Electricity Procurement Research Articles

Competitiveness and structural change in Salatiga economy

The era of globalization has forced all regions at an increasingly fierce and sharp level of competition, both directly and indirectly, both in the domestic and international markets. One approach to overcoming these challenges is through a regional development that refers to increasing regional competitiveness as the basis for regional growth. The purpose of this study was to determine the leading sectors and shift in the share of economic sectors in Salatiga. The analytical method used in this research is the Estaban Marquillas Shift-Share (SS) analysis. The results showed that the sectors that had competitive advantages and specialization were as follows: (i) 2013, namely Water Supply, Waste Management, Waste and Recycling, Construction, Wholesale and Retail Trade; Car and Motorcycle Repair, Transportation and Warehousing, and Real Estate; (ii) in 2017, namely the Provision of Accommodation and Food and Beverage, Corporate Services, and Educational Services. Besides that, in Salatiga City, it can be said that the economic structure has shifted, namely Agriculture, Forestry, and Fisheries; Processing industry; Electricity and Gas Procurement; Water Supply, Waste Management, Waste and Recycling; Construction; Wholesale and retail trade; Car and Motorcycle Repair; Transportation and Warehousing; Provision of Accommodation and Food and Drink; Real Estate; Company Services; Educational Services.

Risk-Constrained Optimal Chiller Loading Strategy Using Information Gap Decision Theory

This paper presents a novel framework for economic cooling load dispatch in conventional water-cooled chillers. Moreover, information gap decision theory (IGDT) is applied to the optimal chiller loading (OCL) problem to find the optimum operating point of the test system in three decision-making modes: (a) risk-neutral approach, (b) risk-aversion or robustness approach, and (c) risk-taker or opportunistic approach. In the robustness mode of the IGDT-based OCL problem, the system operator enters a desired energy cost value in order to find the most appropriate loading points for the chillers so that the total electricity procurement cost over the study horizon is smaller than or equal to this critical value. Meanwhile, the cooling load increase is maximized to the highest possible level to find the most robust performance of the benchmark grid with respect to the overestimated load. Similarly, the risk-taker optimization method finds the on/off status and the partial load ratio (PLR) of the chillers in order to keep the total energy cost as low as the given cost function. In addition, the minimum value of cooling load decrease can be found while satisfying the refrigeration capacity of the chiller and the load-generation balance constraint. Thus, a mixed-integer non-linear programming problem is solved using the branch and reduce optimization (BARON) tool of the generalized algebraic mathematical modeling system (GAMS) for a five-chiller plant, to demonstrate that IGDT is able to find a good solution in robustness/risk-taker OCL problem.

Design and management of a distributed hybrid energy system through smart contract and blockchain

This paper studies the design and management of a distributed energy system incorporating renewable energy generation and heterogeneous end-users from residential, commercial and industrial sectors. A hierarchical framework is first proposed for the energy demand side management through peer-to-peer exchange of energy information in the real-time market. The heterogeneity of demand flexibility associated with different types of users is reflected in the framework with inter-sectorial interactions modelled by a non-cooperative game. The inherent uncertainty of renewable generation is also considered with the technique of receding horizon optimization. Subsequently, smart contracts and decentralized identifier guaranteed by blockchain technologies are implemented to create a seamless, secured and efficient distributed energy system. Finally, a Singapore-based case study is conducted and the results show that with effective interactions among participants, electricity consumption of the entire energy system closely tracks the generation pattern of renewable resources, resulting in a significantly flattened schedule of grid electricity procurement.

Convergence and Potential Economic Development in the Special Region of Yogyakarta

This study aims to determine whether there is a lag between a region with another, to determine whether the regions with low income will be able to catch up with regions with higher income. The objectives of this study are to analyze the convergence that might occur in Yogyakarta and analyze the potential economic sectors in economic development in Yogyakarta. This study used panel secondary data, the data were obtained from 5 regions in Yogyakarta from 2010-2015. The methods were panel data regression, location quotient, dynamic location quotient, and shift share. The result showed that there was no convergence, but there was divergence, and competitive and specialized sectors in regencies / cities in Yogyakarta were agricultural, forestry, and fishing sector, mining and excavation sector, processing industry sector, procurement of electricity and gas sector, water supply, waste management and recycling sector, construction sector, and transportation and trade sector.Keywords: Convergence, Potential Sector, Economic Development.

