groups of such planning methods have been singled out. The analysis of application of bond interest rate planning methods applied by enterprises of different national industries has been made. The analysis has been carried out in the spheres of mechanical engineering, generation, transmission and sales of electric power, ferrous metals production, transportation and logistics, foodstuffs production, and information transmission provision. Corporate bond issues issued between 2015 and 2020 have been analyzed. As a result, the three methods most frequently used by enterprises in planning bond interest rates have been identified: methods of considering the macroeconomic risk of an organization; methods of considering the combination of macroeconomic and individual risk of an organization; methods based on market analysis. The study of the mentioned methods allowed us to propose a method of planning the bond interest rate, which calculates the weighted average of the forecast bond interest rate. To assess the quality of the proposed method, it has been tested. The article concludes that it can be used at enterprises planning to issue their own bonded loans.

Integration of Price Data in Wind Power Sales Systems Using Association Rule Mining Combined with Deep Learning Algorithms

With the growing attention of the global population towards renewable energy sources such as wind power derived from natural resources such as Solar, Geothermal, and Wind energy, there is a growing need for genuine estimation of wind energy. Wind energy is important in the supply of electricity in the global energy markets because of its enormous importance in the delivery of renewable energy. As such, it is crucial for accurate appreciation of the power of the wind to ably respond to issues that relate to the trading of power while at the same time addressing issues to do with planning, scheduling and strategic positioning of wind power generation. Therefore, the present work aims to develop a new model known as the Association Rule with DL-based Wind Power Generation and Price Prediction (ARDL-WPGPP). It utilizes two datasets: An Energy dataset includes various columns like tie, wind onshore forecast, and price actual, whereas the weather features dataset includes only wind speed. These datasets are combined to create a dataset where each transaction represents 2 hours of wind generation. A data mining approach is employed to uncover hidden patterns, rules, concepts, and correlations within these datasets, operating on various types of data including quantitative, textual, and multimedia formats. To efficiently extract rules from the dataset, an improved Apriori algorithm is introduced. Subsequently, the generated rules incorporating wind speed are passed into an improved LSTM model, which learns by comparing the label data. The price actual value serves as the label data, assigning labels to data points based on their actual price value. High price actual values indicate high wind power prices, while low values indicate low wind power prices.

Energy sales activities development in electric power market

The energy sales activities development processes in the electric power industry have been studied. The factors determining the infrastructural nature of activity in the modern market, aimed at supporting opportunities for implementing competitive transactions of electric power purchase and sale, have been formulated. The process of planning to implement in 2005–2008 a “resale” scheme for organizing energy sales activities in the course of developing a new market model has been assessed. The choice of such a scheme is not simple and not the best of possible solutions. The problems arising for economic entities in the modern Russian electric power market under the conditions of the “resale” scheme for organizing energy sales activities have been characterized. Mechanisms and procedures of the market do not provide its subjects with acceptable competition conditions. This is largely due to the fact that energy sales companies, seeking to preserve and expand the monopoly sale of electricity, suppress the possibility of competitive choice of its suppliers and consumers, creating conditions of entrepreneurship low efficiency in the market. The article proposes approaches to improving energy sales activities based on the implementing the “agency” scheme within the framework of the electric power market digital model with the solution of tasks to provide its subjects with opportunities for competitive choice, ensuring fair competition conditions for detecting and implementing opportunities to obtain entrepreneurial benefits.

Optimization of the Coupling between Water and Energy Consumption in a Smart Integrated Photovoltaic Pumping Station System

Agricultural irrigation requires significant consumption of freshwater resources and energy. The integration of photovoltaic power generation into irrigation systems has been extensively investigated in order to save the cost of energy. However, current research often neglects the coupling relationship between photovoltaic power generation and irrigation schemes. This study presented a novel smart integrated photovoltaic pump station system to effectively address the issue associated with water and energy consumption in irrigation. An optimization model was proposed to synchronize the energy consumption of irrigation pump stations with photovoltaic power generation, accurately meeting the irrigation water demand while maximizing solar energy utilization. The optimization model incorporates power balance, grid-connected power, and total water demand as constraints while considering pump speed as the decision variable and aiming to minimize daily operational costs. Finally, a high-standard farmland was used as a case study to validate the efficacy of the optimization strategy through two photovoltaic grid-connected policies—one allowing for the sale of surplus power and the other prohibiting it. An improved dynamic programming method was employed to solve for optimal energy consumption schemes under different water demand conditions; the results were compared against traditional methods, revealing potential cost savings ranging from 6.2% to 30.5%. The optimization model and method propose a new operational concept for the irrigation system with photovoltaic generation, effectively utilizing the distinctive features of both irrigation and photovoltaics to optimize water and energy resources.

