Power Procurement Research Articles

Legal Imperatives for the Implementation of Energy Auctions in Nigeria

Abstract With the passage of the Climate Change Act, and to help meet its net zero obligations by 2060, Nigeria must transition from its dependence on fossil fuel energy sources to renewable energy. This will involve the procurement of large amounts of renewable energy by the government. In the past, procurement of power from the government-owned bulk trader has been chaotic, with no discernible strategy, and it is doubtful whether the government or Nigeria's citizens have derived value for money from the process. This article suggests a transition from the current, mostly unsolicited, proposal system to energy auctions, as the authors believe that this will help the country achieve low prices for renewable energy. The article also examines polices that have been implemented in other countries to drive energy auctions, with a view to applying relatable practices to the Nigerian exercise.

Unlocking the potential: Insights from industry on barriers, solutions and policy gaps in Ireland's energy storage sector

The energy storage sector across Europe faces many financial, regulatory and policy barriers which has to date hindered development in many countries. This study documents industry perspectives from Ireland, a country which requires a significant increase in the development of energy storage due to security of supply concerns, its isolation from Europe’s central transmission network and its reliance on wind energy as a primary intermittent renewable energy resource. Using focus groups and a survey with the renewable energy and storage sector, we document perspectives on the critical barriers, innovative solutions and policy gaps identified by industry stakeholders and policy makers. Our participants believe energy storage will play a crucial role in unlocking Ireland’s substantial wind energy potential in order to meet its energy security and climate aspirations. However, our respondents suggest that unlocking this potential will require a coherent national energy storage strategy designed to reduce curtailment, identify storage technologies with duration-specific targets and establish a more comprehensive renewable energy plus storage power procurement mechanism designed for the Irish market which supports the grid, rewards low carbon technologies and reduces emissions.

A hierarchical framework for aggregating grid-interactive buildings with thermal and battery energy storage

The behind-the-meter (BTM) thermal and battery energy storage can help improve energy efficiency, reduce energy costs, and enhance energy resilience, particularly in rural areas and for disadvantaged communities. Aggregating numerous BTM energy storage systems can act as a price influencer with a significant source of load shifting and peak demand reduction. An integrated and scalable control mechanism is required to effectively utilize energy storage systems and flexible building loads to maximize the economic benefits, considering various distribution system constraints. This paper presents an innovative hierarchical coordination framework for energy storage and flexible load in buildings, considering various factors such as electricity prices, thermal comfort, and distribution system modeling and constraints. At the upper level, a distribution system operator optimizes the power flow to minimize its power procurement costs from the electricity wholesale market, while at the lower level, aggregators determine the optimal dispatch of battery and thermal energy storage systems in multiple buildings on behalf of end-users to minimize operating costs according to the power prices. These problems are solved using a game-theoretic approach through negotiations between the distribution system operator and aggregators as a bi-level decision model. Simulation case studies have been performed for a test distribution network with a number of building end-users using energy storage systems to quantify the performance of aggregators. The results demonstrate that the proposed strategy can reduce peak load for a reliable electricity distribution network while saving electricity bills for customers.

Improvement and Analysis of Peak Shift Demand Response Scenarios of Industrial Consumers Using an Electricity Market Model

Electricity procurement of industrial consumers is becoming more and more complicated, involving a combination of various procurement methods due to electricity liberalization and decarbonization trends. This study analyzed and improved power procurement strategies for a factory to achieve carbon neutralization through a multi-agent model simulating the electricity market and introduced a factory agent using various procurement methods including PV, FC, storage batteries (SB), and DR. Firstly, we created a new procurement strategy utilizing all methods. Then, by using the simulation model, we assessed the effectiveness of the existing peak shift DR scenarios in terms of cost reduction efficiency. Results revealed that the introduction of PV has led to a counterproductive outcome for DR. Based on the results, we proposed two methods to improve the effectiveness of DR, namely considering the operation of PV in the DR scenario and expanding the range of optional time periods for DR activation. Finally, we made three new DR scenarios based on our proposal. Through experiment, the new scenarios were confirmed to be effective in cost-effectiveness for decarbonization.