Acceleration for the Administration Process of Project Contract in Power Plant Service Company using DMAIC

Indonesian Government has committed to provide electricity to its citizen throughout Indonesia. Thus, PT Perusahaan Listrik Negara (PT PLN), an Indonesian Government-owned company, issued the Electricity procurement business plan (RUPTL) every year that shows the increasing demand of electricity of people. As a result, both increasing electrical capacity and the number of development of power plant in Indonesia must be arranged. Those facts can be opportunities for Power Plant Service Companies. The more power plants will be built, the more chances for company to get the project of power plant development. On the other side, Power Plant Service Companies often have an administrative issue, which contract documents takes overlong to be completed. This research aims to speed up the administrative process of document contract completion for Power Plant Service Companies. Define, Measure, Analyze, Improve, and Control (DMAIC) method has been chosen to be implemented in a Power Plant Service Companies. The result shows that lead time of document completion has been increase for 52.87 percent.

ANALISIS SEKTOR-SEKTOR EKONOMI TERHADAP PENERIMAAN DAERAH KABUPATEN WAJO

This study aims to find out the basic economic sector, strategic economic sectors and the potential to be developed as supporting regional revenues in Wajo District. The study was descriptive quantitative research which employed gross regional domestic product data and rate of economic growth in 2012-2016. The method analysis used Location Quotient (LQ), Shift Share, and Klassen Typology. The results of the study reveal that the base sectors are agriculture, forestry and fishery, mining and excavation, procurement of electricity and gas, large and retail trade, and car and motorcycle repair; whereas, other sectors are included as non-base. The results of shift share method reveal that the competitive sectors are agriculture, forestry and fishery, government administration, mandatory defense and social security, educational services, transportation and warehousing, real estate, financial services, information and communication, health services and social activities, other services, provision of accommodation and food and beverage, company services, and procurement of electricity and gas. The result of Klassen typology indicates that there are two superior sectors, those are agriculture, forestry and fishery, and procurement of electricity and gas which are in quadrant I position

A Short-Term Decision Model for Electricity Retailers: Electricity Procurement and Time-of-Use Pricing

This paper establishes a short-term decision model, based on robust optimization, for an electricity retailer to determine the electricity procurement and electricity retail prices. The electricity procurement process includes purchasing electricity from generation companies and from the spot market. The selling prices of electricity for the customers are based on time-of-use (TOU) pricing which is widely employed in modern electricity market as a demand response program. The objective of the model is to maximize the expected profit of the retailer through optimizing the electricity procurement strategy and electricity pricing scheme. A price elasticity matrix (PEM) is adopted to model the demand response. Also, uncertainty in spot prices is modeled using a robust optimization approach, in which price bounds are considered instead of predicted values. Using a robust optimization approach, the retailer can adjust the level of robustness of its decisions through a robust control parameter. A case study is presented to illustrate the performance of the model. The simulation results demonstrate that the developed model is effective in increasing the expected profit of the retailer and flattening the load profiles of customers.

Uncertainty-based electricity procurement by retailer using robust optimization approach in the presence of demand response exchange

In this paper, robust optimization approach is proposed to handle market price uncertainty in which the upper deviation from forecasted value of pool price will be considered for risk analysis for a retailer. Objective of this paper is minimization of energy procurement cost for retailer from pool market, forward contracts and demand response programs (DRP). Therefore, three new designs of demand response (DR) programs have been proposed in this study which retailer can use to procure their required energy. These new DR schemes consist of pool-order option, forward-DR and reward-based DR contracts. The robust optimization approach examines the retailer’s performance at risk-averse and risk-neutral strategies, in which risk-neutral explains the normal performance of retailer, and risk-averse explains the risky performance of retailer. The proposed robust scheduling of retailer is modeled via MIP model which can be solved using CPLEX solver under GAMS software. The achieved results show that the retailer cost in risk-neutral strategy is reduced due to use of new DR schemes. Also, in risk-averse strategy, retailer cost reduction is more than the risk-neutral strategy use of new DR schemes.