Inventiveness as a Driver of Small and Medium-Sized Business Profitability in South Africa: A Quantile Regression Method

In South Africa, inventiveness is a critical factor in expansion and growth, and small and medium-sized businesses have been designated as tools for achieving the societal and economic objectives and innovation outlined in the National Development Plan. The aim of this research is to look at the impact of inventiveness on small and medium-sized profitability in South Africa. The quantile regression method was utilised in empirical studies to explore the influence of inventiveness on enterprise profitability across different sales stages. The research was based on data from the World Bank's business questionnaire. The research results showed that expenses on development and research had a positive and substantial influence on profitability for businesses with greater sales (fast expansion or bigger enterprises). Existing proof demonstrates that incorporating new items and services boosts profitability for businesses with low progress or tiny businesses. Based on empirical evidence, inventiveness is essential for the growth and development of small and medium-sized businesses. Smaller or low-growth businesses don't have the ability to make expenditures on R&D because of a shortage of funds, which could contribute to their low chances of surviving. Considering the significant cash investment needed for R&D expenditures, additional support could be offered to smaller businesses in less powerful sales expansion. Because of a lack of funding for R&D, smaller businesses are being driven to create new items and production procedures that do not require big financial commitments.

Analyze The Effect of Service Quality, The Role of Social Media Technology, and Company Reputation On Increasing Power Sales

The purpose of the research to identify effect of service quality, the role of social media technology, and company reputation on increasing power sales. This research is an explanatory research using hypothesis testing methods and quantitative approaches. The goal is to explain the causal relationship between one variable that affects another variable, namely independent variables in the form of service quality, the role of social media technology and company reputation on the dependent variable that is increased sales. Based on the discussion in the previous chapters and answering the problem formulation, research objectives and referring to the process and results of data analysis in this study, the following conclusions can be drawn: There is a positive and significant influence between service quality and increased electricity sales at PLN UP3 Ponorogo. There is a positive and significant influence between the role of social media technology and the increase in electricity sales at PLN UP3 Ponorogo. There is a positive and significant influence between the company's reputation and the increase in electricity sales at PLN UP3 Ponorogo

Concentrating Solar Power (CSP) Plant Optimization Study for the California Power Market (CalCSP)

In the United States, many states are implementing goals to achieve 100% carbon free power generation by 2050 or sooner. California has one of the more aggressive goals to achieve 100% carbon free generation of its retail power sales by 2045. California has excellent solar resources, but to accomplish this goal, California’s power utilities will need new zero carbon resources that can replace the natural gas units that they currently rely on for suppling power at night. Appropriately configured concentrating solar power plants with thermal energy storage are an option to serve this nighttime load. These plants would be designed to take advantage of CSP’s low-cost thermal energy storage and collect and store energy during the day and then be dispatched to produce power at night. The U.S. Department of Energy has funded a study to identify the design of a CSP plant that optimally meets the evolving CA grid needs. This will be done by taking a fresh look at how CSP technologies can best be designed to meet the emerging nighttime market for carbon free power generation or zero-carbon firm resources. The paper provides an overview of the study and present preliminary findings on the California power market requirements, CSP configurations, technoeconomic analysis, siting opportunities, and key issues for CSP deployment in this market.