Physical vs Virtual corporate power purchase agreements: Meeting renewable targets amid demand and price uncertainty

Power purchase agreements (PPAs) have become an important corporate procurement vehicle for renewable power, especially among companies that have committed to targets requiring a certain fraction of their power demand be met by renewables. PPAs are long-term contracts that provide renewable energy certificates (RECs) to the corporate buyer and take two main forms: Physical vs Virtual. Physical PPAs deliver power in addition to RECs, while virtual PPAs are financial contracts that hedge (at least partially) power price uncertainty. We compare procurement portfolios that sign physical PPAs with ones that sign virtual PPAs, focusing on fixed-volume contracts and emphasizing uncertainties in power demand and the prices of power and RECs. In particular, we first analyze a two-stage stochastic model to understand the behavior of procurement quantities and costs when using physical and virtual PPAs as well as variants that limit risk. We subsequently formulate a Markov decision process (MDP) that optimizes the multi-stage procurement of power to reach and sustain a renewable procurement target. By leveraging state-of-the-art reoptimization techniques, we solve this MDP on realistic instances to near optimality, and highlight the relative benefits of using PPA types to meet a renewable target. We underscore a trade-off between expected cost and cash flow variance that buyers should consider when choosing between physical and virtual PPAs. Moreover, advanced reoptimization techniques significantly impact the ability to manage this trade-off.

Optimal operation of an electricity-hydrogen DC microgrid with integrated demand response

Uncertainties introduced by the high penetration of renewable sources, plug-in-hybrid-electric vehicle load demand, and limited capacity of firm generation available in a DC microgrid make the energy scheduling task rather challenging. This paper proposes a decentralized energy management scheme with a real-time pricing-based demand response implementation for a DC microgrid, considering the sectoral coupling between electricity and hydrogen energy. The objectives of the scheduling strategy are to maximize the profit of the DC microgrid operator and reduce the cost of energy use by the consumers, considering the interaction and interdependence of the electrical and hydrogen systems with a detailed DC microgrid network model and associated network constraints. The DC microgrid operator schedules flexible resources under its control (power procurement from the upstream grid, microturbines, battery energy storage, hydrogen storage, electrolyzer and fuel cell) and sets real-time prices. The consumers set their consumption patterns according to the real-time price. The DC microgrid operator side flexibilities are coordinated with the consumer side flexibilities (thermostatically controlled load like air-conditioner and plug-in-hybrid electric vehicle) using the decentralized “Alternating Direction Method of Multipliers” approach. The probabilistic Copula theory models correlated input uncertainties. Simulation results on a six-bus DC microgrid test system reveal that the operating cost of the DC microgrid operator reduces by ∼11.06% while the energy use cost of consumers reduces by ∼4.80% using the proposed approach for the system under study.

Reviewing the overcapacity claim: Insights from Kenya’s electricity sector

Typical approaches to assessing excess generation capacity in African electricity systems have considered the nameplate capacities of existing generation plants, the planned generation capacity, and peak load. However, the omission of variables such as the condition of transmission and distribution infrastructure, the age of existing power plants, and whether generation capacity is intermittent (as in the case of wind or solar) or subject to climate impacts (as in the case of hydropower) has caused such assessments to be misleading. This can result in misguided public policy and power procurement processes that are poorly matched to the needs of evolving power systems. In this paper, we analyze the case of Kenya to show how power system planning must consider these key factors that are often ignored. Far from having excess capacity as has been repeatedly reported, the Kenyan grid has limited capacity to take up additional load at present.

Cost-Benefit Analysis Tool for Deploying Solar Irrigation Pumps: The Case for Rajasthan

This technical note discusses a cost benefit analysis tool to assess the economic viability of Solar Irrigation Pumps by calculating the monetary benefits to stakeholders such as distribution companies, the Rajasthan state government, and farmers by creating an additional income source. Feasible costs and assistance from DISCOMs and the state government will embolden more farmers to opt for solar irrigation pumps. Additionally, this technical note also highlights the reduced carbon footprint resulting from the avoided power procurement costs by DISCOMs.