Distributed Scalable Autonomous Market-Based Demand Response via Residential Plug-In Electric Vehicles in Smart Grids

Flexibility in power demand, diverse usage patterns and storage capability of plug-in electric vehicles (PEVs) grow the elasticity of residential electricity demand remarkably. This elasticity can be used to form the daily aggregated demand profile and/or alter instantaneous demand of a system wherein a large number of residential PEVs share one electricity retailer. In this paper, we propose a demand response technique to manage vehicle-to-grid enabled PEVs’ electricity assignments (charging and discharging) in order to reduce the overall electricity procurement costs for a retailer bidding to a two-settlement electricity market, i.e., a day-ahead and a spot or real-time (RT) market. We show that our approach is decentralized, scalable, fast converging and does not violate users’ privacy. Extensive simulations show significant overall cost savings can be achieved for a retailer bidding to an operational electricity market by using the proposed algorithm. This technique becomes more needful when the power grid accommodates a large number of intermittent energy resources. There, RT demand altering is crucial due to more likely contingencies and hence more RT price fluctuations and even occurring the so-called black swan events . Finally, such retailer could offer better deals to customers as well to stay competitive.

Cost-Optimal Flexibilization of Drinking Water Pumping and Treatment Plants

This paper examines potential cost savings attained through the flexible operation of water treatment plants and drinking water pumping and the benefits gained by investing in extended water storage capacities that enhance flexibility. An existing plant in South Germany serves as an example. Mixed-integer linear programming is used to model the plant and the electricity procurement on the German spot market while ensuring the security of supply. Cost optimization considering the different cost components reveals potential cost savings through flexible operation. The paper evaluates the benefits of building additional water reservoirs and rates the financial effects of the measures used to enhance the flexibility of water pumping and treatment plants.

Joint Bidding and Geographical Load Balancing for Datacenters: Is Uncertainty a Blessing or a Curse?

We consider the scenario where a cloud service provider (CSP) operates multiple geo-distributed datacenters to provide Internet-scale service. Our objective is to minimize the total electricity and bandwidth cost by jointly optimizing electricity procurement from wholesale markets and geographical load balancing (GLB), i.e., dynamically routing workloads to locations with cheaper electricity. Under the ideal setting where exact values of market prices and workloads are given, this problem reduces to a simple linear programming and is easy to solve. However, under the realistic setting where only distributions of these variables are available, the problem unfolds into a non-convex infinite-dimensional one and is challenging to solve. One of our main contributions is to develop an algorithm that is proven to solve the challenging problem optimally, by exploring the full design space of strategic bidding. Trace-driven evaluations corroborate our theoretical results, demonstrate fast convergence of our algorithm, and show that it can reduce the cost for the CSP by up to 20% as compared with baseline alternatives. This paper highlights the intriguing role of uncertainty in workloads and market prices, measured by their variances. While uncertainty in workloads deteriorates the cost-saving performance of joint electricity procurement and GLB, counter-intuitively, uncertainty in market prices can be exploited to achieve a cost reduction even larger than the setting without price uncertainty.

Design and performance investigation of a biogas fueled combined cooling and power generation system

Nowadays, different renewable sources and energy storages are attracting world attention due to the major concerns about the excessive emissions and the global energy crisis. Hence, this paper studies design and performance investigation of a biogas fueled building cooling and power system, which comprises of an air compressor, an air preheater, a combustion chamber, a gas turbine, some compression chillers and aggregated plug-in electric vehicles. In the proposed coproduction facility, biogas is used as an alternative fuel to reduce the total greenhouse gas emissions and increase the economic saving in the consumption of fossil fuels. The feasibility and robust performance of this microgrid is evaluated under extremely-hot summer days. Three compression chillers are installed to satisfy total cooling demand of a large hotel building located in Ahwaz, Iran. Moreover, the total energy requirement of chillers and building electricity demand is supplied through the biogas driven gas turbine cycle. A mid-high temperature waste heat is recovered from the exhaust gases of gas turbine to be used in the air preheating stage. A comprehensive thermodynamic analysis is developed to solve a mixed integer non-linear programming problem with the aim of minimizing total electricity procurement cost of the proposed zero-emission cogeneration micro-plant taking into account the operational constraints of gas turbine cycle, compression chillers, and electric drive vehicles.