Optimal green investment strategy for grid-connected microgrid considering the impact of renewable energy source endowment and incentive policy

Microgrid is a promising way to integrate renewable distributed generation into the electric power sector, which has received widespread attention. In this paper, a uniform capacity-constrained optimization model under different power purchase and sale price contracts is developed to explore the optimal green investment strategy for grid-connected microgrid (GCM) with three configuration types. The impact of renewable energy source endowment and incentive policy is focused when macrogrid’s generators emit more pollution than GCM’s non-renewable generators, such as in China and India. The results show that: (1) GCM with renewable generation can only be invested in a site with relatively abundant renewable endowment; (2) carbon tax effectively promotes the deployment of GCM with renewable generation and achieves carbon emission abatement, but excessive carbon tax cannot incentive investment in the most desired GCM type; (3) a subsidy trap is found under feed-in tariff (FIT) subsidy, which implies that the fade-out or exit of FIT subsidy is beneficial for microgrid’s healthy development; (4) and the comparisons under different price contracts emphasize the importance of macrogrid providing non-discriminatory access to feed-in and feed-out services to microgrid.

Optimization strategy of power purchase and sale for electricity retailers in a two-tier market

Against the backdrop of the gradual advancement of China's electricity market reform, the number of Power Trading Companies in China has been increasing year by year, and as of October 2022, the number has reached more than 10,000. As an important hub connecting the electricity market and users, electricity retailers face double risks from downstream user load fluctuations and electricity market price fluctuations. Therefore, a reasonable power purchase and sale strategy is very important for an electricity retailer. In this study, a block bidding mechanism is adopted to optimize the clearing of the medium-to long-term market and a DA-RBF neural network is established for spot electricity price forecasting model based on numerical feature similarity to improve the accuracy of electricity price forecasting. Furthermore, the model considers the differences in user demand responses and investigates the optimal power purchase and sale strategy, guided by differentiated time-of-use electricity pricing. The case study analysis demonstrated that the proposed power purchase and sale optimization strategy yields favorable results, improving profitability and enhancing the stability of the power system.

Design of a bidirectional EV charger using unit template-based current-controlled synchronous reference frame hysteresis

Abstract Existing distribution networks were not designed with large-scale electric vehicle (EV) charging infrastructure in mind. Integrating EV charging stations with the distribution grid might lead to power quality (PQ) issues at the point of common coupling (PCC). This work proposes a two-mode, unit template-based synchronous reference frame hysteresis current-controlled (SRF-HCC) three-phase Level 2 EV charger. Mode one focuses on charging the EV battery from the grid (G2V) and utilizes current and voltage control techniques to enhance battery life and performance. Whereas mode two enables the EV’s stored energy to be discharged to the grid (V2G) by the EV user, allowing the sale of power to support the transient effect of the grid voltage and frequency and enhancing the grid’s PQ. The HCC generates switching pulses for both the AC-DC and buck-boost converters. The SRF-based unit template-based control (SRF-UTC) method ensures system stability, voltage, and frequency regulation for power exchange with the grid by combining its efficiency with that of the HCC. The EV charger proposal comprises three primary components: a 3-phase bidirectional AC-DC converter, a bidirectional buck-boost converter, and a filter circuit. The proposed system was modeled using MATLAB/Simulink and evaluated in two case studies to assess its performance.

Business decision-making of power generators in competitive electricity market

This paper presents a theoretical framework for the business decision-making process of the power generators as price takers when considering the participation of energy storage. The framework assesses rational valuation, optimal sales strategies, and hedging options for power plants with and without a gross sales constraint. The valuation and optimal sales strategy problems are analyzed using a risk-neutral pricing approach, dynamic programming principles, and the trinomial tree model suitable for the regime switching model. The formulation of a price risk hedging scheme flexible and widely used over-the-counter electricity derivative, the electricity contract for difference, as a tool for hedging electricity spot price risk. The minimum variance hedge ratio and its corresponding hedging efficiency formula are derived. In the section of numerical simulations, we first use the EM algorithm to calibrate the electricity spot model based on electricity spot price data of Nord Pool. Numerical simulations are then conducted on the operational decision-making of power generators under three different forms of energy storage. The results of the simulations provide a basis for power generators to evaluate the real-time value of power plants, to select optimal real-time power sales, and to determine the optimal timing of power plant transfer and storage methods.