A multi-timescale energy scheduling model for microgrid embedded with differentiated electric vehicle charging management strategies

This paper presents a novelty energy management model embedded with differentiated charging management strategies for optimal scheduling of the microgrid (MG), including electric vehicles (EVs) and renewable energy sources (RES) in similar official buildings and industrial parks. The study firstly synthetically considers the objectives of multiple stakeholder entities in the MG and various uncertainties and employs a multi-timescale energy schedule model to satisfy each entity’s different objective and optimize the power procurement strategy. In the day-ahead stage, an enhanced variant multi-objective particle swarm optimization algorithm (EVMOPSO) is used to solve the multi-objective equilibrium optimization model, while in the real-time stage, a rolling correction model based on model predictive control (MPC) is introduced. Secondly, considering the significant diversity of driving behaviors of the EV users unique to the MG above, this study presents a set of differentiated charging management strategies for the first time in the multi-timescale energy management model. These strategies are based on credibility, which assigns different credibility levels to users by evaluating the degree of regularity of their driving behaviors to assign corresponding charging and price strategies. Simulation results verify the method’s practicality and validity, and the model’s robustness is also verified by sensitivity analysis.

Integrating spatial analytics in power system planning techniques for the green energy transition

Abstract. Fossil fuel energy generation contributes significantly to greenhouse gas emissions globally. Energy transition towards sustainable, low-carbon energy needs to occur. South Africa has pledged to achieve a net-zero carbon economy by 2050 and in-line with this energy transition. The country has implemented the Renewable Energy Independent Power Procurement Programme (REIPPPP) to promote private investment within the energy sector. As new capacity is constructed, it requires the national grid to move from a vertically integrated passive power model to a deregulated active power flow due to the distributed sources of energy. In this paper, a method for connecting distributed power producers is introduced by providing candidate locations for Network Planners to develop insights for optimal placement of collector stations that connect multiple power producers in an orderly manner onto the electrical grid. This method uses buffer distances and Voronoi polygons from the stations on the national grid in order for the power producers to be aggregated and assigned connection to a collector station. Furthermore, this paper proposes a model for potential power producers that allows Network Planners to adequately plan for future grid access applications.

Sowing the seeds of change: Policy feedback and ratcheting up in South African energy policy

More ambitious and stringent policy intervention is required to accelerate the transition to renewable energy technologies. The ratcheting-up of policy ambition hinges on the political feasibility of policy change. Positive policy feedback can, in theory, enhance the political feasibility of ratcheting-up by creating pro-change constituencies and policy learning. To analyze the empirical mechanisms through which policy feedback operates, in this study, we analyze two energy policy instruments in South Africa. We examine how the Renewable Energy Independent Power Procurement Program (REIPPP), a renewable energy auction program for niche support, affected the re-design of the Integrated Resource Plan (IRP), a central energy planning instrument. We use a qualitative case study approach, drawing on a large dataset of policy documents, public consultation responses and expert interviews. We show that REIPPP, through mechanisms of largely positive interpretive and resource feedback, has increased the political feasibility of more ambitious, pro-renewable energy planning in IRP. Our case thus demonstrates positive political feedback from the market creation to the central planning policy instrument. The findings suggest that the temporal sequencing of (re-designing) policy instruments can, under certain conditions, enable dynamic ratcheting up of energy policy mixes and thus sow the seeds for major policy change.