Energy Collectives: A Community and Fairness Based Approach to Future Electricity Markets

While power system organization has evolved from a hierarchical structure to a more decentralized model, electricity markets are still not up to date with the ongoing transformation toward more consumer-centric economies. As information and communication technologies are broadly adopted, they allow prosumers to have a more proactive role in power system operation. This work introduces the concept of energy collectives, as a community-based electricity market structure. We find that when prosumers are allowed to share energy at community level, the overall electricity procurement for the community reflects prosumers' preferences. We show that community members can be influenced by a supervisory third-party in charge of interfacing with the market and system operator and of guaranteeing the collective common agreements. We simulate a number of test cases and apply typical principles from analysis of communication networks and distributed systems to assess community fairness.

Two-Stage Optimal Scheduling of Electric Vehicle Charging Based on Transactive Control

In this paper, a two-stage optimal charging scheme based on transactive control is proposed for the aggregator to manage day-ahead electricity procurement and real-time electric vehicles (EV) charging management in order to minimize its total operating cost. The day-ahead electricity procurement considers both the day-ahead energy cost and expected real-time operation cost. In the real-time charging management, the cost of employing the charging flexibility from the EV owners is explicitly modeled. The aggregator uses a transactive market to manage the real-time charging demand to provide the regulating power. A model predictive control-based method is proposed for the aggregator to clear the transactive market. The real-time charging decisions of the EVs are determined by the clearing of the proposed transactive market according to the real-time requests and preferences of the EV owners. As such, the aggregators decisions in the real-time EV charging management and regulating power markets can be optimized. At the same time, the charging requirements and response preferences of the EV owners are respected. Case studies using real world driving data from the Danish National Travel Surveys were conducted to verify the proposed framework.

Optimizing residential heating and energy storage flexibility for frequency reserves

The increase in intermittent renewable generation motivates participation of also the electricity consumers in maintaining the production–consumption balance of the electrical grid. This paper proposes a distributed price-based optimization scheme for involving a population of consumers in day-ahead procurement of electricity and frequency containment reserves. Energy storage charging and heating of residential houses are planned before the operating day, while taking into account uncertainties in the day-ahead electricity and reserves markets, weather conditions, and realized frequency. The proposed approach is formulated as stochastic quadratic programming problems and coordinated using a parallelized formulation of the alternating direction method of multipliers (ADMM). Chance constraints for the storage state of charge variations under uncertain reserve activation are formulated as second-order cone constraints. The numerical results illustrate the potential benefits of including consumers in the optimization of reserves.

Optimal Energy Procurement for Geo-distributed Data Centers in Multi-timescale Electricity Markets

Multi-timescale electricity markets augment the traditional electricity market by enabling consumers to procure electricity in a futures market. Heavy power consumers, such as cloud providers and data center operators, can significantly benefit from multi-timescale electricity markets by purchasing some of the needed electricity ahead of time at cheaper rates. However, the energy procurement strategy for data centers in multi-timescale markets becomes a challenging problem when real world dynamics, such as spatial diversity of data centers and uncertainties of renewable energy, IT workload, and electricity price, are taken into account. In this paper, we develop energy procurement algorithms for geo-distributed data centers that utilize multitimescale markets to minimize the electricity procurement cost. We propose two algorithms. The first algorithm provides provably optimal cost minimization while the other achieves near-optimal cost at a much lower computational cost. We empirically evaluate our energy procurement algorithms using real-world traces of renewable energy, electricity prices, and workload demand. Our empirical evaluations show that our proposed energy procurement algorithms save up to 44% of the total cost compared to traditional algorithms that do not use multi-timescale electricity markets or geographical load balancing.

An Analysis of Regional Economic Advantage and Specialization (Shift-Share Esteban Marquillas Model Approach) and Analysis of Its Accessibility in Banyumas Regency

This study aimed (1) to identify the competitive advantage, specialization and effect of sectors allocation in Banyumas Regency in 2010-2015; (2) to identify region with the most advantageous position in terms of accessibility level. The result indicated that (1) competitive and specialized sectors in Banyumas Regency were mining and excavation sector, procurement of electricity and gas sector, construction sector, big scale trade and retail, car and motorcycle repair, transportation and warehousing sector, provision of accomodation and food and beverage sector, information and communication sector, financial and insurance services sector, real estate sector, corporate service sector, government administration sector, defense and compulsory social security, education service sector, health service and social activities sector, and other service sectors. (2) In terms of accessibility, Banyumas Regency had the second advantageous position after Purbalingga Regency when compared to regencies in Karesidenan Barlingmascakeb. Based on the accessibility of each sub-district in Banyumas Regency, the sub-district with the most advantageous position to interact with the sub-districts in Banyumas Regency was Tambak sub-district. This can be seen from the lowest CQ value of Tambak sub-district.Keywords: Shift-Share Esteban Marquillas, Accessibility, Connectivity Quotient.