Renewable Energy Power’s Investment and Production Strategies for a Class of Noncooperative Game Models of Power Sales With Risk Avoidance

Renewable Energy Power’s Investment and Production Strategies for a Class of Noncooperative Game Models of Power Sales With Risk Avoidance

Coordinated planning method considering flexible resources of active distribution network and soft open point integrated with energy storage system

AbstractFaced with the uncertainty of wind and photovoltaic power output and load fluctuation caused by the increase of new energy penetration in active distribution network, the demand for operational flexibility and the construction demand for flexible resources of distribution network are gradually increasing. The flexible operation of active distribution network can be realized by coordinated planning of the soft open point integrated with energy storage system (ESOP) and flexible resources. Firstly, the flexibility resource adjustability evaluation and margin indicators are proposed for the response model of typical flexibility resources. Secondly, a two‐stage distributionally robust coordinated planning model considering the coordination planning scheme of distributed generation, flexibility resource, and ESOP as well as the comprehensive norm uncertainty of wind power and photovoltaic outputs multi‐operation scenarios is established with the distribution network construction cost, annual operation cost, and annual power sales revenue as the objective functions meanwhile the investment and flexibility resource operation as constraints. Finally, the column constraint generation algorithm is used to solve the problem, and the effectiveness of the proposed model is verified by the modified IEEE33 node system.

Reviewing the Situation and Prospects for Developing Small Renewable Energy Systems in Poland

The objective of this study was to evaluate changes in the number of small renewable energy sources (RES) power plants and the volume of generated energy in the years 2016–2020, with an outlook to year 2025. The study covered the area of Poland, including the division into provinces and different sources of renewable energy. Absolute values of electric power production and sale were presented, in addition to calculated structure indices. Moreover, the number and structure of small power plants using different renewable energy sources was determined for every Polish province. A classification of the provinces was made, where four classes were distinguished depending on the number of RES plants operating in the provinces. The research results allowed us to diagnose the current situation and make a prognosis for the future, which may translate into support for the development of particular types of installations, depending on the natural and economic characteristics of each area. The added value of the study stems from the fact that previous reports focused mainly on micro or large power plants and the time span covered data before and during the pandemic. This made it possible to assess the impact of the pandemic on the development of small renewable energy sources.

Research on the Dynamic Characteristics of Photovoltaic Power Production and Sales Based on Game Theory

This paper mainly studies the dynamic characteristics of production and sales of distributed photovoltaic power. This is beneficial for the construction and development of a green power system, and it promotes the sustainable development of the social economy. First, the production and sales laws of the photovoltaic power are analyzed, and the trade process between photovoltaic power producers (PVPs) and photovoltaic power demanders (PVDs) is modeled as a game. Different from the existing relevant literature, two kinds of payoff bimatrices are provided, which correspond to the PVD market and PVP market, respectively. Then, the dynamic characteristics of the model are revealed by using the semitensor product method. The results present a more reliable theoretical basis for the sustainable development of the green electricity market. Finally, through an illustrative example, it can be seen that the strategies of all participants are constantly changing to obtain more profits rather than stable at a traditional Nash equilibrium point. It is worth pointing out that the method and results are applicable to other distributed low-carbon energies, contributing to the development of sustainable energy systems.

Neuroselling: applying neuroscience to selling for a new business perspective. An analysis on teleshopping advertising.

This paper presents an innovative research project that aims to study the emotional factors influencing decision-making elicited by infomercials, a powerful sales technique that uses emotional communication to engage viewers, capture attention, and build trust. Using cutting-edge consumer neuroscience techniques, this study focuses on the identification of the variables that most impact the Call-to-Action and Purchase Intention. Forty participants were selected and divided into two groups, with each group exposed to one of two infomercials (condition A = male seller; condition B = female seller). EEG signals were recorded as well as Eye-tracking data. After the viewing, participants completed a self-report questionnaire. Results show that seller characteristics such as Performance and Trustworthiness, as well as Neurophysiological variables such as Approach-Withdrawal Index, Willingness to Pay, Attention and Engagement, significantly impact the final Call-to-Action, Purchase Intention, and infomercial Likeability responses. Moreover, eye-tracking data revealed that the more time is spent observing crucial areas of the infomercial, the more it will increase our Willingness to Pay and our interest and willingness to approach the infomercial and product. These findings highlight the importance of considering both the Seller attributes and the consumers' Neurophysiological responses to understand and predict their behaviors in response to marketing stimuli since they all seem to play a crucial role in shaping consumers' attitudes and purchase intentions. Overall, the study is a significant pilot in the new field of neuroselling, shedding light on crucial emotional aspects of the seller/buyer relationship and providing valuable insights for researchers and marketers.