An optimization approach for the economic dispatch incorporating renewable energy resources into Lesotho power sources portfolio

Electricity demand in Lesotho has surpassed the main domestic generation of 72-MW hydropower station with 59% capacity deficit currently met by imports from South Africa and Mozambique through costly fixed bilateral contracts. With the abundant renewable energy sources in Lesotho, independent power producers could be incentivized to erect solar PV plants and wind farms to increase local energy security at lower cost and diversify utility's power mix. This article develops a power dispatching approach that prioritizes solar PV and wind generators to aid hydropower station meet demand and only be backed by imports. It uses the Monte Carlo approach to simulate generation adequacy analysis in order to establish monthly average expected demand not supplied (EDNS) and loss of load probability (LOLP) for the baseline case and three dispatch scenarios. According to the analysis, the EDNS for all simulated scenarios never drops to 0 MW, while the LOLP only reaches a minimum of 52% for the scenario with all local renewable energy generators combined. Furthermore, main grid energy imports can be minimized by 22.3% with the introduction of 50-MW solar PV and by 40.2% for 58-MW wind farms. A 59.7% minimization can be obtained by combining solar PV at 50-MW, wind farms at 58-MW and MHP at 72-MW. These introductions would lead to subsequent reductions in power procurement costs of about 6.2% for solar PV alone and 1.11% for both solar PV and wind. However, the inclusion of wind energy alone would lead to slight cost increase of about 0.6%.

Blockchain-Based Market Procurement of Reactive Power

A flexible and adaptable market procurement of reactive power has the potential to improve network efficiency, voltage stability, and operational costs. In Europe, such a dynamic procurement must be in accordance with the European Union directive EU 2019/944 on non-frequency ancillary services. In accordance with this situation, a blockchain-based framework of market procurement of reactive power is proposed and presented in this paper. The devised framework is in alignment with the European Union’s directive to establish a non-discriminatory, transparent, and free market. Moreover, the blockchain-based framework is applicable at all network levels and allows for the variety of different distributed resources to participate. A two-layer blockchain topology is proposed to overcome scalability and transaction time issues. The first main-layer blockchain acts as the agent for trust and guarantees the immutability of data as well as the remuneration of participating market players. The second-layer blockchain facilitates direct access to tendering processes or auctions, fast transactions, and low transaction fees for involved stakeholders. Additionally, a decentralized oracle network is proposed to integrate external data into the second-layer blockchain. Data required for verifying the physical reactive power transactions are delivered by smart meters. The entire procurement process is automated by deploying smart contracts at the various blockchain layers. Thus, in principle, the involved stakeholders are the system operators and market players. For the purpose of validation, the holistic market procurement process is demonstrated and analyzed in a hardware-in-the-loop environment involving reactive power procurement at the distribution network level.

Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM

AbstractThis paper presents the genetic algorithm (GA) and particle swarm optimization (PSO) based frequency regulation for a wind‐based microgrid (MG) using reactive power balance loop. MG, operating from squirrel cage induction generator (SCIG), is employed for exporting the electrical power from wind turbines, and it needs reactive power which may be imported from the grid. Additional reactive power is also required from the grid for the load, directly coupled with such a distributed generator (DG) plant. However, guidelines issued by electric authorities encourage MGs to arrange their own reactive power because such reactive power procurement is defined as a local area problem for power system studies. Despite the higher cost of compensation, static synchronous compensator (STATCOM) is a fast‐acting FACTs device for attending to these reactive power mismatches. Reactive power control can be achieved by controlling reactive current through the STATCOM. This can be achieved with modification in current controller scheme of STATCOM. STATCOM current controller is designed with reactive power load balance for the proposed microgrid in this paper. Further, gain values of the PI controller, required in the STATCOM model, are selected first with classical methods. In this classical method, iterative procedures which are based on integral square error (ISE), integral absolute error (IAE), and integral square of time error (ISTE) criteria are developed using MATLAB programs. System performances are further investigated with GA and PSO based control techniques and their acceptability over classical methods is diagnosed. Results in terms of converter frequency deviation show how the frequency remains under the operating boundaries as allowed by IEEE standards 1159:1995 and 1250:2011 for integrating renewable‐based microgrid with grid. Real and reactive power management and load current total harmonic distortions verify the STATCOM performance in MG. The results are further validated with the help of recent papers in which frequency regulation is investigated for almost similar power system models. The compendium for this work is as following: (i) modelling of wind generator‐based microgrid using MATLAB simulink library, (ii) designing of STATCOM current controller with PI controller, (iii) gain constants estimation using classical, GA and PSO algorithm through a developed m codes and their interfacing with proposed simulink model, (v) dynamic frequency responses for proposed grid connected microgrid during starting and load perturbations, (vi) verification of system performance with the help of obtained real and reactive power management between STATCOM and grid, and (vii) validation of results with available literature.