Stochastic Dynamic Pricing for EV Charging Stations With Renewable Integration and Energy Storage

This paper studies the problem of stochastic dynamic pricing and energy management policy for electric vehicle (EV) charging service providers. In the presence of renewable energy integration and energy storage system, EV charging service providers must deal with multiple uncertainties-charging demand volatility, inherent intermittency of renewable energy generation, and wholesale electricity price fluctuation. The motivation behind our work is to offer guidelines for charging service providers to determine proper charging prices and manage electricity to balance the competing objectives of improving profitability, enhancing customer satisfaction, and reducing impact on power grid in spite of these uncertainties. We propose a new metric to assess the impact on power grid without solving complete power flow equations. To protect service providers from severe financial losses, a safeguard of profit is incorporated in the model. Two algorithms-stochastic dynamic programming (SDP) algorithm and greedy algorithm (benchmark algorithm)-are applied to derive the pricing and electricity procurement policy. A Pareto front of the multi-objective optimization is derived. Simulation results show that using SDP algorithm can achieve up to 7% profit gain over using greedy algorithm. Additionally, we observe that the charging service provider is able to reshape spatial-temporal charging demands to reduce the impact on power grid via pricing signals.

ANALISIS IDENTIFIKASI SEKTOR PEREKONOMIAN SEBAGAI SEKTOR BASIS DAN SEKTOR POTENSIAL DI KOTA BOGOR

This study aims to determine the sectors that become the basis sector and non-base in the city of Bogor, then to know the performance of each sector in the city of Bogor, and to know the sector that became a potential sector in the city of Bogor. The research was conducted by using Location Quotient / LQ method. In the city of Bogor, from the period of 2011 to 2015 there is one sector of the highest base of electricity and gas procurement sector. Of the 16 economic sectors, the economic sector including the basic sector in 2011 is the procurement of electricity and gas, the transportation and warehousing sectors, the financial services sector and insurance and other services sectors. In addition to these four sectors in 2011, in 2012-2015, it increased by 7 sectors, to 11. The additional sectors were water supply, waste management, waste, construction, and large and retail trade sectors; car and motorcycle repair, accommodation, food and beverage sector, information and communications sector, corporate services sector, health services sector and social activities. then that included in the non-base sector is the other five sectors.In the city of Bogor the performance of the economic sector can be explained that the sector that has the average value of Regional Growth (PR) is the highest sector of procurement of electricity and gas. This value indicates that the growth of electricity and gas procurement sector in Bogor City is higher than that of Indonesia. In Bogor City from 2011 to 2015 included in the potential sector is sector. Then from these sectors, the most potential sector or the most potential sector is the electricity and gas procurement sector.From the results of research that has been obtained by researchers, the researchers provide suggestions that must be taken are as follows: First, the base sector should be more maintained and developed again without exclude development against other sectors. The electricity and gas procurement sector that contributes to the GRDP should be developed by industrializing in cooperation with investors, so that the contribution from the gas and electricity procurement sector can increase again. Second, planning in development should be given to sectors that have the potential to be developed as a top priority so that development can be carried out more optimally.

Long-Term Electricity Procurement for Large Industrial Consumers under Uncertainty

Due to the need for adjusting plant operations to time-varying electricity prices and changing product demand, managing the procurement of electricity in power-intensive businesses has become a major challenge. Large industrial electricity consumers often enter into long-term contracts with favorable rates. However, such power contracts require the consumers to commit themselves to the amount that they are going to purchase months in advance when future demand is not yet known with certainty. In this work, we simultaneously optimize long-term electricity procurement and production planning while considering uncertainty in product demand. We propose a multiscale multistage stochastic programming model in which a 1-year planning horizon is divided into seasons, with each season represented by two characteristic weeks; also, each season corresponds to a stage at which the demand for that season is revealed. The progressive hedging algorithm is applied to solve industrially relevant large-scale instances of t...