Peak-to-average ratio incentive scheme to tackle the peak-rebound challenge in TOU pricing

Time of use (TOU) pricing scheme reduces the peak demand, and electricity procurement costs by shifting flexible loads from peak to off-peak hours. The electricity price is known to the end-users a day ahead or a season in TOU pricing. When penetration of home energy management system (HEMS) and automation in a distribution system is high, the TOU pricing may cause peak rebounds in the grid load profile due to deferrable load accumulation during low price periods. It may cause suppliers’ economic loss, power imbalance, voltage violations, increased power loss in the network, and may overload the transformers and distribution lines. This paper proposes a pricing scheme for residential customers to eliminate the deferrable load accumulation during low price periods of TOU pricing. The proposed pricing scheme considers peak to average ratio (PAR) incentive on energy consumption charge for each price period of TOU pricing. The PAR incentive is included in HEMS at customers’ premises and supplier’s price calculation. The proposed PAR incentive scheme is implemented in 200 houses with different appliances and different energy requirements. The proposed PAR incentive scheme successfully avoids the deferrable load accumulation during low price periods of TOU pricing. The cost of power procurement in the proposed PAR incentive scheme is found lesser than other compared schemes for load profiles with and without solar PV. The proposed incentive scheme also reduces the electricity bills of the customers.

Industrial Flexibility as Demand Side Response for Electrical Grid Stability

Electricity markets are currently experiencing a period of rapid change. The intermittent nature of renewable energy is disrupting the conventional methods used in operational planning of the electrical grid, causing a shift from a day-ahead forecast policy to a real-time pricing of delivered electric power. A path towards a more renewable, robust and intelligent energy system is inevitable but poses many challenges to researchers and industry. In the field of process industry, strategies based on demand side response are receiving attention and could represent a partial solution for this challenge. Coordination between production scheduling and procurement of electric power is of high importance and can contribute to reducing cost and emissions associated with production. A methodology to quantify such benefits is presented here with a case study, which reveals the potential benefits of flexible operation. In this case, the minimum compensation for flexibility services ranges between 5 and 20 € per unit (MWh) of restricted power. However, such a compensation depends on geographic location (electricity prices) and the frequency of restrictions. The method follows a rolling scheduling approach that provides optimization of the short-term schedule. This work introduces the concept of representing flexible processes as ‘equivalent batteries’ which store electricity from low-cost periods as intermediate products and consume the embedded energy during high-cost periods. Cost related to providing flexibility combined with the profits from optimized process scheduling contribute toward monetization of flexibility as an ancillary service for the grid. Balancing this service with the cost of implementing DSR solutions provides a means for calculating a pricing strategy for grid flexibility.

Uncertainty-aware optimal dispatch of building thermal storage portfolios via smoothed variance-reduced accelerated gradient methods

The rapid penetration of uncertain renewable energy resources into the power grid has made generation planning and real-time power balancing a challenge, prompting the need for advanced control on the demand-side. Although a grid-integrated building portfolio has been studied by coordinating building-level flexible energy resources, to reap further benefits, the need to develop a scalable supervisory control framework with computational efficiency is paramount. In this work, we introduce an uncertainty-aware transactive control framework for a large-scale building portfolio with thermal energy storage (TES) using a decomposition-based approach. We propose a day-ahead decision making framework for the power procurement problem, which is cast as a two-stage stochastic optimization problem. To solve this problem, we propose a smoothed variance-reduced accelerated gradient method. Notably this framework allows for parallelization in computing the sampled gradient. Preliminary numerics demonstrate the scalability and computational efficiency of the proposed algorithm to apply to the control framework with respect to the existing algorithm. Substantial energy cost savings were observed for the stochastic control framework over all the validation scenarios. This study provides further insights into the supervisory controller development for building portfolio-based grid services that can help advance electrification goals through coordination of energy storage assets.

Sensitivity analysis of factors relevant to extreme imbalance between procurement plans and actual demand: Case study of the Japanese electricity market

In a liberalized power system, operators control the power system to compensate for imbalances, which are the differences between the scheduled power procurement in electricity markets and the actual power supply. Interpreting the influence of factors that affect extremely large imbalances (i.e., extreme imbalance events) enables power system operators to implement appropriate system operation plans. Conventionally, such imbalance analysis has focused only on a limited number of factors and described variation in imbalance by utilizing highly interpretable statistical models, assuming that the probability of imbalance events varies monotonically with changes in those factors. In particular, sensitivity analysis of such models can be a powerful tool to support the decision-making of system operators. However, when dealing with the increasingly complex behavior of markets involving many actors, a flexible statistical analysis framework is required to identify informative factors among the various observable quantities, and to describe nonmonotonic relationships when essentially necessary. This study focuses on the statistical behavior of the odds ratio of the extreme imbalance events by concentrating on an inherently large number of explanatory variables. The authors propose a model-based approach using a class of partially linear additive models and a variable selection method to reveal the statistical relationships between the relevant variables and extreme imbalance events. The framework further provides an analysis scheme to determine the response sensitivity of relevant variables to the odds ratio of extreme imbalance events. The usefulness of the framework was demonstrated by applying the approach to a real-world dataset collected in the Japanese electricity market system. The results show that the proposed approach based on partially linear additive models works well to describe the extreme imbalance events; the constructed models derive the interpretable sensitivity curves to clarify the impact of informative variables to extreme events, while identifying monotonicity/nonmonotonicity among variables.

A social cost benefit analysis for the procurement of reactive power: The case of Power Potential

This paper quantifies the benefits of introducing reactive power markets that promote the participation of distributed energy resources (DER) in a coordinated way, between the electricity system operator and the electricity distribution utilities. The contribution that DER could make by displacing conventional network assets in supplying reactive power support is evaluated in the context of a case study, the Power Potential (PP) project in Great Britain. We discuss the rising need for absorptive (leading) reactive power in the PP trial area, driven by the rapid connection of renewable generation in an area of low demand growth. A social cost benefit analysis (SCBA) is performed to quantify the net benefits, with sensitivities regarding bid prices, % of DER participation, time horizons. Price information from the PP live trial conducted between January and March 2021 is also used to evaluate the robustness of the SCBA and to estimate benefits using actual prices. Our results suggest that energy consumers could save from 8 to 21% of business as usual asset costs by 2050. The introduction of actual bid prices increases these savings by around 3% of business as usual asset costs out to 2050. Potential sources of additional benefits on top of those identified in the SCBA are also discussed.

Real Time Market (RTM) at Indian power exchanges: Need, short term assessment and opportunities

In India, short term electricity market realises on power exchanges to trade standard contracts on intraday and day ahead horizon. In the absence of contracts on real time horizon, market participants often used to exploit frequency based grid balancing mechanisms. This led to the concerns on grid safety and security. Therefore, to address this issue, the policy makers formulated ‘Real Time Market (RTM)’ to offer contracts on real time horizon. RTM was introduced in 2020 and in the short span of time, it has attracted significant liquidity to become second highest avenue in terms of number of transactions taken place. This paper elaborates on these developments and narrows down its scope gradually. First, the paper briefly provides an overview of short term electricity market in India inter alia describing power trading and power exchanges. The paper then elaborates on the erstwhile issues of real time power procurement and misappropriation of deviation settlement mechanism and ancillary services by the market participants. The paper while discussing these, derives the necessity of RTM and opportunities which it offers. In last, paper provides a short term assessment of RTM and concludes it with few policy recommendations.